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Maximilian Kenfenheuer

Manager @ BearingPoint

Maximilian Kenfenheuer

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Why Microsoft’s New Focus on Measuring Completed Work Matters for Enterprise AI

Most AI dashboards still tell you what happened in the tool, not what happened in the work. That is why Microsoft’s latest shift around Copilot Cowork measurement stands out to me. The conversation is moving beyond prompts, clicks, and activity counts toward something more useful: whether AI is actually helping people complete meaningful work and return time to the business. For organizations investing in Microsoft AI solutions, that matters. If value is measured only by interaction volume, it is easy to confuse usage with impact. But when Microsoft starts framing measurement around assisted hours, completed work, and business process outcomes, it signals a more mature model for enterprise AI adoption. In the article, I explore: • why this change in measurement is strategically important for Microsoft AI solutions • what it says about the shift from AI engagement metrics to work outcome metrics • why baseline process measurement and role-based use cases matter more than generic adoption reporting • and how organizations can think more clearly about ROI as Copilot and agents become part of operational work For me, this is one of the more important signs that Microsoft AI solutions are being positioned not just as tools people use, but as capabilities businesses need to evaluate against real work transformation. How do you think organizations should measure AI success: by usage, by time returned, or by completed business outcomes?

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Why Power BI Grounding Could Be a Bigger Microsoft AI Shift Than It First Appears

Power BI is becoming a more important part of the Microsoft AI story. One of the more interesting recent updates is that Microsoft 365 Copilot can now reason over Power BI reports and semantic models in Chat and Cowork. For me, that matters because it moves Microsoft AI solutions closer to a question many leaders actually care about: can AI work with governed business metrics, not just documents and conversations? That is a meaningful step. When AI can answer in natural language against enterprise data models people already trust, the conversation shifts from generic productivity to decision support grounded in the business’s own definitions, permissions, and reporting structure. In the article, I explore: • why Power BI grounding changes the strategic value of Microsoft AI solutions • how semantic models help create more reliable AI answers than disconnected data access • why governed metrics may become a key layer in enterprise AI adoption • and what organizations should consider as Copilot moves closer to analytics and operational decision-making For me, this is another sign that Microsoft is building AI not only around content creation, but around enterprise understanding. How important do you think governed analytics context will become in making Microsoft AI solutions truly useful at scale?

Why Work IQ Could Become a Foundational Layer in Microsoft AI Solutions (1)

June 16 is a notable date in Microsoft AI solutions, not because of another chat feature, but because Work IQ APIs are becoming generally available beyond Microsoft 365 Copilot licensing. For me, that signals something bigger: Microsoft is starting to define enterprise AI around a shared intelligence layer for agents, apps, and workflows, not only around one assistant experience. That matters because once AI can reason over chat, files, meetings, people, and actions through a governed, permission-aware layer, the conversation changes. It becomes less about isolated copilots and more about how organizations build reliable AI systems on top of their actual work graph. In the article, I explore: • why Work IQ represents a deeper architectural move in Microsoft AI solutions • how APIs, A2A support, and a compact tool model point toward more scalable agent design • why governance and cost controls are becoming part of the platform story, not an afterthought • and what organizations should consider as Microsoft expands AI from product feature to enterprise intelligence layer I think this is one of the clearest signs yet that Microsoft AI solutions are evolving into infrastructure for how work gets understood and executed. How important do you think a shared intelligence layer like Work IQ will become in enterprise AI strategy?

Posts tagged #EnterpriseAI

Microsoft Scout and the Rise of Always-On Enterprise Agents

#Microsoft365Copilot #MicrosoftAI #Copilot #AI #EnterpriseAI

Microsoft is testing a bigger idea than another chat feature. With 𝐌𝐢𝐜𝐫𝐨𝐬𝐨𝐟𝐭 𝐒𝐜𝐨𝐮𝐭, the company is introducing an always-on personal agent that can stay active in the background, understand priorities across Microsoft 365, and take action under governed identity and policy controls. What makes this interesting to me is the operating model. This is not just AI that waits for a prompt. It is AI that can help carry work forward between prompts—scheduling, surfacing risks, preparing materials, and coordinating across apps—while still staying inside enterprise security, access, and compliance boundaries. In the article, I explore why that matters for Microsoft AI solutions: • why always-on agents could become a meaningful new enterprise category • how identity, permissions, and human sign-off shape trust in autonomous action • why background coordination work is an important AI opportunity • and what organizations should think about before adopting this model at scale The next phase of enterprise AI may depend less on better conversations alone, and more on whether AI can be trusted to keep work moving responsibly in the background. How are you thinking about that trade-off: where should organizations draw the line between helpful autonomy and human control?

Why Legal Work May Be One of the Best Proving Grounds for Microsoft AI Solutions

#Microsoft365Copilot #MicrosoftAI #LegalTech #AITransformation #Copilot #EnterpriseAI

Legal work is a good test for whether enterprise AI is becoming truly useful. Not because it is easy to automate, but because it is hard to get wrong. What caught my attention is Microsoft’s push to bring legal-specific agent capabilities directly into the Microsoft 365 flow of work. When legal review, redlining, playbook-based contract analysis, and document interrogation happen inside Word and Copilot, the strategic shift is bigger than a feature launch. It suggests a broader direction for Microsoft AI solutions: domain expertise is moving closer to the place where decisions are actually made. In the article, I look at why that matters: • why embedded, profession-specific AI may create more trust than generic assistance alone • how legal workflows show the importance of citations, tracked changes, and human review • why agents connected to systems of record can reduce friction without removing accountability • and what this means for organizations thinking about scalable, governed AI adoption The next phase of enterprise AI may be less about giving everyone the same assistant, and more about delivering the right expertise in the right workflow. Where do you see the bigger opportunity: broad AI support across the business, or deeply specialized agents for high-stakes work?

Why Copilot Cowork Matters: Microsoft’s Shift from AI Assistance to AI Execution

#MicrosoftAI #Microsoft365Copilot #Copilot #AI #EnterpriseAI

30 million paid seats is an adoption milestone. But the more interesting signal is 𝑤ℎ𝑎𝑡 𝑀𝑖𝑐𝑟𝑜𝑠𝑜𝑓𝑡 𝑖𝑠 𝑡𝑟𝑦𝑖𝑛𝑔 𝑡𝑜 𝑠𝑐𝑎𝑙𝑒 𝑛𝑒𝑥𝑡. With Copilot Cowork now generally available, Microsoft is pushing beyond AI as a responsive assistant and toward AI as an execution layer for longer-running, multi-step work. That changes the enterprise conversation. This is not just about getting better answers in chat. It is about delegating work across skills, plugins, files, business apps, scheduled tasks, and even event-driven triggers—while keeping the user in control. In the article, I explore why that matters for Microsoft AI solutions: • why Cowork represents a shift from prompt-response AI to managed execution • how integration across Microsoft 365, Edge, plugins, and business systems changes the operating model • why usage-based billing and governance controls matter strategically, not just technically • and what organizations should think about now if they want agentic AI to create real business value The next phase of enterprise AI may be defined less by who can generate the best response, and more by who can orchestrate work most effectively. How are you thinking about this shift: is the bigger opportunity still AI assistance, or AI that can carry work forward across steps and systems?

Why Human Agency May Be the Most Important Microsoft AI Story Right Now

#Microsoft #Microsoft365Copilot #AI #GenerativeAI #EnterpriseAI #DigitalTransformation

66% of AI users surveyed by Microsoft say AI is helping them spend more time on higher-value work. That number matters because it shifts the enterprise AI conversation away from simple productivity gains and toward something more strategic: human agency. Microsoft’s recent framing around Microsoft 365 Copilot highlights a point I think many organizations are only starting to absorb. As AI takes on more execution, the differentiator is not just automation. It is whether people are equipped to direct, evaluate, and improve that work with better judgment. In the article, I explore why this matters for Microsoft AI solutions: • why agency may become a more useful leadership lens than efficiency alone • how Copilot changes the shape of knowledge work when more people can do higher-value tasks • why management systems and culture may matter more than individual prompting skill • and what organizations should do now to turn AI capability into durable business value The next phase of AI adoption may reward the companies that redesign work around human judgment, not just machine output. How are you thinking about this in your organization: is the bigger opportunity cost reduction, or expanding what your people can actually take ownership of?

Why Copilot Tuning Could Become a Strategic Advantage in Enterprise AI

#Microsoft365Copilot #MicrosoftAI #CopilotStudio #EnterpriseAI #AITransformation

One of the more important Microsoft AI signals this year is not another model release. It is the move toward 𝑡𝑢𝑛𝑖𝑛𝑔 AI around how a specific organization actually works. Microsoft’s announcement of Microsoft 365 Copilot Tuning and multi-agent orchestration points to a meaningful shift for enterprise AI. The question is no longer only whether AI can help with generic tasks. It is whether organizations can shape agents around their own language, processes, compliance boundaries, and domain expertise—without turning every project into a custom AI engineering effort. That matters because scalable value rarely comes from generic capability alone. It comes from making AI behave in ways that fit the business. In the article, I explore why this is strategically important for Microsoft AI solutions: • why tuning may become a practical bridge between foundation models and real enterprise workflows • how low-code customization changes the adoption equation • why multi-agent orchestration matters when work crosses functions, not just prompts • and why the next differentiator may be organizational fit, not just raw model power If enterprise AI is going to create durable value, it needs to reflect how the organization operates—not just what the model can do in general. Do you think the bigger long-term advantage will come from stronger general models, or from AI that can be tuned to the way each business actually works?