{"id":23832,"date":"2026-05-28T09:05:00","date_gmt":"2026-05-28T16:05:00","guid":{"rendered":"https:\/\/www.microsoft.com\/insidetrack\/blog\/?p=23832"},"modified":"2026-06-09T13:25:29","modified_gmt":"2026-06-09T20:25:29","slug":"visualizing-success-steering-your-ai-deployment-with-a-strategy-council","status":"publish","type":"post","link":"https:\/\/www.microsoft.com\/insidetrack\/blog\/visualizing-success-steering-your-ai-deployment-with-a-strategy-council\/","title":{"rendered":"Visualizing success: Steering your AI deployment with a strategy council"},"content":{"rendered":"\n
The pace of change when it comes to AI\u2019s impact on business today is astounding. Companies are scrambling to develop and maintain a cohesive strategy for managing this impact and getting the most out of this revolutionary technology.<\/p>\n\n\n\n
At Microsoft Digital, the company\u2019s IT organization, we\u2019re using a set of employee councils to guide how we deploy and adopt AI across our organization. We took this approach for a simple reason: We need a model that can keep pace with technological change while staying grounded in business value.<\/p>\n\n\n\n
Our baseline expectation for AI at Microsoft is practical.<\/p>\n\n\n\n
Our AI initiatives need to deliver value every quarter, and we track progress through KPIs reviewed monthly at the leadership level. That standard creates healthy pressure. It also exposes a common gap many organizations experience in the beginning stages of their AI efforts: It\u2019s easy to generate a lot of activity without producing business results.<\/p>\n\n\n\n \u201cOur strategy council is how we separate signal from noise in our AI acceleration. It identifies the top scenarios with the greatest enterprise leverage, sharpens our executive focus on what truly matters, and enforces a one-to-one alignment between the work we resource and the outcomes we’re accountable to deliver.\u201d<\/p>\nDon Campbell, principal group technical program manager, Microsoft Digital<\/cite><\/blockquote>\n\n\n\n In our council-based approach to AI, different councils focus on different needs. Together, they help us move from experimentation to repeatable, enterprise-grade outcomes. We think of these councils as building blocks that we can combine and evolve as the technology, the business, and our operating model change.<\/p>\n\n\n\n In this model, AI strategy needs its own council to help guide the overall approach and align our efforts across the enterprise. At the highest level, the strategy council is where we prioritize what matters most, decide how it maps to the outcomes we\u2019re accountable for, and determine how we\u2019ll judge progress month over month.<\/p>\n\n\n\n \u201c<\/strong>Our strategy council is how we separate signal from noise in our AI acceleration,\u201d says Don Campbell, a principal group technical program manager in Microsoft Digital. \u201cIt identifies the top scenarios with the greatest enterprise leverage, sharpens our executive focus on what truly matters, and enforces a one-to-one alignment between the work we resource and the outcomes we’re accountable to deliver.\u201d<\/strong><\/p>\n\n\n\n AI councils at Microsoft<\/strong><\/p>\n\n\n\n Check out our series on how employee councils are guiding how we use AI here at Microsoft.<\/p>\n\n\n\n Strategy keeps our AI conversation at Microsoft from getting bogged down in discussions of tools and technology and forces us to keep our focus on the main goal: What are we trying to change in the business, and how will we know if we\u2019ve succeeded?<\/p>\n\n\n\n \u201cWe need a single cohesive story to bring together what’s happening across the organization and how those efforts contribute to real impact. The goal is to stitch that story together and solve for redundancies\u2014if one part of the org has already solved a problem, another team shouldn\u2019t have to reinvent the solution.\u201d<\/p>\nMohit Chand, principal group engineering manager, Microsoft Digital<\/cite><\/blockquote>\n\n\n\n As our AI work at Microsoft accelerates, we continuously balance two truths at the same time. We want broad experimentation, because it\u2019s how teams and employees learn fast. At the same time, we want our people to focus on what matters most to our enterprise and to ensure we are identifying and reducing potential redundancy.<\/p>\n\n\n\n Maintaining this balance is the core work of our AI strategy council. It helps us identify the AI-enabled scenarios that will deliver the most value, then keeps us honest about whether we\u2019re delivering against the outcomes we\u2019ve committed to.<\/p>\n\n\n\n \u201cWe need a single cohesive story to bring together what’s happening across the organization and how those efforts contribute to real impact,\u201d says Mohit Chand, a principal group engineering manager in Microsoft Digital. \u201cThe goal is to stitch that story together and solve for redundancies\u2014if one part of the org has already solved a problem, another team shouldn\u2019t have to reinvent the solution.\u201d<\/p>\n\n\n\n We have a detailed process that relies on engaging with our subject matter experts to keep the most impactful AI portfolio visible and actionable. We use it to summarize and track our top scenarios. Our AI strategy council views this process as work that\u2019s always in process\u2014a living view that changes as products ship and priorities shift. Delivered items come off, emerging bets go on, and the continuing discussion stays anchored to our goals.<\/p>\n\n\n\n \u201cThe pace right now is incredible. There\u2019s a lot of excitement, but there\u2019s also a risk if it\u2019s not sustainable. A big part of our focus is figuring out how to take churn out of the system and make this work long\u2011term\u2014for the business and for our people.\u201d<\/p>\nMyron Wan, principal group product manager, Microsoft Digital<\/cite><\/blockquote>\n\n\n\n A tight rhythm and monthly cadence ensures that our conversations stay focused on whether the biggest bets are moving the needles we care about. That cadence helps us answer the questions leaders and customers are asking on a regular basis:<\/p>\n\n\n\n When these questions frame the conversation, the outcomes naturally align to the direction our enterprise wants to go.<\/p>\n\n\n\n To make our strategy council effective, we needed more than just a monthly meeting. We needed a way to organize work, assign accountability, and compare progress across very different teams without forcing everyone into the same mold.<\/p>\n\n\n\n We use three practices to accomplish this:<\/p>\n\n\n\n \u201cThe pace right now is incredible,\u201d says Myron Wan, a principal group product manager in Microsoft Digital. \u201cThere\u2019s a lot of excitement, but there\u2019s also a risk if it\u2019s not sustainable. A big part of our focus is figuring out how to take churn out of the system and make this work long\u2011term\u2014for the business and for our people.\u201d<\/p>\n\n\n\n When we started to scale our initial AI efforts, our first challenge was simple: Everyone is building, but not always toward the same destination. That\u2019s why we split the work into two primary focus areas that match how an IT organization operates. These areas include:<\/p>\n\n\n\n From there, we map AI initiatives into those focus areas so we can see what\u2019s happening across the landscape and spot gaps, overlaps, and opportunities to reuse what already exists.<\/p>\n\n\n\n \u201cWe operate a council which helps set direction, but product management oversees execution of the solutions. Without product management\u2019s ownership, our council would degrade into just a low-level approval step, which quickly makes us a roadblock instead of an enabler.\u201d<\/p>\nBill O\u2019Brien, principal group product manager, Microsoft Digital<\/cite><\/blockquote>\n\n\n\n This step sounds basic, but it changes the conversation. It moves us away from a list of disconnected projects and toward a portfolio view, where we can figure out which scenarios matter most, where we have duplication, and where we need to invest more.<\/p>\n\n\n\n While our AI strategy council sets direction, execution lies strictly with our product owners. A strategy council can\u2019t run delivery. If it tries, it slows everything down. We avoid that trap by separating direction from doing.<\/p>\n\n\n\n \u201cWe operate a council which helps set direction, but product management oversees execution of the solutions,\u201d says Bill O\u2019Brien, a principal group product manager in Microsoft Digital. \u201cWithout product management\u2019s ownership, our council would degrade into just an approval step, which quickly makes us a roadblock instead of an enabler.\u201d <\/p>\n\n\n\n This clarity on roles and responsibilities helps teams work fast and ensures the council remains strategic. Product owners can prioritize week by week, learning from usage, adjusting product features, and shipping value. The council can stay focused on the portfolio and which bets rise to the top, what tradeoffs to make, and how we communicate progress and business outcomes to leadership.<\/p>\n\n\n\n \u201cThe first part of our strategy was all about getting people to a point where they could identify what they were trying to accomplish and report on how they\u2019re getting there. We created a value measurement framework in partnership across multiple key players to give teams an idea of what\u2019s valuable to the organization.\u201d<\/p>\nKeith Bunge, principal software engineer, Microsoft<\/cite><\/blockquote>\n\n\n\n Once we can see the portfolio and have identified clear ownership, we still need one more thing: A shared language for determining value. Early in our journey, we were tempted to declare success simply based on activity\u2014how many pilots we launched, how many tools we built, or how many demos we could show.<\/p>\n\n\n\n That activity is critical for innovation, but it doesn\u2019t help us understand and drive business value. We needed teams to define the value they expect to deliver, explain why, and show how they’ll measure it.<\/p>\n\n\n\n \u201cThe first part of our strategy was all about getting people to a point where they could identify what they were trying to accomplish and report on how they\u2019re getting there,\u201d says Keith Bunge, a principal software engineer at Microsoft. \u201cWe created a value measurement framework in partnership across multiple key players to give teams an idea of what\u2019s valuable to the organization.\u201d<\/p>\n\n\n\n That framework helps in two ways:<\/p>\n\n\n\n As our approach matures, we\u2019re also pushing past raw savings metrics to the harder question: What did we do with the time or money we saved, and how did this create increased agency or capabilities?<\/strong><\/p>\n\n\n\n Here\u2019s how that looks when we apply this approach to a real-world scenario.<\/p>\n\n\n\n Say one of our teams is proposing an AI solution to automate energy management in buildings. On day one, the idea sounds great: use signals from internal temperature and movement sensors to automatically adjust HVAC usage across large buildings. But the role of the strategy council isn\u2019t just to approve great ideas. We ask for a clear value claim and a measurement plan.<\/p>\n\n\n\n Bunge provides a solid value claim for the example above.<\/p>\n\n\n\n \u201cI\u2019m going to come up with an automation that allows me to automatically turn off air conditioning in a building based on signals that we have from our internal sensors,\u201d he says. \u201cI think I\u2019m going to be able to save $100,000 a quarter with this project because of my usage projections overlaid on the HVAC costs over the past five years.\u201d<\/p>\n\n\n\n That kind of statement is useful, because it\u2019s specific. It also forces the next question: How do you prove it? We\u2019re asking teams to explain what data they\u2019ll use as a baseline, what counts as savings, and how they\u2019ll report progress over time.<\/p>\n\n\n\n We\u2019re also raising the bar as the program matures.<\/p>\n\n\n\n Early on, teams may be able to prove that they saved time or reduced effort. As we get more rigorous, we\u2019re pushing the \u201cso what\u201d conversation: What happens with the time saved, and what changes in the business as a result? It\u2019s all part of moving from value measures to business outcomes, including what gets reinvested and where impact actually accrues.<\/p>\n\n\n\n Our AI strategy council is not the final measure or a standalone solution. We use it as the front door to a broader ecosystem that helps us move AI from ideas to enterprise outcomes.<\/p>\n\n\n\n \u201cBusiness strategy needs to lead the AI strategy. Business strategy defines the \u2018what and why.\u2019 AI defines the \u2018how\u2019 to get the business strategy implemented with real value. We need to use AI to help us achieve the business strategy, not the other way around.\u201d<\/p>\nQingsu Wu, principal group product manager, Microsoft Digital<\/cite><\/blockquote>\n\n\n\n Here\u2019s how it fits together in practice. We use the strategy council to set our direction, and we keep a short list of top scenarios visible. Then we rely on complementary councils and capability groups to make those scenarios real: teams are building skills and patterns through enablement, strengthening foundations through data readiness, and applying Responsible AI practices so solutions scale safely.<\/p>\n\n\n\n We use process improvement and change management to drive adoption, because a strong model doesn\u2019t matter if people don\u2019t change how they work. And we use metrics and value tracking to keep the entire system accountable.<\/p>\n\n\n\n We\u2019re also keeping a clear principle at the center: Business strategy leads, AI follows.<\/p>\n\n\n\n \u201cBusiness strategy needs to lead the AI strategy,\u201d says Qingsu Wu, a principal group product manager in Microsoft Digital. \u201cBusiness strategy defines the \u201cwhat and why.\u201d AI defines the \u2018how\u201d to get the business strategy implemented with real value. We need to use AI to help us achieve the business strategy, not the other way around.\u201d<\/strong><\/p>\n\n\n\n That distinction matters as AI capabilities keep expanding and as teams continue to move faster.<\/p>\n\n\n\n As this work matures, one thing is clear: Strategy isn\u2019t something we finish and move on from. It\u2019s something we\u2019re actively maintaining as AI adoption accelerates.<\/p>\n\n\n\n What we\u2019ll do next is consistent with that mindset.<\/p>\n\n\n\n We plan to keep scaling what works while tightening and improving the system around it. We\u2019re strengthening alignment across teams, pushing for more consistent measurement of impact, and sharpening how we choose the right approach for the right problem. We\u2019re also treating strategy as a living motion, not an annual document, because business and technology are constantly changing.<\/p>\n\n\n\n We know that what got us here isn\u2019t going to get us where we need to go next. We\u2019re excited about the continued evolution of AI strategy here at Microsoft Digital as we focus on scale, alignment to real business problems, and making sure the pace is sustainable for our business.<\/p>\n\n\n\n Key takeaways<\/p>\n<\/div>\n\n\n\n Leaders who are scaling AI across IT can apply these lessons from our experience to stay focused, move faster, and deliver measurable business impact.<\/p>\n\n\n\n Try it out<\/p>\n<\/div>\n\n\n\n New to Microsoft 365 Copilot? Check it out!<\/a><\/p>\n<\/div>\n\n\n\n Related links<\/p>\n<\/div>\n\n\n\n The pace of change when it comes to AI\u2019s impact on business today is astounding. Companies are scrambling to develop and maintain a cohesive strategy for managing this impact and getting the most out of this revolutionary technology. At Microsoft Digital, the company\u2019s IT organization, we\u2019re using a set of employee councils to guide how […]<\/p>\n","protected":false},"author":92,"featured_media":23834,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":true,"_jetpack_newsletter_tier_id":0,"_jetpack_memberships_contains_paywalled_content":false,"_hide_featured_on_single":false,"_show_featured_caption_on_single":true,"_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[912],"tags":[199,868,850,237,852,263,827,849,870],"coauthors":[550],"class_list":["post-23832","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-ai-councils","tag-ai","tag-ai-deployment-and-adoption","tag-end-user-services-and-support","tag-governance","tag-it-and-business-operations","tag-microsoft-365","tag-microsoft-365-copilot","tag-network-and-infrastructure","tag-works-councils","m-blog-post"],"yoast_head":"\n
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AI strategy in action: Focus, alignment, and a monthly cadence<\/h2>\n\n\n\n
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Structuring strategy and execution<\/h2>\n\n\n\n
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Working into focus areas<\/h3>\n\n\n\n
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Keeping execution with product owners<\/strong><\/h3>\n\n\n\n
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Using a common value framework<\/strong><\/h3>\n\n\n\n
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Combining strategy and execution: A practical example<\/h3>\n\n\n\n
Connecting AI strategy to the rest of our councils<\/strong><\/h2>\n\n\n\n
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Moving forward<\/h2>\n\n\n\n
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