One organisation had 331 monthly active agents. Another had over 1,000. A third partner's customer base? Thousands of agents already running. And not one of these environments had a governance framework in place. No registry. No lifecycle management. No visibility into what these agents were doing, what data they were accessing, or who was responsible when something went wrong.

If you're a Microsoft Partner reading this and thinking "that sounds like my customers," you're probably right. And if you're thinking "we should really be helping with that," you're definitely right.

This post is a practical signpost. Microsoft 365 E7 (the "Frontier Suite") goes GA on 1 May 2026, and Agent 365 ships with it. The window for partners to build services around this is right now, not after launch. I want to lay out where the opportunity sits, how two very different types of customer end up needing the same thing from you, and what you can go and do about it on Monday morning.

What Are We Actually Talking About?

Let me ground this quickly, because the naming can be confusing.

Microsoft 365 E7 is the first new enterprise tier since E5 launched in 2015. It bundles four things together at $99 per user per month:

• Microsoft 365 E5 (the full productivity, security, and compliance stack you already know)
• Microsoft 365 Copilot (the AI assistant, now included rather than bolted on)
• Microsoft Entra Suite (identity, Zero Trust Network Access, internet access controls)
• Agent 365 (this is the new bit)

Agent 365 is the control plane for AI agents across an organisation. Think of it as the governance layer that lets IT discover, register, monitor, secure, and manage agents built with Microsoft AI platforms, agents from Microsoft's ecosystem partners, and any agents you register yourself. It integrates with Defender, Entra, and Purview so security, identity, and compliance all wrap around agent operations.

Here's the bit that matters for partners: Agent 365 is not a product customers configure once and forget. It's an operational capability that needs design, implementation, tuning, and ongoing management. That is services work. Your services work.

And E7 isn't the only route in. Customers with Copilot are already encountering agent challenges. Agent sprawl doesn't wait for a licensing upgrade. The governance problem exists today, across your entire installed base.

Two Types of Customer, One Destination

Here's what I keep seeing in conversations with partners across the channel. There are two very different starting points for customers, but they converge on the same need.

Track A: "We Already Have Agents Running"

These customers have been experimenting. Their power users built agents in Copilot Studio. Someone in finance created a custom agent that processes expense reports. Someone in HR built one that answers policy questions.

The result? Dozens, sometimes hundreds, of agents running across the business with no central visibility. Nobody knows what data these agents can access. Nobody has tested what happens when they get things wrong. There's no registry, no lifecycle management, and no audit trail.

Their immediate problem is risk and control. They need to understand what's already running, assess the exposure, and put guardrails in place. The agent genie is out of the bottle and it's not going back in.

Track B: "We Want to Automate Business Processes"

These customers are at the other end. They've seen the demos. They understand that Copilot isn't just about writing emails and summarising meetings. They want to use AI agents to automate real business processes: customer onboarding, invoice processing, support ticket triage, compliance checking, and more.

But they don't know where to start. Which processes are good candidates? How do you measure success? What does the architecture look like? How do you make sure the agents are accurate, compliant, and actually saving money?

Their immediate problem is direction and validation. They need someone to help them identify the right use cases, prove value quickly, and build confidence before scaling.

Where the Tracks Meet

Both tracks end up in the same place. Track A customers need governance first and business process optimisation second. Track B customers need business process design first and governance alongside it. Either way, they need a partner who can do both, and who can start small and build up over time.

This is the point I really want to hammer home: you don't need to have all the answers on day one. You need a starting point and a direction of travel. The services mature as the customer matures.

Start Simple. Deliver Value. Build From There.

I've talked to too many partners who immediately try to 'boil the ocean', over complicating the solution and getting bogged down in minute details. Then they get overwhelmed by the investment required and do nothing.

Stop it. Start smaller.

The best services practices I've seen in the channel follow a staircase model. You start with something repeatable, chargeable, and low-risk, then build upward as the customer relationship deepens and the complexity of their needs grows.

Step 1: Discovery and Advisory

This is your entry point. It's chargeable from day one and you can have it packaged within a week.

DSPM for AI (Data Security Posture Management for AI) is a discovery conversation you can run across every customer regardless of what SKU they're on. It maps where data is exposed, which AI tools are in use (sanctioned and unsanctioned), and what the risk profile looks like. This frames a services conversation before any licensing discussion even happens.

AI Discovery Cards are a structured, design-thinking workshop that maps business challenges to AI use cases. Simple. Repeatable. Chargeable. You're turning "we're exploring AI" into a paid engagement, and that's the mindset shift most partners need to make.

Copilot Readiness Assessments evaluate whether a customer's environment is actually ready for Copilot and agents: identity hygiene, data classification, security posture, change management readiness.

None of these require you to be an agent development shop. They require you to ask good questions and present findings clearly. If you can run a security assessment today, you can run these.

Step 2: Professional Services

Once you've run discovery, you'll have findings to act on. This is where you design and build.

Agent design workshops help customers identify their highest-value agent use cases and map out the architecture. Governance framework implementation puts the policies, controls, and monitoring in place. Business process mapping translates "we want to automate expenses" into a concrete specification. Copilot Studio builds deliver the actual agents.

This is project work. It has a defined scope, a start, and an end. Each engagement should lead naturally to the next step: who's going to run and maintain all of this once you've built it?

Step 3: Managed Services

This is where the real stickiness develops. You're not delivering a project any more; you're operating an ongoing service.

An Agent Operations Centre could monitor agent performance, catch errors, manage compliance, handle lifecycle (provisioning, updating, decommissioning agents), and continuously optimise. If you already run a Security Operations Centre, you have most of the operational muscle you need. The tooling and the subject matter are different, but the operating model is familiar.

The customer conversation shifts from "what will this cost?" to "what will this deliver, every month?" Recurring value is always worth more than one-time delivery.

Step 4: Outcome-Based Services

This is where you guarantee business results. You're not billing for time or for agent count; you're billing for outcomes. Reduced processing time. Lower error rates. Improved compliance scores. You share in the value you create.

Very few partners are here today, and that's fine. The point is to know the direction of travel. You start at step 1 and build towards step 4 as your capability and your customer relationships deepen. Each step makes the next one possible.

The Agent Maturity Ladder

There's another lens that's useful here: where are your customers on the agent maturity curve, and what services attach at each level?

Most customers are at level 1 or 2. They're using Copilot for productivity (summarising meetings, drafting emails) and maybe they've built a few agents in Agent Builder or Copilot Studio.

But the ones at level 1 and 2 who have been busy building? They've created a level 5 problem. They have an unmanaged agent estate that needs governance now, even though they haven't matured through levels 3 and 4 yet.

That gap between where most customers sit (level 1-2) and what they actually need (level 5 governance) is your services opportunity. You don't need to help every customer climb every rung sequentially. Many need to jump to governance first and then work on maturing their agent capabilities within that framework.

This is the opposite of the traditional adoption curve. Usually you build capability first, then add governance. With agents, the governance has to come first (or at least in parallel), because the risk of ungoverned agents is too high and the proliferation is already happening.

What to Do on Monday Morning

I'm conscious that a 3,000-word post about services strategy is useless if it doesn't end with something you can actually go and do. So here are five things you can start this week.

1. Audit your customer base for agent active users.

Pull the data. Look at agent MAU and any custom agent deployments you're aware of. The numbers will surprise you. I've yet to meet a partner who wasn't shocked by how much agent activity was already happening across their accounts. That data is your prospecting list for services conversations.

2. Package a repeatable discovery engagement.

Pick one: DSPM for AI, AI Discovery Cards, or a Copilot Readiness Assessment. Define the scope, the deliverables, the price, and the timeline. Make it something your pre-sales team can pitch next week. It doesn't need to be perfect. It needs to exist.

3. Pick one customer and run a pilot.

Don't wait for E7 GA on 1 May. The governance problem exists today for any customer with agents. Find a customer with visible agent sprawl (your audit from action 1 will tell you who), offer them a discovery engagement, and deliver it. You'll learn more from one real engagement than from six months of internal planning.

4. Train your team on the three-level Copilot conversation.

Most partner sales teams sell Copilot at level 1: "it helps you write emails and summarise meetings." The real revenue is at level 3: "it's the foundation for an agent ecosystem that runs your business." Get your pre-sales and account teams talking about process automation and governance, not just productivity. The licensing conversation gets much bigger when the customer sees the platform, not just the assistant.

5. Start the managed services conversation early.

Don't wait until you've finished a professional services engagement to mention managed services. Plant the seed in the discovery phase: "Once we've built this governance framework, who's going to operate it day-to-day?" The customer is thinking about it even if they're not saying it out loud. The earlier you position managed services as the natural next step, the higher your conversion rate.

And one more thing, the one that matters most: licensing follows services. Not the other way around. The partners I think will close the biggest E7 deals are the ones who lead with a services conversation about governance and agent operations, and the licensing decision is a natural consequence. If you lead with the SKU, you end up in a procurement conversation about price. If you lead with the problem, you end up in a business conversation about value.

The Clock Is Ticking

The risk for partners right now isn't that E7 is complicated or that Agent 365 is hard to understand. The risk is that your customers are already building and deploying agents without you. They're doing it themselves, because nobody has offered them a better option.

The customers with 1 agent, 331 agents, or with 1,000 agents? They didn't wait for a partner to show up with a proposal. They just got on with it. And now they have a governance problem that's growing every week.

You can be the partner who helps them solve it, or you can be the partner who eventually sells them the licence after someone else has done the hard work. The services opportunity is right there. Start simple. Deliver value. Build from there.

The agents aren't waiting. Neither should you.

So I built a system. And then I built another system on top of it. And then I gave that system a coaching council made up of six imaginary advisors. This is the story of how I turned an Obsidian vault and GitHub Copilot CLI into something that genuinely changed how I work, what went wrong along the way, and what I'd tell you if you're thinking of doing something similar.

The Problem I Was Trying to Solve

My job is to help three large partners build their Microsoft practices. Think tech strategy, go-to-market, skilling, security services, AI adoption, and more. It's the kind of role where the value you bring is directly proportional to how well you can connect dots between conversations that happened on different days, with different people, about different things.

The trouble is, my brain is not a database. I'd walk into a meeting with one person and forget that something we discussed with another person last week was directly relevant. I'd lose track of who I'd promised what to. I'd sit down to write a weekly update email and spend 45 minutes reconstructing what I'd actually done.

I tried OneNote. I tried Notion. I tried just being better organised (spoiler: that didn't work either). What I really needed wasn't a better note-taking app. I needed something that could take the raw material of my working life and help me think about it.

Why Obsidian, and Why AI Agents?

I landed on Obsidian because it stores everything as plain markdown files in a folder on my machine. No proprietary format. No proprietary cloud lock-in. Just text files I can version-control with Git, search with grep, and process with scripts. That last bit turned out to be the key.

GitHub Copilot CLI lets you define custom agents: small, specialised AI assistants that can read and write files, run scripts, and call external APIs. Each agent has a markdown file that describes its purpose, its workflow, and the rules it must follow. It's like writing a very detailed job description, except the employee actually reads it and does what you ask.

I started with one agent. Then two. Now I have twenty.

What the System Actually Looks Like

The vault has about 370 notes: meeting notes, daily journals, People notes (a mini-CRM of 70+ stakeholders), partner strategy hubs, project trackers, coaching sessions, and weekly reflections. Underneath, there are five layers that make it work.

20 agents, grouped by function. There's a daily operations team (scaffold meetings from my calendar, debrief them afterwards, prep briefings before important conversations, plan the week ahead). There's a knowledge management team (maintain wiki links, scan for broken references, audit vault health). There's a coaching team (more on that shortly). And there's a relationship tracker that monitors whether I'm staying in touch with the right people at the right frequency.

8 skills: shared knowledge modules that agents load when they need domain context. Things like "how does the Microsoft fiscal year work?" and "what are the wiki-linking rules for this vault?" and "how do I detect which partner a meeting belongs to?" Skills mean I write the rule once and every agent follows it.

14 Python scripts for anything that needs to be deterministic. Date calculations, name normalisation, pollen forecasts (yes, really), frontmatter parsing, partner detection. I don't trust a language model to compute fiscal years correctly. I trust Python.

External integrations via MCP servers: Microsoft 365 (calendar, email, Teams) thanks to Work IQ, Oura Ring (heart rate during meetings, readiness scores), and Open-Meteo (daily pollen levels). The biometrics are admittedly a bit of a vanity feature. But seeing that my heart rate spiked during a tense planning session is potentially useful coaching data.

Obsidian plugins tie it together: Dataview for dynamic queries, Tasks for action tracking with due dates, Templater for note creation, and Obsidian Git for automatic version control.

A Typical Day

I open my terminal and say @scaffold. The scaffold agent pulls my calendar from Microsoft 365, filters out the noise (focus time, lunch, broadcast webinars), detects which partner each meeting belongs to, normalises attendee names against my People notes, and creates pre-populated meeting note files. It also checks today's pollen level and adds it to my daily note. This takes about 30 seconds.

Before an important meeting, I run @prep Joe Bloggs. The prep agent reads Joe's People note, finds our last meeting, extracts open actions, checks coaching commitments related to the relationship, queries M365 for recent emails, and produces a structured briefing with talking points. It saves this into the meeting note's prep section so it's right there when I need it.

After the meeting, I fill in my notes (summary, key points, actions) and run @debrief. The debrief agent checks for transcript name errors, adds biometrics from my Oura Ring, tags my action items with due dates, scans for duplicate tasks across the vault, updates the People note's last contact date, and logs what it did to my daily note. If the meeting revealed something significant about a person's role or priorities, it flags the People note for enrichment.

At the end of the week, @reflect gathers all the week's data (meetings attended, actions completed, people connected with, coaching commitments tracked) and pre-populates my weekly reflection note. I still write the reflective parts myself. The agent just removes the friction of remembering what happened.

The Coaching Council Experiment

This is the part that sounds slightly unhinged, so bear with me.

I have six coaching personas: systems thinking, accountability, commercial urgency, growth mindset, marginal gains, and behavioural transition. They run as separate agents, orchestrated by a coach agent that conducts a Delphi-style deliberation across all six perspectives. The output is a coaching session with a scorecard tracking six dimensions over time.

Does it work? Honestly, more than I expected. The scorecard trajectory over nine sessions has been genuinely useful for spotting patterns I wouldn't have seen myself. My "Follow-Through" score dropped for three consecutive sessions before I noticed and took it seriously. The different lenses catch different things; process decomposition questions are completely different from accountability challenges.

Is it overkill? Absolutely. Six personas is too many for the signal they produce. If I were starting again, I'd pick three. But the coaching data has become one of the most valuable parts of the vault, and the commitments I track through it have directly influenced real decisions at work.

What I Got Wrong

Quite a lot, actually.

I built the system instead of doing the work. For the first few weeks, I was spending more time refining agent prompts, writing scripts, and tweaking templates than I was actually using the vault for its intended purpose. My coaching scorecard flagged this. Follow-Through was my weakest dimension, and the irony of building a follow-through tracking system while not following through on actual commitments was not lost on me.

I over-indexed on observability. Agent activity logs, health audits, consistency checks, relationship scoring. I could see everything about the state of my vault. But observability without action is just a prettier way of procrastinating. The dashboard was green. The work wasn't done.

Weekly reflections died. I built an entire reflect agent with data gathering, pre-population, and contextual prompts. Then I didn't use it for five months. The daily notes were raw ore that never got smelted. I've since restarted, and the reflect agent genuinely helps, but the gap taught me that tooling doesn't create habits. Habits create habits. The tooling just reduces friction.

Name resolution is harder than you'd think. Speech-to-text transcripts mangle names constantly. I've built a corrections memory system and a name normalisation script, but it's a never-ending battle.

What I'd Tell You

If any of this resonates, here's what I've learned.

Start with one agent, not twenty. The debrief agent is the single most valuable thing I built. If you do nothing else, build something that processes your meeting notes after the fact: tags actions, links people, updates your CRM. The compound value of consistent post-meeting processing is enormous.

Externalise computation to scripts. Don't ask a language model to calculate dates, detect partners from attendee lists, or parse YAML frontmatter. Write a Python script. It'll be right every time, and you'll never wonder whether the agent hallucinated a fiscal year.

Design for the lazy version of yourself. If the system requires you to remember to run something, you won't. The best parts of my setup are the ones where I type one command and the agent handles everything else. The worst parts are the ones that need me to manually maintain them.

Be honest about whether you're building or using. There's a fine line between productively improving your system and using system improvement as a form of avoidance. If you haven't written a weekly reflection in five months but you've refactored your agent architecture three times, you might be on the wrong side of that line. I certainly was.

It doesn't have to be this complex. My vault has 20 agents, 8 skills, 14 scripts, and integrations with three external services. Most people would get 80% of the value from an Obsidian vault with Dataview, a good daily note template, and one well-written debrief agent. The other 19 agents are diminishing returns. Enjoyable, useful, occasionally brilliant diminishing returns. But diminishing returns nonetheless.

Try It

If you're curious, everything I've described runs on GitHub Copilot CLI with custom agents defined as markdown files. Obsidian is free. The scripts are Python stdlib with no pip dependencies. The whole thing is version-controlled in a private Git repo that syncs across my devices.

I'm not suggesting you build what I've built. I'm suggesting you look at the gap between what you know and what you can recall at the right moment, and ask yourself whether a well-structured vault with a couple of AI agents might close it. For me, it did. Not perfectly, not without wrong turns, but meaningfully.

I'd love to hear if you're doing something similar, or if you have questions about any of this. Drop a comment, or find me on LinkedIn.

Microsoft 365 E7 at a glance:

• Price: $99/user/month (with Teams) or ~$90.45/user/month (without Teams)
• Launch date: May 1, 2026
• Includes: Everything in E5, plus Microsoft 365 Copilot, Agent 365, and the full Microsoft Entra Suite, with advanced Defender, Intune, and Purview security capabilities
• Agent 365 standalone: Also available separately at $15/user/month
• Why it matters for Partners: Creates new service opportunities across advisory, professional, and managed services, particularly around AI agent governance

If you're a Partner and you're reading the headline as "Microsoft added a more expensive plan," you're missing the point. E7 isn't just a new licence tier. It's the commercial expression of the Frontier Firm vision that Microsoft has been building towards since the 2025 Work Trend Index: organisations where humans and AI agents work side by side, with the governance and security to make that safe. For Partners, that signal should be translating into practice-building conversations today, not in May.

What's Included in Microsoft 365 E7 vs E5?

E7 sits above E5 and consolidates several capabilities that previously required separate add-ons or standalone licences. If you've got customers running E5 with Copilot bolted on, plus Entra ID Governance, plus Intune Plan 2, they're likely spending close to (or more than) $99/user/month already. E7 wraps it all up.

Here's a quick comparison of the key differences:

A couple of things worth highlighting beyond the feature matrix:

Alongside the E7 announcement, Microsoft unveiled Wave 3 of Microsoft 365 Copilot, which brings deeper agentic capabilities across Word, Excel, PowerPoint, Outlook, and Copilot Chat. Two things worth calling out:

Copilot Cowork is a new capability built in close collaboration with Anthropic, bringing the technology that powers Claude Cowork into Microsoft 365 Copilot. It enables long-running, multi-step work that unfolds over time: delegating complex tasks like compiling meeting follow-ups, drafting competitive analyses, or preparing board packs from data scattered across SharePoint, Outlook, and Teams. Copilot Cowork is currently in research preview with select customers via the Frontier program and is not yet generally available.

Work IQ is the intelligence layer that underpins Microsoft 365 Copilot and agents. It's how Copilot understands relationships, context, priorities, and work patterns across the Microsoft 365 estate. Work IQ is what makes Copilot contextually aware rather than just generatively capable, and it's available to all Microsoft 365 Copilot users, not exclusively E7.

What Is Agent 365, and Why Is It the Real Story?

Agent 365 is a unified control plane for managing, securing, and governing AI agents across the enterprise. It's the feature that should have every Partner's attention.

Here's the challenge that Agent 365 addresses: organisations are already building and deploying AI agents using Copilot Studio, Power Platform, Azure AI Foundry, and third-party tools. But right now, most of them have no centralised way to see what agents exist, what they have access to, or what they're doing. Sound familiar? It's the shadow AI problem, but for agents instead of people.

Agent 365 treats every AI agent as a first-class digital identity. Each agent gets its own Entra Agent ID, not piggybacking on a user account, but a distinct identity with its own permissions, audit trail, and lifecycle. From the Microsoft 365 admin centre, IT teams can:

• Discover and register agents across all platforms (Copilot Studio, Foundry, third-party frameworks)
• Assign ownership and permissions, defining exactly which scopes each agent can access (Mail.Send, Files.ReadWrite, etc.)
• Monitor activity through real-time dashboards, risk alerts, and usage analytics
• Enforce policies through Defender (threat protection), Entra (identity), and Purview (compliance)
• Manage the full lifecycle, from onboarding through to suspension and retirement

This is significant. Organisations aren't just going to need help deploying agents. They're going to need help governing them. And governance is a practice, not a project. It's ongoing, it evolves, and it requires expertise. That's where Partners come in.

Agent 365 is also available as a standalone add-on at $15/user/month for organisations that want the governance layer without the full E7 suite, which opens up an entry point for Partners whose customers aren't ready for the jump to $99.

What Service Opportunities Does E7 Create for Microsoft Partners?

Let me be direct: the biggest risk for Partners right now isn't that E7 is complicated. It's that Partners treat it as a licensing conversation and miss the service opportunity sitting right behind it. This isn't a resale motion. It's a practice-building one.

I think about the opportunity in three layers: advisory, professional, and managed services. Each creates a distinct revenue stream, and they compound: advisory leads to professional, professional leads to managed.

Advisory Services

The immediate opportunity is helping customers make sense of what E7 means for them. That starts with understanding where they are today:

• E7 readiness assessments. Audit current Microsoft 365 licensing, identify where customers are paying for overlapping add-ons (Copilot, Entra ID Governance, Microsoft Entra Suite), and model the business case for consolidation. For some customers, E7 will be cheaper than what they're paying now.

• Agent governance strategy. Most organisations have no policy framework for AI agents. Help them design governance models: who can create agents? What data can they access? What approval workflows exist? What happens when an agent is retired? These are the questions boards and risk committees are going to ask.

• AI adoption roadmaps. Position E7 as the platform for a phased AI strategy, starting with Copilot Chat for productivity and Copilot Cowork as it moves beyond research preview, then moving to custom agents for business process automation. Map this against the customer's strategic priorities.

• Shadow AI remediation. I've written about this before. E7's bundled Copilot plus governance tooling (Purview, DLP, Defender) makes it a strong answer to the shadow AI problem. If you've already had shadow AI conversations with customers, E7 gives you a concrete next step.

Professional Services

Once the strategy is agreed, someone has to implement it. This is bread-and-butter work for technical Partners:

• Agent 365 deployment and configuration. Standing up the control plane, configuring the agent registry, defining permission scopes, and integrating with existing identity and security infrastructure.

• Entra Agent ID architecture. Designing the identity model for AI agents: how they're provisioned, what access they receive, how they're grouped and governed. This is a natural extension of existing identity and access management (IAM) practices.

• Custom agent development. Building agents in Copilot Studio or Azure AI Foundry to automate specific business processes. Think onboarding workflows, procurement approvals, customer service triage, compliance checks, and reporting. Each of these is a scoped engagement.

• Purview and DLP configuration. Extending data loss prevention policies and sensitivity labels to cover agent-generated content and agent interactions. This is new territory for most compliance teams and they'll need expert help.

• E5-to-E7 migration planning. For customers consolidating from E5 plus add-ons, there's a transition to manage: licence reassignment, feature enablement, user communication, and training.

Managed Services

This is where the recurring revenue lives. Agent governance isn't a one-time project; it's an ongoing discipline:

• Agent lifecycle management. Continuous onboarding of new agents, monitoring of existing ones, and retirement of obsolete agents. As organisations build more agents, this becomes a dedicated function, and most won't have the internal capacity to do it well.

• Security operations. Monitoring agent activity for threat signals via Defender, including detecting prompt injection attempts, anomalous data access patterns, or agents behaving outside their intended scope.

• Compliance monitoring and reporting. Using Purview to track agent interactions with sensitive data, generate compliance reports, and respond to audit requests. Regulated industries (financial services, healthcare, legal) will need this immediately.

• Continuous optimisation. Reviewing agent performance, identifying underused or redundant agents, and recommending improvements. Think of it as FinOps for agents.

• Licence management. Helping customers optimise their E7 deployment: ensuring the right users are on the right plans, tracking usage, and managing the cost envelope.

How Does E7 Fit the Frontier Firm Vision?

Microsoft didn't call E7 "The Frontier Suite" by accident. The naming ties directly to the Frontier Firm concept from the 2025 Work Trend Index, where Microsoft defined a new kind of organisation: one that embeds AI at its core, operates with human-agent hybrid teams, and treats intelligence as an on-demand resource rather than a headcount line item.

The Frontier Firm has three defining characteristics: employees manage AI agents alongside human colleagues, workflows are re-engineered around what AI can do autonomously, and governance keeps all of it secure and compliant. If you map that against what E7 actually ships, the alignment is hard to miss:

• Copilot makes every employee an "agent boss," able to delegate complex, multi-step work to AI that acts on their behalf. With Wave 3's agentic capabilities and the upcoming Copilot Cowork (currently in research preview), this delegation becomes increasingly autonomous.
• Agent 365 provides the governance infrastructure that stops autonomous agents from becoming an unmanaged risk.
• Work IQ, the intelligence layer powering Copilot, gives the AI contextual awareness of relationships, priorities, and work patterns, so agents aren't just fast, they're relevant.
• Entra, Defender, and Purview wrap the whole thing in the identity, security, and compliance controls that enterprise customers require before they'll commit.

In practical terms, E7 is the closest thing to a "Frontier Firm starter kit" that Microsoft has shipped. For your customers, it's the platform that turns the Frontier Firm from a concept in a research report into an operational reality.

What this means for Partner credibility

There's a second angle here that's worth thinking about. The Frontier Partner badge requires Partners to demonstrate that they're using AI internally, not just selling it. Microsoft calls this being "Customer Zero," and it's become a genuine differentiator. Partners who can show they've operationalised Copilot, governed their own agents, and built practices around these tools carry more weight with customers than those who are just reselling licences.

Adopting E7 internally does two things for your Frontier Partner credentials. First, it gives your team hands-on experience with the full stack (Copilot, Agent 365, Purview, Entra Agent IDs) so they can speak from experience, not just training materials. Second, it gives you a credible story to tell customers. "We've deployed this ourselves, here's what we learned, and here's how we can help you" is a much stronger opening than "here's what the product documentation says."

I've written before about how distributors and Partners should be thinking about AI agents. E7 takes that from theory to practice. The Partners who are already building Frontier capabilities internally will be the ones best positioned to help customers do the same.

How Should Partners Prepare for E7 Before May 1?

E7 launches on May 1. That gives you less than two months. Here's what I'd be doing right now:

1. Audit your customer base. Who's on E5 with Copilot today? Who's paying for Entra ID Governance or Intune Plan 2 as add-ons? These are your warmest E7 prospects, and the consolidation story writes itself.

2. Build internal Agent 365 expertise. Get your technical team familiar with the Agent 365 admin experience, Entra Agent IDs, and the governance capabilities. If you're already building agents in Copilot Studio, start thinking about how you'd govern them at scale.

3. Develop a customer conversation framework. Don't lead with licensing. Lead with the question: "How are you planning to govern AI agents across your organisation?" Most customers won't have a good answer. That's your opening.

4. Package your services. Create named offerings across the advisory, professional, and managed service layers. A defined "E7 Readiness Assessment" or "Agent Governance as a Service" is easier to sell, easier to deliver, and easier to scale than ad-hoc consulting.

5. Position early. Write about it. Talk about it. Share your perspective with your customers before they hear it from someone else. The Partners who own this conversation now will be the ones customers turn to when the budget conversation happens.

Frequently Asked Questions

The Bottom Line

Microsoft 365 E7 is the clearest signal yet that the Frontier Firm isn't a research concept; it's a licensing SKU you can buy on May 1. For Partners, the opportunity isn't in the resale margin on a $99 licence. It's in the advisory, professional, and managed services that sit around it, and in the credibility you build by being a Frontier firm yourself.

Agent 365 alone creates a net-new governance discipline that most organisations don't have the skills, tooling, or capacity to handle internally. Partners who build practices around this now, who can help customers design, deploy, and manage their agent estates, will be the ones defining what the next generation of Microsoft services looks like.

The question, as always, is whether you'll lead or follow.

I'd love to hear your thoughts. What opportunities are you seeing? What questions are your customers asking? Let me know in the comments below.

It doesn't seem like that long ago we were in the Modern Partner era. Everything that matters has Frontier all over it. Frontier Firms, Frontier Badges, Frontier Programs. If you want to be aligned with what's important make it Frontier and you'll be met with nods of approval all round. But that's not the spirit of the Frontier ambition. It runs deeper than that, and speaks to an important point. This round of AI isn't a fad. Ignoring what this shift in technology and operations means for your business will have lasting implications.

A few years ago, I wrote a short series of posts looking at the things I thought were important when choosing a 'modern' distributor. With the rise and rise of AI I thought it would be a good idea to consider some of the ways that distributors could think about using AI to become, or remain, 'Frontier'. So let's do that, shall we?

Ecosystem & Operational Complexity

Cloud distributors operate in an environment of structural change. Historically, they compete on process efficiency and price, not products or services. If the threat of disintermediation has passed, it's certainly been replaced by the threat of margin compression and operational debt.

A typical distributor will manage multiple systems (ERP, CRM, billing platforms, partner portals, marketplace integrations, etc.) without integrated data flows. It's no surprise then, that 74.2% of B2B partners prioritise integrated portals when purchasing partner technology, yet many lack them. Front-line teams still spend valuable time manually re-entering data, chasing information across systems, and struggle with stale or conflicting records.

I see this with distributors I've worked with over the last few years. Tasks that should take seconds or minutes can take days, or even weeks to complete thanks to outdated and broken systems and processes. Imagine how this compounds when those tasks are recurring!

Talent constraints also present a challenge. High-value roles (architects, senior BDMs) are expensive, especially ones who have deeper AI skills. Distributors cannot scale delivery teams proportionally without eroding unit economics. In other words, they're making less money - or even losing it - because their costs are too high relative to revenue. The way out of that maze isn't through hiring or firing, but augmentation through automation. Working smarter. Not harder.

The AI Agent Opportunity

AI agents differ from chatbots or RPA. Built right, they can autonomously perceive context, reason through multi-step problems, access external systems, integrate with CRM and ERP systems, and execute actions without human intervention. As a technology, they're rapidly maturing in capability and reliability. For distributors, I see agents helping address three economic imperatives:

1. Protect margin through operational efficiency: Reduce manual billing, reconciliation, and data management overhead.

2. Accelerate deal cycles and revenue capture: Front-line teams move from administration to strategy and relationship management.

3. Defend customer relationships: Proactive renewal management, personalised onboarding, and health scoring prevent churn and expand attach rates.

Front-Line Role Challenges & AI Readiness

Let's explore a few role types, where I see friction today, and where agents could potentially help.

Business Development Managers

BDMs are challenged on multiple fronts, with as little as 20-30% of their time actually spent selling.

Current Friction:

• Researching opportunities manually consumes hours.
• Contact management requires external tools and manual updates (think: firmographics, intent signals, org structures, etc.) if it's done at all.
• CRM and email systems are disconnected. Task switching overhead can be 5-10 minutes or more per day, per context switch.
• The technology moves rapidly. BDMs fall behind on service offerings or new vendor capabilities.

AI Agent Fit?

Yes. BDMs work within bounded problem spaces (work with defined segments, etc.), have clear data dependencies (CRM, email, web research), and benefit from task automation.

Solution Architects

Solution Architects are the linchpin between customer problems and technical implementations. Yet they face sturctural constraint: discovery, design, and proposal validation are sequential, time-consuming, and iterative.

Current Friction:

• Assessment phase requires deep technical discussion but is also subjective; different architects propose different solutions for similar problems.

• Solutioning and proposal writing are tangled; architects write and revise in parallel, rather than validating designs before documentation.

• Architects lack systematic access to best-practice templates, reference architectures, or prior solutions.

• Multi-stakeholder review cycles (technical, sales, compliance) extend timelines by weeks.

• Customer communication is brittle; changes to design are not propagated to all stakeholders.

AI Agent Fit?

Yes. Architects work with structured problem taxonomies (cloud migration patterns, infrastructure design, compliance requirements), reference large internal knowledge bases, and communicate across organisational boundaries. AI agents can facilitate discovery interviews, synthesise requirements, recommend reference architectures, and automatically flag compliance/security gaps, acting as a design assistant rather than a replacement.

Operations & Renewal Teams

Customer success and renewal teams manage recurring revenue, yet lack the data infrastructure to act predictively. Manual tracking of renewals, usage metrics, support tickets, and engagement signals means most teams react to churn rather than prevent it.

Current Friction:

• Renewal alerts come too late; missed early engagement opportunities.

• Churn prediction is rule-based (e.g., low license usage) rather than statistical; many at-risk customers are not flagged.

• Upsell recommendations are not prioritised; teams lack visibility into which customers are ready for upgrade conversations.

• Billing disputes consume energy; reconciliation errors and complex multi-currency, multi-entity setups create friction.

• Partner portal information is stale; distributors do not have real-time visibility into partner performance or health.

• Customer onboarding is manual; task assignment, follow-up reminders, and progress tracking are email-driven.

AI Agent Fit?

Yes. Renewal and operations teams work with structured data (customer subscription data, usage telemetry, support ticket sentiment, engagement metrics) and benefit from predictive automation (churn risk scoring, renewal forecasting, health scoring). Microsoft’s CSP partners already use billing automation platforms; agents can extend this to predict outcomes and automate proactive engagement.

10 Agents For Frontier Consideration

The following 10 agent ideas are sequenced to build on one another. Each includes an implementation owner, problem statement, and an outline technical approach to implementation. They're suggetions to get you thinking, rather than prescriptions to specifically implement.

Click, or tap, to expand each one to learn more.

The Frontier Distributor

The Microsoft AI Cloud Partner Program launched a Frontier Distributor designation recently, and while it audits key areas like support, security, channel enablement, platform capabilities, and technical delivery excellence, it doesn't necessarily push for the deep agentic transformation of distribution. I think to be truly 'Frontier', distributors need to go further.

There are some great examples, such as Arrow who launched ArrowSphere Assistant which is not only embedded into their portal but a source of monetisation from the value it unlocks. Pax8 launched their MCP server recently, recognising the power of integrating Pax8 data with LLMs. I'm sure there are more to come.

AI agents represent a fundamental shift in how cloud distributors operate. Unlike prior automation tools, agents reason about context, integrate across multiple systems, and continuously improve through feedback. For distributors facing margin compression and operational complexity, agents offer a path to scale delivery, protect relationships, and drive profitability without proportional increases in headcount.

The 10 implementations outlined above are sequenced to build capability, demonstrate value, and transform front-line operations in phases. Each is grounded in real distributor pain points and proven Microsoft technologies. Together, they constitute a transformation program that, if executed with discipline and attention to data governance, can reposition a distributor as a Frontier Firm set up for profitable growth in the AI-native era.

The window to act is now. Competitors who deploy AI agents first will capture market share and talent. Distributors who lead their ecosystems with AI-enabled partners will build defensible moats and commanding margins.

That decision quietly locked in a long‑term constraint.

Convenience during onboarding becomes a permanent design choice

In 2019, Microsoft began tightening up security baselines, requiring partners to enforce multi-factor authentication for all users in their tenants. Suddenly, every account, from the executive suite to the service accounts running your office photocopier, was subject to the same rigid security baselines required to manage customer environments.

Meeting this new baseline would be a challenge.

By associating Partner Center with a general‑purpose corporate tenant, you collapse two very different risk profiles into one. Partner Center is a high‑privilege control plane for customer environments. Corporate Entra ID is designed for broad access, collaboration, and day‑to‑day work. Mixing the two increases the likelihood that a compromise in one place can have consequences somewhere far more sensitive.

MFA is a good idea, but back in 2019 it wasn't universal (it still isn't!), and having to implement this for potentially thousands of users with little notice, when most of them had nothing to do with Microsoft or Partner Center, was a big deal. Some legacy systems just wouldn't be able to meet the requirements, which would lead to non-compliance. This could be a show-stopper if it impacted the partner's ability to transact and administer customer environments.

The guidance exists, but it is easy to miss

I remember crawling through documentation at the time trying to find concrete guidance from Microsoft stating not to use your mail Entra ID and sure enough, I found it. Microsoft’s documentation does state that you should consider not using your corporate tenant for Partner Center. That guidance exists, and it has existed for years. It is just easy to miss, and rarely surfaced at the moment when the decision is actually being made:

📝 Update (February 2026): Since publishing this post, I submitted a PR to Microsoft Learn to strengthen this guidance, and the documentation has now been updated. The original wording shown in the screenshot above has been improved.

Personally, I think the note is too soft. I'd like to see the guidance be more explicit: don't use your main corporate Entra ID tenant for authenticating with Partner Center. I think the problem arises because the people onboarding as a Microsoft Partner within a business might not be the people who understand or care about the impact of a decision like this, and just sign in with their corporate credentials.

Anyway, fast forward to 2026.

By now, MFA will have been implemented but there's still the lingering question of what to do about this Entra ID / Partner Center association. It's still desirable to strictly limit access to Partner Center and keep it well away from your wider corporate environment where you could be prone to lateral movement from an attacker.

For a while, I was convinced it would be possible to add in another Entra ID and remove the original, thereby solving the problem. Certainly on first-pass, the documentation seems to support this. There is an article for adding existing Entra IDs, and another for removing them. Surely, after some due diligence and planning, this would be the perfect solution?

Well, no.

You cannot remove the primary Entra ID tenant

After some brainstorming and testing with a friend of mine who works in a Microsoft Partner, we discovered it isn't possible, and it turns out there's a third article that buries this fact at the bottom of the page.

So while you can add multiple Entra IDs to your Partner Center tenant you cannot remove the original, primary Entra ID tenant. This makes sense when you consider that the ID appears in places like the recon file; it is hardwired into things.

Back to square one then.

(What's also interesting to learn is that when you add multiple Entra ID tenants, roles like Admin Agent, Helpdesk Agent, and Sales Agent only seem to flow from the primary.)

The realistic options in 2026

Once you accept that the original tenant cannot be detached, the available paths narrow quickly:

1. You can migrate your corporate environment into a new tenant and leave Partner Center behind. That is a major transformation project with wide‑ranging implications.
2. You can create a new Partner Center account and migrate customers to it. That carries commercial, operational, and programme‑level consequences, including potential impacts on incentives, designations, and historical data.
3. Or you can accept the situation and mitigate risk through other controls, knowing that the underlying coupling remains.

None of these are clean. All of them involve trade‑offs. The lesson is a pragmatic one: architecture decisions made for "convenience" during onboarding often become the constraints that define your security posture for years to come.

Why this still matters in 2026

From 1st April, 2026, Microsoft will begin enforcing MFA on all App+User usage of Partner Center APIs. So if you're still clinging on to some legacy integrations, or have managed to hold off on MFA for those last few service accounts, you've got some work to do.

When you read the documentation, you'll see a number of common issues, and whether they're good candidates for a technical exception. Needless to say, the answer is uniformly no.

UPDATE

Thank you to Guy Gregory for finding a fourth article that touches on the topic, with slightly more explict guidance!

I'd still make a case that even this isn't clear enough - I think 'avoid' is still too passive.

What each product is and who it targets

Microsoft 365 Copilot is an AI assistant embedded into core Microsoft 365 apps such as Word, Excel, PowerPoint and Outlook. It generates content, analyses data and automates routine tasks by drawing on the user’s tenant data and application context. It is aimed at business professionals who want a deeply integrated assistant that works inside the applications they already use.

Copilot Chat is the conversational, chat-first interface for interacting with Microsoft’s AI capabilities. It provides an easy way to ask questions, get summaries, draft text and work with files through a single chat window. Copilot Chat is useful for users who prefer a dialogue-style interaction, want quick answers, or need a low-friction alternative to switching between multiple apps. By default, Copilot Chat is grounded in web search and requires users to manually upload files or provide content directly to interact with organisational information. When configured for enterprise use, it respects organisational controls on the content users provide — such as DLP rules and sensitivity labels — but does not proactively access tenant data like emails, files, and chats.

How they differ in practice

The biggest practical difference is how each tool is grounded in data. Microsoft 365 Copilot is deeply integrated with Microsoft Graph and can pull context from emails, files, calendars and Teams messages that the user is authorised to see. That work grounding makes its answers contextually rich and specific to your organisation. By contrast, Copilot Chat is chat-first and by default relies on web grounding (via Bing search) and user-provided files. It does not automatically access organisational data held in Microsoft Graph. This is a design trade-off that allows for faster deployment and clearer data boundaries, but means Copilot Chat requires users to manually bring in the organisational context they need—either by uploading files or by pasting information directly into the chat. This looser integration actually supports rapid deployment in high-risk environments: it limits the surface area of potential data exposure until governance is mature (see grounding and architecture).

From a governance standpoint, Microsoft 365 Copilot leverages the full suite of Microsoft 365 compliance and protection controls such as Purview sensitivity labels and DLP. Copilot Chat, when set up for enterprise use, respects those controls on any content users provide, including uploaded files and pasted text. Administrators manage Copilot Chat’s scope through settings such as web grounding (enabled by default; must be explicitly disabled for regulated data environments) and chat retention. This means Copilot Chat can be deployed quickly as a governed alternative to consumer tools while still fitting into your existing compliance framework. Because it does not access tenant data by default, it creates a controlled entry point for AI adoption before moving to the richer data integration of Microsoft 365 Copilot (see enterprise data protection).

Quick comparison: Copilot Chat vs Microsoft 365 Copilot

The elephant in the room: shadow AI in the workplace

Shadow AI occurs when employees use consumer or unauthorised AI tools to solve work problems without IT or compliance approval. Typical examples include staff using public chatbots to draft confidential emails, uploading customer lists to online summarisation tools, or using image generators with proprietary brand assets. These shortcuts can speed up tasks, but they happen outside the controls that protect corporate data.

The risks are tangible. Data leakage is the primary concern, as sensitive or personal data may be exposed to third-party vendors with unknown retention or use policies. There are compliance gaps where regulated data moves outside monitored systems, and inconsistent controls across teams create uneven risk profiles. Legal and reputational exposure follows if an unauthorised AI use leads to a breach or a regulatory violation.

Addressing shadow AI requires both technical controls and behavioural change. Technical options include providing a sanctioned, tenant-aware alternative that users can trust. Behavioural measures include clear policies, training and visible support from IT and risk teams so employees do not feel forced to use consumer services to get work done.

Why Copilot Chat is an effective de‑risking tool

Copilot Chat gives organisations a sanctioned and convenient substitute for consumer AI tools. It is accessible inside Microsoft 365, so employees can get the speed and interactivity they seek without leaving a governed environment. That convenience reduces the incentive to reach for unsanctioned chatbots that operate outside corporate controls.

Crucially, Copilot Chat enforces enterprise data protection on content users provide to it. It respects existing DLP rules and sensitivity labels, so confidential files labelled by Purview are excluded from being uploaded or shared in chat; if a user attempts to do so, DLP policies block the action. Admins can configure chat history retention to meet regulatory needs, disable web grounding for specific users or groups (important for handling regulated or sensitive data, note that web grounding is enabled by default), and block uploads of sensitive file types. These settings let you balance usability and risk. Because Copilot Chat doesn’t automatically access organisational data, it gives administrators a clear control boundary: they can govern what gets uploaded or shared into the tool, rather than attempting to govern a system that continuously ingests tenant data (see admin and data protection docs).

Centralised monitoring, via Microsoft Purview and audit logs, gives visibility into who is using AI, what types of content are being shared, and when controls block risky behaviour. That telemetry supports detection of anomalous usage patterns and faster response. Combined with role-based access and policy rules, Copilot Chat channels AI usage through auditable, controlled pathways rather than dispersed consumer services.

Finally, embedding Copilot Chat in familiar apps boosts adoption and embeds safe practices. When employees can access high-quality AI assistance through the tools they already use, they are less likely to adopt shadow AI. Industry analysts highlight that providing approved alternatives and clear guidance is one of the most effective ways to reduce shadow AI adoption.

Practical roadmap to adopt Copilot Chat and reduce shadow AI

1) Enable and promote Copilot Chat. Confirm your organisation holds an eligible Microsoft 365 or Office 365 licence (the full list includes Business, E3/E5, education, and Teams plans). Copilot Chat is included at no additional cost. Make it visible by pinning to the Microsoft 365 app launcher and roll out to pilot groups. Use the Copilot Success Kit to streamline enablement. Ensure users know it is supported and safe to use.

2) Configure DLP and sensitivity labels for AI use. Create DLP rules that explicitly block uploads of recognised sensitive data to AI chats, and apply Purview sensitivity labels to files that must never be summarised or extracted. This ensures that even with the convenience of chat, protected content stays protected.

3) Set sensible admin controls. Examples include adjusting chat history retention to match regulatory needs, explicitly disabling web grounding for users handling regulated data (since it is enabled by default), restricting access to users with appropriate licenses, and configuring DLP policies to block upload of sensitive file types. These settings strike a balance between productivity and risk containment. Remember that Copilot Chat’s protection model is based on governing what users can share into the tool rather than governing automatic access to tenant data.

4) Train users and publish clear policies. Use scenario-based training to show what is and is not appropriate to share with AI, and publish quick reference guides. Reinforce that Copilot Chat is the sanctioned route for AI assistance so employees do not feel compelled to use external services.

5) Monitor adoption and behaviour. Use Purview audit logs and activity reports to track usage, blocked uploads and sensitive term patterns. Dashboards with key indicators make it easy to spot unusual patterns and measure the impact of controls.

6) Decide when to expand to full Microsoft 365 Copilot. Pilot Copilot Chat first to capture usage and address policy adjustments. If demand grows and you require deeper, app-level assistance that uses richer tenant context, plan a phased rollout of Microsoft 365 Copilot with stronger governance and targeted training. Review compliance posture and user feedback before scaling.

Conclusion

Copilot Chat and Microsoft 365 Copilot are complementary: Copilot Chat provides a fast, chat-based entry point that can be configured and governed quickly, while Microsoft 365 Copilot offers deeper, app-integrated assistance when you are ready for it. For organisations concerned about shadow AI, Copilot Chat is an effective first-line defence because it delivers the convenience employees want while keeping data within your organisation and applying enterprise controls.

Start by enabling Copilot Chat for a pilot group, lock down sensitive data with DLP and sensitivity labels, train users on acceptable AI use, and monitor behaviour through Purview. If you need richer contextual assistance later, consider a controlled rollout of Microsoft 365 Copilot. Together these steps let you embrace AI while reducing the risks of unsanctioned consumer tools.

Key resources and further reading:

• Microsoft Copilot overview and architecture
• Copilot Chat documentation
• Microsoft 365 Copilot data protection
• Data loss prevention in Microsoft 365

Why Microsoft Ignite 2025 Matters for Partners

Ignite defines Microsoft’s roadmap and your investment priorities

Ignite is Microsoft’s annual signal of product direction, pricing/licensing changes, and partner program updates. The 2025 theme - agentic enterprises powered by Agent 365, Work IQ, Fabric IQ, and Microsoft Foundry - shifts partner monetisation from one‑off projects to repeatable IP, subscription managed services, and marketplace products grounded in governed data and enterprise security.

Who benefits most

• ISVs: to package vertical agents and Copilot extensions as transactable products.
• SIs: to design agent governance, integration and enterprise rollouts at scale.
• MSPs/CSPs: to operate, monitor, and optimize agent platforms (agent operations, AI FinOps, security).
• All partners: to use the unified marketplace, resale-enabled offers and co‑sell to scale distribution.

Key Announcements

Agent 365: a tenant-level control plane for agents

Agent 365 centralises lifecycle management, observability, policy and governance for AI agents and Copilots across the tenant. For partners, it’s the new surface for managed services; monitoring, policy enforcement, incident response, and compliance for agent behavior and integrations.

Partner plays: agent governance assessments, runbook automation and managed agent operations.

Work IQ & Fabric IQ: intelligence layers that ground agents

Work IQ interprets work context (documents, calendars, conversations) while Fabric IQ brings a governed semantic layer across enterprise data. Together they reduce hallucinations and make agent outputs reliable and auditable.

Partner plays: AI‑ready data foundations, semantic modeling on Fabric, role-based dashboards and subscription analytics services.

Microsoft Foundry & Agent Factory: tooling for repeatable agent IP

Foundry (Azure AI Foundry evolution) and Agent Factory provide modular frameworks, CI/CD patterns, and tooling to build multi‑agent systems that are testable and deployable at enterprise scale.

Partner plays: packaged vertical agents, “build-with” co‑development engagements, and marketplace-ready agent products.

Copilot & GitHub Copilot enhancements: from assistant to agentic actions

Copilot is becoming more capable of multi‑step, agentic behavior (acting on behalf of users) and integrates tighter with Teams, Microsoft 365, and developer workflows. GitHub Copilot remains essential for developer productivity and secure development patterns.

Partner plays: Copilot readiness/adoption programs, developer acceleration packages, and Copilot templates tailored to business roles.

Security & Identity: Entra, Baseline Security Mode, Security Copilot

Microsoft strengthened identity and agent security with Entra enhancements, Baseline Security Mode, and deeper Security Copilot integration. Protecting both human and agent identities is now a central trust requirement for enterprise AI.

Partner plays: identity hardening packages, agent MDR (managed detection and response), compliance mapping and responsible AI governance services.

Core Themes from Ignite, What They Mean for Partner Business Models

1) Agents are a platform-level opportunity

Agents will be embedded in business processes, not just chat. Partners need to move from single-use bots to multi-agent orchestration, lifecycle management, and integration playbooks.

2) Data foundations determine success

Work IQ and Fabric IQ show that reliable agents require semantic, governed data. Data engineering and continuous data ops become ongoing, revenue-generating services rather than one-time projects.

3) Security & governance are differentiators

Businesses will pay for demonstrable controls around data access, auditability and human-in-the-loop safeguards. Packaging security and governance with agents justifies premium pricing and unlocks regulated industries.

4) Marketplace + co-sell enable scale

The unified marketplace, AI apps/agents category, and resale-enabled offers let partners push IP to market faster and use Microsoft’s field motion to accelerate deals.

Go‑to‑Market Opportunities, Concrete Plays

1) Vertical & Industry Agents (Productise IP)

• Examples: Claims Intake Agent for insurance, Clinical Intake Agent for healthcare, Sales Development Agent for B2B SaaS.
• How to monetise: Package as SaaS (marketplace listing) + managed services (setup, governance, and run).

2) Copilot Readiness & Adoption Programs

• Deliver fixed‑scope readiness assessments (licensing, tenant config, data readiness, security).
• Offer role-based training cohorts, adoption campaigns and ROI dashboards powered by Fabric/Power BI.

3) Managed Agent Operations & AI FinOps

• Offer 24/7 monitoring, incident response, drift detection and tuning using Agent 365 telemetry and Entra/Defender signals.
• Provide AI FinOps to monitor model usage, optimise costs and forecast consumption across Azure/Fabric.

4) Marketplace & Resale-Enabled Channel Offers

• Productise software + service bundles and enable resale so CSPs/MSPs can sell locally.
• Use App Accelerate and co-sell to qualify for Microsoft field support and incentives.

How Partners Should Prepare (90‑Day Prioritised Plan)

Weeks 1–2: Align leadership & pick focus

• Brief leadership with the Ignite Book of News and partner recap (use the links below).
• Decide your primary plays (one productised agent + one managed service or modernisation offer).

Weeks 3–6: Build a 4–8 week pilot and internal “Customer Zero”

• Design a short POC that demonstrates measurable impact (time saved, leads created, errors reduced).
• Run an internal pilot using Copilot/agent scenarios to gather metrics and refine IP.

Weeks 7–12: Productise & list on marketplace

• Package solution as a marketplace listing (software + services); enable resale if channel expansion is a goal.
• Prepare co‑sell materials and a one‑page value proposition for Microsoft field teams.

Ongoing (90–180 days): Scale and secure

• Launch a skilling program for sales and delivery; require role certifications for your core delivery team.
• Offer governance + security packages by default; embed Baseline Security Mode and Entra hardening in your deployments.
• Measure ROI for pilot customers and convert to managed services or longer-term contracts.

Conclusion: Move from Insight to Execution

Ignite 2025 makes one thing clear: the next wave of Microsoft-centric opportunity is not merely cloud migration or point automation; it’s building safe, governed agent ecosystems that deliver measurable business outcomes. Partners who rapidly productise vertical agent IP, offer managed agent operations and AI FinOps, and leverage the marketplace and co‑sell will capture disproportionate value.

Quick checklist (next steps)

• Brief executive team on Ignite highlights (Book of News, partner recap).
• Choose 1–2 pilot scenarios and run a 4–8 week POC.
• Define a productised offer (agent + managed service) and create a marketplace entry.
• Start a 90‑day skilling sprint using Partner Skilling Hub and Ignite on‑demand sessions.

Selected links and resources

• Ignite 2025 — Book of News
• Ignite 2025 — Partner recap
• Microsoft Foundry (Azure blog)
• Fabric IQ announcement
• Microsoft 365 Copilot & agent announcements
• Microsoft Security — Agentic era
• Marketplace updates and guidance

Every year, Microsoft partners collectively leave thousands of unused Technical Presales and Deployment Services hours untouched. Hours that could accelerate deals, unblock AI projects, and drive millions in untapped revenue.

Your organisation already pays for one of Microsoft’s most powerful partnership benefits: Technical Presales and Deployment Services (TPD). TPD provides up to 50 hours of one-to-one consultation from Microsoft Partner Technical Consultants (PTCs) who validate architectures, remove sales blockers, and help partners close complex deals faster.

Competitors who use TPD report shorter deal cycles, higher win rates, and faster practice growth. Yet, most partners never activate it. For practice leaders navigating cloud and AI complexity, TPD isn’t support; it’s a strategic edge hiding in plain sight.

Why This Matters Now

With AI reshaping customer expectations and cloud architecture evolving faster than most teams can upskill, partners can’t afford slow learning curves.

TPD compresses months of capability-building into hours, giving your team direct access to Microsoft engineers who’ve seen hundreds of similar deployments and know exactly what works.

What is Technical Presales and Deployment Services?

Technical Presales and Deployment Services (TPD) provides Microsoft partners with personalised, one-to-one consultations from Partner Technical Consultants (PTCs) who deliver deep expertise across Microsoft's cloud and AI portfolio. Unlike generic support channels, TPD offers tailored assistance for planning, building, selling, and growing Microsoft-based solutions.

Despite being included in Solutions Partner designations and legacy competencies, TPD represents one of the most underutilised benefits in the Microsoft partner ecosystem. Industry observations suggest many partners fail to leverage their allocated advisory hours, leaving substantial value unrealised. One Microsoft Partner noted this represents "a huge lost opportunity" for partners who don't use it.

Core TPD Service Areas

Plan Your Business Strategy

Partner Technical Consultants assess organisational technical capabilities and identify growth opportunities, including:

• Technical capability assessment and skills evaluation
• Service and application development roadmaps
• Cloud Solution Provider (CSP) enrollment planning
• Technical architecture design for CSP programs

Build Solutions and Applications

TPD supports the entire development lifecycle from initial vision to marketplace publication:

• Azure Infrastructure: Migration planning, application modernisation, SAP on Azure, IoT implementations
• Business Applications: Dynamics 365, Power Platform, Microsoft 365 Copilot for Sales
• Data and AI Solutions: Data Platform Modernisation, Advanced Analytics, Artificial Intelligence
• Modern Workplace and Security: Microsoft 365 cloud productivity, device management, security implementations
• CSP Technical Architecture: Partner Center API integration, GDAP security management, automation development

Accelerate Sales Opportunities

Partner Technical Consultants help close deals by:

• Creating compelling demos and proof-of-concepts
• Removing technical sales blockers
• Providing technical validation for customer presentations
• Assisting with competitive positioning
• Articulating value propositions for complex Azure, AI, and security opportunities

Grow and Support Post-Sale

TPD continues supporting partners after deal closure with:

• Implementation guidance and best practices
• Customer footprint expansion strategies
• Ongoing solution deployment support
• Technical optimisation recommendations

TPD Advisory Hours by Benefit Package

Strategic Value for Practice Leaders

De-Risk Complex Opportunities

High-value deals often carry technical complexity that can stall progress or derail proposals. Access to Microsoft technical expertise at critical junctures, without depleting billable resources, provides competitive advantage. Partner success stories demonstrate how engagement with Microsoft specialists helped close six-figure infrastructure migration deals at risk to competitors by providing architectural validation and positioning within 48 hours.

Accelerate Capability Development

TPD consultations provide fast-tracked knowledge transfer rather than requiring months of internal expertise development. Teams gain insights from consultants who have seen hundreds of similar implementations, avoiding common pitfalls and adopting proven patterns immediately.

Maximise Partnership Return on Investment

Solutions Partner organisations already pay for these benefits through designation requirements. Leaving advisory hours unused equals leaving money on the table, particularly when competitors may leverage this advantage to close deals faster.

Bridge Sales and Technical Team Gaps

Partner Technical Consultants can join customer calls, provide technical validation, and address architecture concerns that sales teams aren't equipped to handle, strengthening credibility and deal momentum.

How to Activate TPD Benefits

Step 1: Access Partner Center

Navigate to Partner Center Benefits section and select "Technical pre-sales & deployment"

Step 2: Choose Benefit Package

Select the benefit package you want to utilise for the engagement

Step 3: Provide Case Details

Submit case title, description, and relevant product information with technical scenario context

Step 4: Include Contact Preferences

Provide full international dial code and time zone preferences for consultation scheduling

Step 5: Select Regional Preferences

Choose country/region and preferred language for proper routing to appropriate Partner Technical Consultant

Response Timeline

Microsoft commits to Partner Technical Consultant response within two business days, with consultation delivery timelines mutually agreed upon based on technical scenario complexity.

Real-World TPD Application Scenarios

Azure Infrastructure Projects

Migration planning, application modernisation, SAP on Azure deployments, analytics, and IoT implementations receive dedicated infrastructure specialist support.

Data and AI Initiatives

Consultants eliminate technical blockers in Data Platform Modernisation, Advanced Analytics, and Artificial Intelligence scenarios, critical as organisations implement AI capabilities.

CSP Business Development

Direct bill CSP partners receive guidance on tenant architecture, security requirements, Partner Center automation using APIs and SDKs, and GDAP implementation, operational foundations determining CSP program success.

Marketplace Publishing

ISVs and solution builders receive end-to-end guidance from solution architecture through marketplace listing and co-sell submission, navigating processes that often confound first-time publishers.

Modern Workplace and Security Sales

Assistance closing Microsoft 365, device management, and security solutions helps partners articulate business value and technical implementation paths resonating with decision-makers.

Integration Strategies for Practice Leaders

Integrate TPD Into Sales Processes

Build TPD engagement into standard opportunity qualification processes. When pursuing deals above specific thresholds or involving unfamiliar technologies, proactively schedule Partner Technical Consultant consultations before customer presentations, not after technical objections emerge.

Enable Technical Teams

Encourage solution architects and technical leads to use advisory hours for architecture validation before customer proposals. This peer review from Microsoft experts catches design flaws early and strengthens technical credibility.

Support Practice Development Initiatives

When building new service offerings or entering unfamiliar solution areas, leverage TPD for capability assessment and development roadmaps. Partner Technical Consultants identify skill gaps, recommend training paths, and provide technical foundations accelerating time-to-market.

Optimise CSP Operations

CSP partners should schedule regular consultations on automation, security architecture, and customer management optimisation to ensure Microsoft best practices and maximise operational efficiency.

Competitive Advantages from using TPD

Organisations that systematically leverage TPD services gain advantages competitors may not realise exist:

• Faster deal cycles through immediate technical validation access
• Higher win rates when competing against partners without this support
• Reduced implementation risk through architecture review
• Stronger customer relationships built on technical confidence
• Accelerated capability development without proportional training time investment

Supported Products and Technologies

All cloud and cloud-hybrid solutions are supported across the Microsoft technology stack, including:

• Microsoft Azure (infrastructure, platform services, data, AI)
• Microsoft Dynamics 365 and Power Platform
• Microsoft 365 (productivity, collaboration, security)
• Cloud Solution Provider program technical architecture
• Microsoft commercial marketplace solutions

Products in private or public preview receive best-effort support for non-production environments with no guarantee on information availability or response time.

Why Senior Leaders Should Prioritise TPD

Technical Presales and Deployment Services represents a strategic asset requiring active management, not passive acknowledgment. For practice leaders responsible for revenue growth, margin protection, and capability development, TPD provides direct access to Microsoft expertise accelerating all three objectives.

TPD Does Not Replace Internal Capabilities, It Amplifies Them

The service validates and strengthens customer-facing expertise rather than substituting for it. No additional budget is required, it's already included in benefits earned through partnership investments.

The Critical Question for Decision Makers

Can your organisation afford to leave this advantage unused while competitors potentially leverage it to close deals faster, build capabilities more efficiently, and grow Microsoft practices more effectively?

Summary: Activating Your Partnership Investment

Your partnership investment has already secured TPD access. The only remaining step is activation. Log into Partner Center, navigate to Benefits > Technical pre-sales & deployment, and submit your first request to begin leveraging Partner Technical Consultant expertise for planning, building, selling, and growing your Microsoft practice.

Frequently Asked Questions About TPD

Who is eligible for Technical Presales and Deployment Services?

Partners with Solutions Partner designations, legacy Gold/Silver competencies, Partner Success benefits packages, or Microsoft Action Pack subscriptions can access TPD services.

How many advisory hours are included with Solutions Partner designations?

Solutions Partner organisations receive 50 advisory hours with unlimited technical presales sessions.

What is the response time for TPD requests?

Microsoft commits to Partner Technical Consultant response within two business days of case submission.

Can TPD consultants join customer calls?

Yes, Partner Technical Consultants can participate in customer engagements to provide technical validation and address architecture concerns.

What technologies does TPD support?

All cloud and cloud-hybrid Microsoft solutions are supported, including Azure, Dynamics 365, Power Platform, Microsoft 365, and CSP technical architecture.

How does TPD differ from standard Microsoft support?

TPD provides personalised consultations focused on partner business growth, sales enablement, and solution development rather than break-fix technical support.

Can I use TPD hours for CSP technical architecture?

Yes, direct bill CSP partners receive dedicated support for tenant architecture, Partner Center API development, GDAP implementation, and customer management automation.

What is Shadow AI and Why Should Microsoft Partners Care?

Shadow AI refers to the widespread use of unapproved consumer AI tools in workplace environments. Microsoft's latest research shows that 71% of UK employees have used unapproved consumer AI tools at work, with 51% doing so every week.

The Scale of the Shadow AI Challenge

The numbers reveal both massive opportunity and urgent risk:

• 12.1 billion hours saved annually across the UK economy through AI adoption
• £208 billion worth of productivity gains from current AI usage
• Only 32% of employees express concern about company data privacy
• Just 29% worry about IT security implications
• 28% report their companies don't provide work-approved AI options

Why This Matters for Microsoft Partners in 2025

Microsoft's global research indicates that 82% of business leaders view 2025 as a turning point for AI strategy. This creates an unprecedented window of opportunity for Partners to position themselves as trusted AI advisors before market saturation occurs.

Five Strategic Service Opportunities for Microsoft Partners

1. What Services Can Partners Offer for Shadow AI Assessment?

Shadow AI Assessment and Governance Services represent the most immediate opportunity. Develop comprehensive assessment frameworks that help organisations:

• Audit current Shadow AI usage across all departments and roles
• Identify data exposure risks and regulatory compliance gaps
• Create AI governance policies aligned with industry-specific regulations
• Establish approval workflows for future AI tool adoption
• Implement monitoring systems to track ongoing Shadow AI usage

Revenue Opportunity: Position this as a foundational consulting engagement that naturally leads to implementation services.

2. How Can Partners Accelerate Enterprise AI Adoption?

Enterprise AI Acceleration Programs address the gap where employees are already saving 7.75 hours per week with unapproved tools. Create structured programs that:

• Rapidly deploy Microsoft 365 Copilot across organisations with proper security controls
• Implement Microsoft Copilot Studio for custom, industry-specific AI solutions
• Provide comprehensive change management to transition users from consumer to enterprise tools
• Deliver targeted training programs that tap into employees' existing AI enthusiasm
• Establish ROI measurement frameworks to demonstrate business value

Key Insight: Organisations can achieve even greater productivity gains with properly implemented enterprise solutions compared to the current 12.1 billion hours saved through Shadow AI.

3. What Security and Compliance Services Are Most Critical?

AI Security and Compliance Consulting addresses the alarming security awareness gap. With only 32% of employees concerned about data privacy, organisations need specialised expertise to:

• Conduct AI-specific security risk assessments using frameworks like NIST AI RMF
• Implement data loss prevention (DLP) policies specifically designed for AI interactions
• Ensure compliance with GDPR, industry regulations, and internal policies
• Develop incident response procedures for AI-related security events
• Create employee training programs to raise security awareness

Positioning: Frame this as essential business protection, not optional enhancement, with potential regulatory fines reaching millions of pounds for non-compliance.

4. How Should Partners Develop Custom AI Solutions?

Custom AI Solution Development leverages the specific use cases identified in the research:

For Communication Tasks (49% of users):

• Build AI-powered email and document drafting systems using Microsoft Graph
• Develop secure chat and collaboration AI agents
• Create automated response systems for customer service

For Report and Presentation Creation (40% of users):

• Implement Power BI AI features for automated reporting
• Develop custom PowerPoint AI integration using Office APIs
• Create industry-specific report generation tools

For Finance-Related Tasks (22% of users):

• Build secure financial analysis tools using Azure AI Services
• Develop automated expense reporting and budget analysis systems
• Create compliance-focused financial AI applications

5. What Strategic Services Do Organisations Need Most?

AI Adoption Strategy and Change Management capitalises on the more than doubling of AI optimism this year. Organisations need strategic guidance to:

• Develop comprehensive AI strategies aligned with specific business objectives
• Create communication plans that address the 36% of employees who still don't know where to start with AI
• Implement phased adoption approaches that build on existing Shadow AI usage patterns
• Establish success metrics beyond the current 7.75 hours saved per week
• Build AI governance frameworks for sustainable, secure adoption

Frequently Asked Questions About Shadow AI for Microsoft Partners

What is the biggest risk of Shadow AI for organisations?

The primary risk is uncontrolled data exposure. With 49% of employees using AI for workplace communications and 22% for finance-related tasks, sensitive company and customer data may be processed by systems without adequate security controls, potentially leading to data breaches, regulatory violations, and competitive disadvantage.

How quickly should Partners act on Shadow AI opportunities?

Immediately. The research shows AI optimism has increased from 34% to 57% in just 10 months, and 82% of business leaders view 2025 as a turning point. Early-moving Partners will establish themselves as trusted AI advisors before the market becomes saturated.

What Microsoft technologies are most relevant for addressing Shadow AI?

The core Microsoft AI stack includes:

• Microsoft 365 Copilot for productivity AI with enterprise security
• Azure OpenAI Service for custom AI applications with data residency
• Microsoft Copilot Studio for building custom AI agents and workflows
• Azure AI Content Safety for filtering and monitoring AI interactions
• Microsoft Purview for AI governance and compliance management

What industries should Partners prioritise for Shadow AI services?

The research shows highest AI usage in:

1. IT & Telecoms - Early adopters needing governance
2. Sales - High productivity potential with customer data risks
3. Media & Marketing - Creative AI use requiring brand protection
4. Architecture & Engineering - Technical AI adoption with IP concerns
5. Finance & Insurance - Regulatory compliance critical

The Urgency Factor: Why 2025 is the Turning Point

Market Timing Indicators

• Employee AI adoption rate: 71% already using consumer tools
• Weekly usage frequency: 51% using AI tools every week
• Productivity impact: 12.1 billion hours saved annually demonstrates proven ROI
• Security awareness gap: Only 32% concerned about data privacy creates urgent need
• Leadership recognition: 82% of business leaders see 2025 as AI turning point

Competitive Advantage Window

Organisations implementing enterprise AI now will gain significant advantages over those delaying:

• First-mover productivity gains beyond current 7.75 hours saved per week
• Enhanced security posture while competitors remain vulnerable
• Employee satisfaction by providing approved tools employees want to use
• Regulatory compliance before enforcement intensifies
• Market differentiation through AI-powered capabilities

Implementation Roadmap for Microsoft Partners

Immediate Actions (Next 30 Days)

1. Audit your AI capabilities - Assess current team skills and identify training needs
2. Develop Shadow AI assessment methodology - Create standardized audit processes
3. Build compelling business cases - Use the £208 billion productivity statistic effectively
4. Identify target prospects - Focus on organisations in high-usage industries

Short-term Strategy (90 Days)

1. Invest in Microsoft AI certifications - Achieve AI specialisations and competencies
2. Create demonstration environments - Build proof-of-concept solutions
3. Develop industry-specific offerings - Tailor services to vertical markets
4. Build strategic partnerships - Connect with security and compliance specialists

Long-term Growth (12 Months)

1. Establish AI practice leadership - Position as go-to AI transformation partner
2. Scale delivery capabilities - Build repeatable methodologies and templates
3. Expand service portfolio - Add advanced AI services and managed offerings
4. Measure and optimize - Track ROI and refine service delivery

Conclusion: From £208 Billion Risk to Strategic Opportunity

The Shadow AI phenomenon represents validation that AI has become essential to modern work, with UK employees collectively saving 12.1 billion hours annually. The challenge for organisations isn't whether to adopt AI, it's how to do it securely, compliantly, and strategically.

Key Takeaways for Microsoft Partners

• 71% Shadow AI usage creates immediate market demand for governance services
• £208 billion productivity impact demonstrates clear ROI for enterprise AI investment
• Low security awareness (only 32% concerned) creates urgent need for expert guidance
• 2025 turning point recognized by 82% of business leaders creates time-sensitive opportunity
• Five service categories provide clear revenue opportunities from assessment to implementation

The Partner Advantage

Microsoft Partners have unique advantages in addressing Shadow AI challenges:

• Enterprise-grade technology stack through Microsoft AI services
• Security and compliance expertise built into Microsoft cloud platform
• Proven business relationships with decision-makers who need AI strategy
• Technical capabilities to implement secure, scalable AI solutions
• Industry knowledge to create vertical-specific AI applications

The Shadow AI revolution is happening with or without organizational approval. Microsoft Partners have the expertise, tools, and opportunity to guide this transformation toward secure, productive outcomes.

The question isn't whether organizations will adopt enterprise AI, it's whether they'll choose your guidance to do it right.

--

About This Research: Based on Microsoft research conducted by Censuswide in October 2025, surveying 2,003 UK employees across multiple industries and organization sizes. Additional insights from Microsoft's global Work Trend Index and "2025: The year the Frontier Firm is born" report.

In this new reality, partners who re-architect their go-to-market (GTM) strategy for AI discovery will capture buyer attention and accelerate growth. Those who cling to legacy tactics won't just fall behind, they will be invisible. I have seen so many examples of partners whose websites or marketplace listings contain old branding, out of date credentials, or bury their value in undiscoverable vaults that traditional search engines, let alone AI, ignore.

Think about your next potential customer, or a decision maker in an existing customer, starting to research solutions to their business challenges. Ask yourself: how do we show up?

Why AI Optimisation Is Existential for Microsoft Partners

AI optimisation is not a minor tweak to SEO. Generative engines prioritise context, authority, and clarity. They reward content that provides credible, question-driven answers, making citation-worthy insight more valuable than backlink volume.

For Microsoft partners, this shift is a filter. If your expertise is not structured for AI citation, you are disqualified before the race begins, no matter how strong your technical credentials are.

The GTM Shifts Required for AI Discovery

Your First Moves: Become Machine-Readable

Your expertise must be both human-readable and machine-ready. Start here:

• Restructure key pages into question-answer formats with concise summaries at a UK Year 9–11 reading level.

• Implement schema markup (like Organisation, Service, and FAQ) and Microsoft-aligned metadata for every service and case study.

• Audit your site for AI crawler accessibility (OAI-SearchBot, GPTBot) and ensure your robots.txt file permits crawling where needed.

• Standardise your brand and service names across all partner directories, marketplaces, and review sites to feed AI context engines.

• Publish referenceable integration stories with Microsoft in formats that AI tools can easily parse and cite.

The Unavoidable Cost of Inaction

Your next customer is already using an AI assistant to create their partner shortlist, often before visiting a single website. If your practice is not citable in this new landscape, your technical excellence is irrelevant.

Moving to an AI-optimised GTM strategy now will allow you to:

• Establish leadership as a trusted digital authority.

• Enter consideration cycles earlier and convert faster.

• Defend margins in an ecosystem that rewards proactive solutions.

The Mandate

AI optimisation is not a future trend; it is the new baseline for visibility. Microsoft partners who act decisively will define the next era of growth. The playbook is clear. The only question is whether you will lead or be left out of the answer.

Accessing these insights is easy at the customer level, from a single portal. If you're a partner dealing with one or two Azure customers, it's manageable to flit between customer portals manually. But what if you're a partner with 20, 50, 500 customers or even more? The scale of Azure can present unique challenges to managed service providers (MSPs), particularly when it comes to managing cloud operations efficiently.

Enter Azure Lighthouse

Azure Lighthouse allows managed service providers to access multiple customer environments from a single portal. Or, "multitenant management with scalability, higher automation, and enhanced governance", as Microsoft put it.

Most CSP resellers will have control over a whole subscription, using AOBO, so it's already helpful where partners have set up this kind of privileged access, but it's not the whole solution.

To put this to the test, I took my demo partner, created the appropriate ARM template, and deployed it to my other Azure subscription. Within a few moments, I was able to see the subscription in the partner "My customers" blade in the Azure portal and Azure Advisor insights aggregated there.

I knew this would be powerful, but I also know that very few people have this level of access within a partner - rightly. I wanted to find a way to make this more accessible, but in a way that didn't jeopardise governance.

Enter Azure Resource Graph Explorer and Power BI

Azure Resource Graph makes it easy to query across a set of subscriptions to get details on things like the properties returned by resource providers without needing to make individual calls to each subscription.

Using a combination of Azure Resource Graph Explorer and Power BI, I was able to create a very rudimentary report that gave me the Azure Advisor recommendations for the subscriptions I manage.

💡 Imagine if you were to combine this dataset with information like the account owner at the partner, or other performance or sales information, to create a holistic view for the business to identify opportunities.

Summary

While there'll be considerations around access, security, and maintaining the reporting suite, it is possible to build a streamlined way to manage Azure Advisor recommendations across customers. You can add value to your customer base by acting on this data.

Bottom line: it gives people a reason to speak to their customers, and therefore create opportunities to sell more. This might be more Azure services, professional services, or managed services that you offer under a managed agreement.

Further Watching

💡 Do you have any favourite devices that have improved your workflow? Let me know in the comments.

Peripherals

Work

• Microsoft Sculpt Ergonomic Desktop keyboard and mouse. I've had this set up for years and have been using Microsoft's ergonomic keyboards for over 20 years. I love them. It's quiet, comfortable, and easy to store out of the way for when I'm gaming. I think it's now discontinued, and I'll be gutted when I have to replace it.

Fun

• Ducky Shine 7 mechanical keyboard. When I'm gaming, it's time to switch to the mechanical keyboard and I love the feel of the Ducky Shine 7, it's a solid unit with Cherry MX brown switches that sound lovely when typing.
• Razer DeathAdder V2 wired mouse. For games like Fortnite, Call of Duty, etc. this is my go-to mouse.
• Razer Naga X wired mouse. For games like Sea of Thieves I switch to the Naga for its thumb buttons so I can easily call up food, weapons, shovel, etc.

Both

• Stream Deck XL, 2, and Pedal devices. Giving me something like 50 customisable buttons between them, these are how I control a lot of my live streaming effects, as well as my lights and other automations.

Audio

• TC Helicon GoXLR audio interface. Recently discontinued, this was an expensive but very useful device. It's got four faders, preamps powerful enough to handle the Shure SM7b, and a dedicated swear and cough button as well as a bunch of other handy features (mostly for streaming). The dedicated cough button is a lifesaver I never thought I'd get so used to using.
• Shure SM7b microphone. Let's be clear: this is overkill, but it is an excellent microphone.
• Arctis Pro Wireless headphones. These mean I get practically zero latency when I'm monitoring my mic and I can use them with my PC, Xbox and Nintendo Switch. When it's noisy or I'm on a sensitive call, I switch to using these from my speakers. I can't wear them for more than a couple of hours without my head hurting though, which might be because the band is wearing out. I am experimenting with switching to a pair of wired in-ear monitors though... so, these might not be around for too much longer!

Video

• Sony a6000 mirrorless camera. Fitted with a Sigma 16mm f1.4 DC DN lens this lovely camera sits on a tripod and is my main webcam (I have a Logitech Brio 4K and Microsoft LifeCam for other purposes, which are more related to streaming). I connect it to the PC using an Elgato Cam Link 4K dongle and it is probably the thing people comment on the most, since Teams can handle the high quality. It looks far better than every webcam I've seen. Good lighting is important whatever camera you're using.

On The Go

• Microsoft Surface Laptop 5 13. When I'm out and about for work, this is my main device. I recently upgraded, coming from a Surface Laptop 3 15. I prefer the smaller form factor of the 13, it's lighter but still does everything I need it to.
• Apple iPhone 15 Pro Max. I can get a surprising amount of work done on this, from taking Teams calls, to editing documents, plus it takes great pictures, and the battery life is pretty decent. And it's USB-C!
• Poly Voyager Focus 2 / Voyager 5200 Bluetooth headsets. I've been a fan of Plantronics/Poly for years now, their kit is great. If I'm not at home, or in the car, chances are I'm using one of these devices. My only gripe is that I find the 5200 doesn't always play well with my iPhone.

Display & Other

• 3x 27" monitors; 2x Dell 1440p and 1x AOC 1080p. I prefer multiple monitors over one giant widescreen, and the lower resolution third monitor is great for screen sharing as I can be sure that people can actually see what I'm sharing! No more "can you zoom in on that spreadsheet please" when on calls.
• Elgato Key light and other LED lighting. Good lighting, natural or artificial is essential for good quality video.
• My PC! This is a self-build, and it's due some upgrades. It's running on an AMD Ryzen 7 3700X CPU, NVIDIA RTX 3090 GPU, with 32GB DDR4 3200MHz RAM.

Until next time...

If you found this newsletter interesting, why share it with your network? I'd love to know your thoughts or suggestions for future topics in the comments below.

I'm James Marshall, an Azure Success Manager at Microsoft, and if you find this content useful, please remember to subscribe and share this with your network. Thank you! 😎

Some Thoughts

In my last edition, I wrote about how being creative with your virtual machines, you could achieve better savings than defaulting to a reserved instance.

In this post we'll look at how Azure Savings Plans work, how they differ from reserved instances, and how they can help you optimise your infrastructure design and bring down your compute costs even further.

What are Azure Savings Plans?

Azure Savings Plans are a flexible and simple way to save money on Azure compute services, such as virtual machines, Azure Kubernetes Service, Azure App Service, Azure Functions, and more. Unlike reserved instances, which require you to specify the instance type, size, region, and operating system upfront, Azure Savings Plans only require you to commit to a certain amount of usage per hour, measured in dollars, for a one or three-year term. You can then use any eligible compute service in any region and any operating system, and the savings will automatically apply to your usage.

For example, if you purchase a one-year Azure Savings Plan for $100/hour, you can use any combination of compute services that add up to $100/hour, such as 50 VMs in one region, 25 VMs in another region, and 25 Azure Kubernetes Service clusters in a third region. You will pay the discounted rate for the $100/hour usage, and the regular pay-as-you-go rate for any usage above that amount.

How Azure Savings Plans Can Help You Optimise Your Infrastructure Design

One of the benefits of Azure Savings Plans is that they allow you to save money on your compute services without compromising on your infrastructure design. You can still use the best compute service for your workload, and you can still scale up or down as needed. You can also take advantage of Azure's global network of regions and availability zones and choose the best location for your applications and data. You can also use different operating systems, such as Windows, Linux, or hybrid, and enjoy the same level of savings.

By using Azure Savings Plans, you can also improve your infrastructure design by following some good practices, such as:

• Right-sizing your compute resources: You can use Azure Advisor, a free tool that provides personalised recommendations for optimising your Azure resources, to identify and resize any underutilised or overprovisioned compute resources. By right-sizing your compute resources, you can reduce your usage and your costs, and free up more capacity for your Azure Savings Plan.

• Using spot instances: You can use Azure Spot Virtual Machines, which offer up to 90% discounts on pay-as-you-go prices, for your interruptible or non-critical workloads, such as dev/test, batch processing, or backup. By using spot instances, you can lower your compute costs and your Azure Savings Plan commitment, and only pay for the compute resources you need.

• Using hybrid benefits: You can use Azure Hybrid Benefit, which allows you to use your existing eligible Windows Server and SQL Server licenses on Azure. By using hybrid benefits, you can lower your operating system costs and your Azure Savings Plan commitment and maximise the value of your existing licenses.

By following these good practices, you can not only save money on your Azure compute services, but also improve your infrastructure design and performance, and deliver better value to your organisation.

Conclusion

Azure Savings Plans are a fairly new pricing model that offers significant discounts on Azure compute services in exchange for a commitment of a consistent amount of usage for a one or three-year term. Azure Savings Plans can help lower compute costs compared to pay-as-you-go rates and reserved instances. Azure Savings Plans can also help you optimise your infrastructure design and performance, by allowing you to use any eligible compute service in any region and any operating system, and by following some best practices, such as right-sizing, using spot instances, and using hybrid benefits.

Interesting Stuff from Others

One of the best videos to recap and expand on reserved instances and Azure Savings Plans is from John Savill. If you're struggling to get your head around the conceptual differences and where they work together, you should check it out!

{% include youtubeplayer.html id="lBnKBV2r6lI" %}

Until next time...

If you found this newsletter interesting, why share it with your network? I'd love to know your thoughts or suggestions for future topics in the comments below.

In this edition, you'll find:

💭 My thoughts on selling Azure solutions.
📝 A summary of the latest Azure updates.
📰 Interesting articles I've seen around the web.

Some Thoughts

In a previous edition of Interesting Stuff, I wrote about how to price Azure solutions. Today, I want to explore how to sell them; particularly in a highly competitive market. Microsoft Azure is a powerful cloud platform that offers a range of solutions for different business needs. So, how do you stand out from other partners who offer similar products and services? How do you convince your customers that Azure is the best choice for their cloud journey?

The answer is simple: lead with business outcomes achieved through partner value. Partner value is the unique and differentiated value proposition that you offer to your customers as a Microsoft CSP partner. It is not just about the features and benefits of Azure, but also about how you can help your customers achieve their goals, solve their challenges, and transform their business with Azure. Partner value is what sets you apart from the crowd and makes you a trusted advisor to your customers.

What is My Value?

I like to say, slightly tongue-in-cheek, that the best way to sell Azure, is to stop selling Azure; or, to sell the outcome not the tech. When you focus on the outcome you unlock the higher margins and increased profitability we all seek.

Your partner value therefore is the combination of your expertise, experience, and services that you provide to your customers. It is the answer to the question: why should your customers buy your Azure-powered solutions and not someone else's? It's not a one-size-fits-all concept, but rather a tailored and customized approach that reflects your unique strengths and capabilities as a partner to deliver business outcomes for your customers.

Some examples of partner value are:

• Providing end-to-end solutions that span across the entire cloud lifecycle, from assessment and migration to optimization and management.
• Offering specialized skills and knowledge in a specific industry, domain, or technology area, such as healthcare, retail, or analytics.
• Delivering value-added services that enhance the customer experience, such as training, support, or development.
• Creating innovative (and repeatable!) solutions that make use of Azure's advanced features and capabilities, such as hybrid and multi-cloud orchestration, security, or AI.

How to Lead with Partner Value?

Unlike me, most people don't wake up and think about how much Azure they need in their life. They think about challenges that matter to their business; growth, competition, attracting and retaining talent, reducing operational costs, innovating, and so on. As the saying goes, "People don’t want to buy a quarter-inch drill. They want a quarter-inch hole!"

Leading with partner value means putting your value proposition at the forefront of your sales conversations with your customers by focusing on how you can help your customers achieve their desired outcomes, rather than just pitching the features and benefits of Azure. It means demonstrating your credibility, trustworthiness, and differentiation as a partner, rather than just competing on price and product. And it means creating a long-term relationship with your customers, rather than just closing a transaction.

Some tips on how to lead with partner value are:

• Understand your customers' needs, challenges, and goals, and align your partner value proposition to them.
• Use customer stories, case studies, and testimonials to showcase how you have delivered partner value to other customers in similar situations.
• Highlight your unique capabilities, credentials, and certifications that demonstrate your expertise and experience as a partner.
• Use funded offerings, proofs of concept, or assessments to show your customers the value of your solutions and services in action.
• Follow up with your customers regularly and provide ongoing support, guidance, and advice to help them optimize and maximize their Azure investment. <-- This one is SO important. Checking back on how your solutions are delivering for the customer can be the difference between them staying with you, or going elsewhere!
• Make sure every seller knows the pitch. From the newest hire, to the most tenured veteran, every seller in your business should be able to tell your story.

Conclusion

Selling Azure solutions is not just about selling a product, but also about selling a partnership. As a Microsoft CSP partner, you have a unique and differentiated value proposition that you can offer to your customers. By leading with partner value delivering business outcomes, you can stand out from the competition, win more customers, and grow your business with Azure.

Azure Updates

As ever, there's always something new to know, so here's a selection of updates you might find interesting: Get the digest!

Interesting Stuff from Others

I recently connected with Richard Tubb and I'm amazed our paths haven't crossed sooner! Richard invited me to record a 'bonusode' for his excellent podcast, talking about the recent Microsoft Ignite conference. It was an absolute pleasure, and I look forward to doing something again in the new year. Catch up on our chat and subscribe to his podcast for more great content!

Until next time...

If you found this newsletter interesting, why share it with your network? I'd love to know your thoughts or suggestions for future topics in the comments below.

In this edition, you'll find:

💭 My thoughts the recent Microsoft Ignite event.
📝 A summary of the latest Azure updates.
📰 Interesting articles I've seen around the web.

Some Thoughts

Last week, it was Microsoft Ignite, the annual event for technologists and IT Pros to come together and see the best of what's next in technology! If you couldn't attend in person, or virtually, I'd highly recommend watching the on-demand content. Microsoft CEO Satya Nadella in particular gave a brilliant keynote.

{% include youtubeplayer.html id="FZhbJZEgKQ4" %}

Without doubt, AI was at the heart of the event, but did you know there we more than 100 new updates across event facet of the Microsoft technology portfolio? Check out the famous Book of News and the official Microsoft blog to learn more about the key announcements.

Personally, my big take away from the event is that we're currently going through an even bigger leap forwards for technology than the one we saw with the mainstream availability of hyperscale cloud platforms like Microsoft Azure. For partners, more than ever, 'standing still is moving backwards' when it comes to developing practices and solutions that solve business challenges for customers. Most partners don't have to become a deep expert in every new thing, but the opportunity created by these innovations can't be ignored. Don't believe me? Check out the Work Trend Index Special Report; early users of Copilot for Microsoft 365 don't want to go back to working without it: 77% said they don't want to give it up.

There are too many updates to list out here, but some of my favourites include:

• The Microsoft Loop app is now generally available. I've become a big fan of Loop and love using it personally, and collaborating with my team.
• Dall-E 3 is now available in preview in Azure OpenAI Service. GPT-4 Turbo (preview) and GPT-3.5 Turbo 16K (GA) will be available in Azure OpenAI Service at the end of November 2023. GPT-4 Turbo model offers lower pricing, extended prompt length, and structured JSON formatting with improved efficiency and control.
• GitHub Copilot Chat will be generally available in December 2023. Bringing natural language as the new universal language for software development, GPT-4 powers Copilot Chat providing code-aware suggestions and code generation. I cannot tell you how blown away by this I was when I first experienced it.

What are you most excited about from Microsoft Ignite? Let me know in the comments!

Azure Updates

As ever, there's always something new to know, so here's a selection of updates you might find interesting: Get the digest!

Interesting Stuff from Others

Cloud Native Innovations with Mark Russinovich

Mark is Microsoft's Azure CTO, and a Technical Fellow, as well as an author, developer, artist - in fact, I'm not sure there's anything he can't turn his hand to. His sessions at any conference are always packed. Check out this session where he's in conversation about the latest innovations in cloud native computing.

{% include youtubeplayer.html id="vCJ1uS5ksuM" %}

How to Use Copilot in Microsoft Word to Create Awesome Documents

The productivity coach, and fellow colleague Stuart Ridout put this great video together looking at how best to use Copliot to your advantage when creating or editing Microsoft Word documents.

{% include youtubeplayer.html id="7JRaFAYSOgI" %}

Until next time...

If you found this newsletter interesting, why share it with your network? I'd love to know your thoughts or suggestions for future topics in the comments below.

In this edition, you'll find:

💭 My thoughts on the different strategies for pricing Azure solutions.
📝 A summary of the latest Azure updates.
📰 Interesting articles I've seen around the web.

Some Thoughts

If you've ever scratched your head and wondered how to make selling Azure a bit simpler, then this edition of Interesting Stuff is for you! By the time you've finished reading, you should have a good idea of two of the main ways you can take Azure solutions to market. Let's get started...

Cost + Margin

The method of applying a margin (or discount) to the consumed services bill each month has its pros and cons. The big benefit is it's agile, and well suited if you're designing bespoke solutions for your customers.

The downside is that it can expose a layer of volatility that creates overheads on your business each month. For example, local currency conversion fluctuates each month as the Pound Sterling changes versus the US Dollar. This means that over a 12 month period of unchanging Azure services use, the actual bill could be different every month.

A Small, Simplified Example

In the chart below, I've plotted what $1000 USD of Azure looks like in Pound Sterling over 12 months, accounting for FX changes each month and including a 5% profit margin on top. Over 12 months, the partner would make £486.06 of "profit" (not including any rebates, incentives, or other adjustments that happen in the back end).

{% include image.html url="/img/margin.png" description="An example chart of an Azure bill over 12 months, showing the fluctuation in profitability over time." caption="An example chart of an Azure bill over 12 months, showing the fluctuation in profitability over time." %}

This fluctuation can make it harder to plan and forecast your business, especially if too much of your success is pegged against the Azure bill itself; if the customer reduces their spend, you see less profit each month. It also likely means you're either having to charge for the value you create separately, or perhaps try and squeeze it into the margin you add.

Value Based Pricing

There is another way to approach this; value-based pricing. Instead of applying a fixed margin on top of the cost of the Azure services, you could sell a "solution" that encompasses the service costs, your created value (like the managed services, support, IP, etc. that you deliver), margin, etc. for a fixed price. A bit like a bundle. A bit like a mobile phone tariff.

You could get an PAYG tariff and only ever pay for what you've used. However, if you take a contract it's likely you pay a fixed amount each month for a bundle of minutes, data, or other services. The cost to the operator to provide those services will go up and down over the months, but they'll have priced their bundle to account for that and still make them money.

Back to our fictitious example, where this time we'll sell a solution bundle that is priced at £1000 per month to the end-customer. We arrived at this price by understanding the value we create, the amount our target customers might be willing to pay for the business outcome, and other factors. It includes the same $1000 USD of Azure services but this time the customer doesn't need to worry as it's the same price every month. They're paying for the business outcome (e.g. inclusive of your services, IP, and other value added work), not just the raw services.

{% include image.html url="/img/value.png" description="An example chart of an Azure bill over 12 months, showing the fluctuation in profitability over time." caption="An example chart of an Azure bill over 12 months, showing the fluctuation in profitability over time." %}

In this example, even though the underlying Azure bill changes each month, the partner would see an average profit margin of 24%, or £2,279 for the year. It shouldn't matter exactly how much Azure service is being consumed, because you're selling the overall value of your solution.

If the underlying Azure consumption rises through time, you may choose to revisit your pricing. For example, if you provide a managed backup solution and the customer ends up backing up huge amounts more data than your standard offer includes, you might 'upsell' another chunk of storage, or charge a per GB cost on top of your solution bundle price.

Have It Your Way

You could pick one or both of these strategies to go to market with Azure. The most successful partners create repeatable solutions, resorting to custom designs and bespoke pricing as little as possible. They also derive much of their profitability from the value created on top of the Azure consumption, not only relying on any back-end rebates or incentives. IDC estimates that by 2024, for every $1 of Microsoft revenue, there'll be up to $10.04 of partner ecosystem opportunity.

How much of that $10.04 are you capturing today? 🤔

Azure Updates

As ever, there's always something new to know, so here's a selection of updates you might find interesting: Get the digest!

Interesting Stuff from Others

How to in-place upgrade Windows Server in Microsoft Azure

Microsoft's Chief Evangelist for Azure Hybrid, Thomas Maurer, re-posted a blog to his timeline from earlier this year all about doing in-place upgrades on Windows Server on Azure. It's well worth checking out if you're wondering how it all works!

Until next time...

If you found this newsletter interesting, why share it with your network? I'd love to know your thoughts or suggestions for future topics in the comments below.

In this edition, you'll find:

💭 My thoughts on why spend optimisation should be your secret weapon.
📝 A summary of the latest Azure updates.
📰 Interesting articles I've seen around the web.

Some Thoughts

I've been out of my shed-office recently attending a few events. It's been a great reminder of how powerful it can be to connect with people in real life! At one of these events, I was taking part in a roundtable and the conversation moved towards Azure (you can imagine my excitement!). "Surely optimisation doesn't really help you if you're trying to grow your Azure revenue", someone said.

I can see why they'd think that. Helping to optimise deployments can lead to reduced spending. If you're making your money based on how much your customers use, then less is... less, right? 🤔

Let's look at it a different way.

Savings vs Investments

Before we dive in, it's worth calling out that this is going to be a simplified explanation of a complex topic that's given rise to whole fields of cloud management like FinOps, and cloud economists. Professionals who deeply understand the value of cloud technology its impact on a business.

In essence, the smart move is to position savings gained through optimisation work as opportunities to tackle other technology priorities on the customer's roadmap.

If left simply as "money saved", there's a risk that those funds will be swallowed up elsewhere in the customer and you'll have missed a chance to land a new project.

The most adept partners are those who've embedded themselves as trusted advisors. They excel at this positioning. Optimisation is their secret weapon because they know the customer's business priorities, the roadmap of things to do, and they can quickly spot how to apply savings in one area to a new project in another. They're highly curious about their customers.

Although, nobody has an infinite budget. Reinvesting savings — especially when supercharged with a funded offer — can help move along the roadmap more quickly, leading to increased cloud spend.

In Summary

Optimisation can be a way to save money, and sometimes that's what's needed when a customer is facing financial pressure. The savvy move is to align savings in one area to new projects in another making it part of the journey so that over time a customer will grow their spend.

Either way, it pays to be curious. You never know what opportunities you might find!

Azure Updates

As ever, there's always something new to know, so here's a selection of updates you might find interesting: Get the digest!

Interesting Stuff from Others

Azure SQL HA and DR

You can't go far in the Azure world without coming across the truly fantastic content-creating powerhouse that is John Savill. I swear he must have a time machine to allow him to create so much in depth, high quality stuff. In this video he unpacks everything you need to know about Azure SQL high availability and disaster recovery scenarios.

{% include youtubeplayer.html id="HTYxfXW3Fo" %}

How cool is GitHub Copilot Chat?

From one great content creator to another. I saw this great short video from April Edwards in my timeline this week. In it, she showcases the power of GitHub Copilot Chat and how it can transform the way you create and test Terraform scripts to write better infrastructure-as-code.

{% include youtubeplayer.html id="2KOw1DzkArw" %}

Until next time...

If you found this newsletter interesting, why share it with your network? I'd love to know your thoughts or suggestions for future topics in the comments below.

In this edition, you'll find:

💭 My top five tips for things you can do right now to kick start your Azure growth.
📝 A summary of the latest Azure updates.
📰 Interesting articles I've seen around the web.

Some Thoughts

Staring at me from the back of my desk is a little display, scrolling through things like time, social media stats, and the number of days until Christmas. Can you believe, it's just under 11 weeks away!? I should probably start planning for, and buying, presents. "This'll be the year I'm organised...", I tell myself naively.

Proactivity rather than procrastination is key for a successful Christmas, just as it is for an Azure practice. (I think I've just about got away with that segue! Don't @ me. 👀)

So, what five things would I suggest you go and do right now that can make a difference? Let's dive in.

5. Automate the Highs and Lows

I'm a big fan of working smarter not harder, so the automation of repeatable tasks has huge appeal. Being able to automatically flag customers who're demonstrating high growth or decline is a relatively simple way to get people better engaged.

By flagging the high growth customers, you can uncover opportunities to help them grow faster. You can also learn about the approaches that are most successful so that they can be repeated with other customers. With the declining customers, you can intervene early — before they become a churn risk — and offer ways to reinvest consumption savings to solve more business challenges, ensure satisfaction, and reduce the erosion in your monthly recurring revenue.

How: Seek ways to drive integration into your CRM systems using the various APIs available through Partner Center.

4. Use the Tools

Speaking of Partner Center, when was the last time you really explored the Insights workspace? In this section, with the right permissions, you can access a treasure trove of insights about your customers. It's in here that we surface up customer opportunities from the CloudAscent model.

There are other tools like Azure Advisor and Microsoft Defender for Cloud that can give you insights into practical measures you can take to improve your customer's Azure environment - a great start point for qualifying further projects to deliver.

How: Regularly review the customer opportunities insights for inclusion in your GTM campaigns.

3. Consumption Planning

Not every existing customer is a good candidate for growth. Some will be, some won't, so what? Next!

Consumption planning typically refers to work done with a customer on an individual basis, but it's worth taking the time at a partner level to broadly plan out priorities across your customer base. Which are the most important, or highest potential customers? What services or offerings do you have that are best aligned to their business objectives? How quickly can you qualify and deliver engagements and do you have the capacity to do enough to create the growth you need to hit your targets?

How: Using your unique knowledge of your customers and their needs, create a high level plan aligning your services and solutions, and a timeline of consumption (i.e. approximately how long it takes to ramp up to achieve a given amount). Map acquisition versus growth focused offerings, and ensure that you have capacity. If you're an indirect reseller, consider the services offered by your indirect provider as a way to bolster your own offerings.

2. Understand Acquisition vs. Growth

Every partner sets targets, but not every partner reverse engineers those targets to deeply understand key details, such as the proportion of a target that can or should be delivered from acquisition versus growth.

Every year there are 12 billing opportunities. The later in the year you deliver an outcome, the less financial impact it'll have in that year. But equally, every year you'll only have the capacity to onboard a certain number of customers. Understanding the split between acquisition and growth will help you prioritise your investments, people, and activities to achieve the right balance for success.

How: Use a tool, like my Cloud Target Calculator, to break down your targets and experiment with acquisition versus growth to figure out exactly how much Azure consumption should come from either tactic.

1. Make Someone Accountable

Perhaps the single most impactful thing you can do is to make someone accountable for growth. Sure, they won't be the one driving it entirely alone, but having someone with accountability for the outcome ensures focus and activity starts to take shape. It's a simple step, and doesn't have to mean hiring more people. Sometimes just the action of saying "you're owning this" is enough as a first step.

How: Identify the right leader (maybe it's you!) to take ownership for driving growth. Begin to carve out time in meetings to specifically focus on growth measures and activity. Agree on OKRs that align with your wider business goals and regularly and consistently review their progress.

Wrapping Up

There are so many things you can do to develop a growth-oriented Azure practice. But not everything requires investment in people, tools, or technology. Often starting with the smallest or simplest of activities can deliver positive outcomes, and create the space to get to the trickier stuff over time.

Bottom line? Start somewhere, do something. I once heard the phrase "start by starting", and it's so true.

Azure Updates

As ever, there's always something new to know, so here's a selection of updates you might find interesting: Get the digest!

Interesting Stuff from Others

DTX Europe

Last week, I had the privilege of attending DTX Europe in London. It was a weird experience as I'm used to being the one exhibiting at these types of events, having done BETT for many years.

{% include image.html url="/img/hannahfrydtx.jpg" description="Professor Hannah Fry" caption="Professor Hannah Fry delivering her keynote speech at DTX Europe" %}

One of my favourite sessions was the keynote from Professor Hannah Fry, a brilliant mathematician, author, and presenter on everything from YouTube to the BBC. Her perspective on AI and its potential was fascinating, and you can hear from her on the topic on her podcast. Definitely one to check out!

The Copilot Cheesewheel

There's a lot of innovation happening at Microsoft, across seemingly every product and service. Copilots and AI technology are rapidly transforming the way we can work with our tools, it can sometimes be tricky to get a singular view of where it all fits together. Luckily, longstanding Microsoft MVP Alex Pearce has created the Copilot Cheesewheel that seeks to do just that! I highly recommend following his content on the topic, as I know he has lots more to come in this space...

Until next time...

If you found this newsletter interesting, why share it with your network? I'd love to know your thoughts or suggestions for future topics in the comments below.

In this edition, you'll find:

💭 Some thoughts on "shifting left" and being proactive around lifetime value growth.
📝 A summary of the latest Azure updates.
📰 Interesting articles I've seen around the web.

Some Thoughts

Noticing the Ordinary

Do you ever pause to appreciate the ordinary? Let's be honest, most of us don't. With customers, our attention gravitates towards the high-revenue generators or the high-maintenance ones. The "ordinary" customers, who silently support our business, often go unnoticed.

Now, when selling tangible products, overlooking these customers might not be so bad. After all, they pay upfront. They can't return half a server, right?

However, in a recurring billing model, this changes. If a customer reduces their usage, it hits your monthly billing. It might start with a couple of customers, but as your client base expands, this drop in usage can balance out your growth, stalling your progress.

Shift Left

In software development and testing, there's the concept of "shift left". Simply, the idea is that rather than leaving testing until the end of the development cycle you should test earlier and all the way through. Leaving it too late can mean the failure of the project. I see parallels in the Azure success world.

Instead of scrambling to retain customers at the eleventh hour, why not ensure their satisfaction from day one? The smart salespeople understand this. They know that prioritising customer satisfaction from the onset means not just happier customers but also an expanding recurring revenue stream over time.

Get Good Data

I wrote back in the second edition of Interesting Stuff about Azure success being a three-pronged measure of satisfaction, lifetime value, and churn management. What do you need to start on any of these? DATA!

{% include image.html url="/img/data.jpeg" description="Mr Data from Star Trek: The Next Generation" caption="No, not that kind of data. Although, who wouldn't want their own Mr Data?" %}

One of the first things you can do to get a handle on this is to start analysing the data you have. Here are some good questions to ask:

• Which customers demonstrate consistent growth or decline?
• How many workloads have our customers deployed? (Paying particular attention to ones that are only using infrastructure workloads for opportunities to modernise.)
• What is the gap between our mean and median average consumption, and how is that trending? (Basically: is our monthly recurring revenue too dependent on a small number of high-consuming customers or resellers?)

By understanding these insights, you'll notice patterns. Maybe 5 customers cut down their Azure services, costing you $5k monthly. It might seem trivial initially, but that's a potential loss of $180k over three years!

Just as small increases grow their positive impact on your recurring revenue, so too do small declines grow their negative impact.

By "shifting left" our approach to interacting with these customers we might've been able to recapture that lost revenue into other projects, services, or reduced the decline entirely.

Wrapping Up

The key to Azure success? Be proactive. "Shifting left" the approach to engaging with customers, so that it's earlier and more often in the lifecycle management process can save you hundreds of thousands of dollars in lost revenue, and even open up new opportunities for growth.

You don't have to start with anything complicated — just a bit of basic analysis can be the catalyst for wider transformation around Azure success.

You don't need to dive deep right away. Start with some basic analytics. So, get your data, pull up your preferred tool (I'm an Excel and Power BI fan), and dive in!

Now, it's time to crunch some numbers and make the ordinary extraordinary!

Azure Updates

As ever, there's always something new to know, so here's a selection of updates you might find interesting:

• General Availability: Malware Scanning in Defender for Storage
• General Availability: Azure Update Manager
• General Availability: GitHub Advanced Security for Azure DevOps
• Retirement: Azure AI Document Intelligence v2.0 API will be retired on 31 August 2026

Interesting Stuff from Others

Managing Servers

If you're working with servers in the cloud and on-prem, then this video from Dean Cefola over at the Azure Academy channel on YouTube is for you! This short video covers loads of useful tips and concepts, from Azure ARC and Windows Admin Center, through Automanage, and Image Builder.

{% include youtubeplayer.html id="GbSjkg8MZrE" %}

AI-generated Bedtime Stories

I'm constantly amazed at the potential for AI tooling to transform the way we work, and when it comes to Azure OpenAI service I love seeing ways that it can be integrated into things like the Power Platform. In this streamed session, Power Platform Advocate Daniel Laskewitz and Microsoft MVP Robin Rosengrun, dig into the Azure OpenAI service and how it can be used to enhance your Power Platform solutions. Check it out!

{% include youtubeplayer.html id="LbbEY2Juq90" %}

Until next time...

If you found this newsletter interesting, why share it with your network? I'd love to know your thoughts or suggestions for future topics in the comments below.

💭 Some thoughts on working smarter, not harder and a bit of a plug for something I made.
📝 A summary of the latest Azure updates.
📰 Interesting articles I've seen around the web.

Some Thoughts

A friend once gave me some invaluable advice: "Work smarter, not harder". Similarly, a past boss advised me, "If you repeat something more than a few times, you probably need to automate it." These insights have occupied my thoughts for years, and they've never felt more relevant than now.

That mentality, of optimising my time, working smarter, and wanting to learn new things led me to create the Cloud Target Calculator. This free tool, hosted on Azure and developed on GitHub, assists sales and marketing leaders in partners to:

• Determine the number of customers they should add.
• Estimate the number of marketing and sales-qualified leads they might need.
• Identify what proportion of existing customers should increase their spend.

Now, this isn't meant to be an 'advertorial' post. Although, the smartest people in the channel use the tool - and you look like a smart person to me. 😉

Always Learning

I understood that people either made (or ignored) these types of calculations all the time. I believed there had to be a simpler method; one that would show clearly the link between marketing and sales targets. I invested some learning time, and some coaching from ChatGPT, to figure out how to use Azure App Service for web hosting, how to use Visual Studio Code to write my code and store it on GitHub, and how to turn a business challenge into a solution an algorithm could quickly and reliably address. The benefits are twofold: I learned a bunch of useful things, and I created something that saves both my time and, potentially, yours.

What's stopping you from having a go at learning and creating?

Using the Cloud Target Calculator, you can test various scenarios and quickly discern the steps needed to meet your targets.

If you're focusing on Azure success, the calculator also highlights how much Azure consumption correlates with the number of new customers you aim to acquire vs growing your existing customers.

In conclusion...

A solid Azure practice should do two things: acquire new customers, and enhance the success of existing ones. Solely focusing on one aspect makes hitting your targets exceptionally challenging.

Grasping the nuances of performance required at each sales cycle stage, from demand generation to lifetime value management, can seem daunting.

The Cloud Target Calculator offers a streamlined approach to understanding these nuances.

What tips have you got for working smarter, not harder? Let me know in the comments! 👇🏻

Azure Updates

As ever, there's always something new to know, so here's a selection of updates you might find interesting:

• Preview: Export Cost Management data to secure storage accounts with firewall
• Azure Firewall Single-Click Upgrade and Downgrade is now in general availability
• Preview: Azure Portal experience for Azure Database Migration Service
• Generally available: Azure Site Recovery Higher Churn Support
• Generally available: Azure SQL updates for late-August 2023

Interesting Stuff from Others

Large Language Models

I'm naturally curious. I like understanding things in a little more detail as I think it helps them make sense. When I saw this post shared onto my timeline by Sarah Critchley, I jumped right in! LLMs are everywhere at the moment, and they're not going away. Check out this primer to get a deeper understanding of what's happening behind the scenes...

AI Cost Management

I was having a catch up with a couple of colleagues the other day, when the topic of copilots came up (it's happening a lot these days!). I was particularly interested in the copilot for Microsoft Cost Management. Managing costs in Azure is something I know partners and customers think about all the time, so wouldn't it be great to get more insight? Check out this overview video to learn more.

{% include youtubeplayer.html id="KuGkXGE4eWc" %}

Until next time...

If you found this newsletter interesting, why share it with your network? I'd love to know your thoughts or suggestions for future topics in the comments below.