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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 #Microsoft

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 Microsoft Scout Could Shift Enterprise AI From Prompted Help to Persistent Support

#Microsoft365 #Copilot #AI #EnterpriseAI #Microsoft

An always-on agent is a different proposition from an on-demand assistant. What caught my attention in Microsoft’s latest Copilot direction is the move toward a personal agent that stays connected to the user’s flow of work across Microsoft 365, rather than waiting for the next prompt. That is strategically important because the value of AI often disappears in the gaps between moments of interaction. In the article, I explore why Microsoft Scout points to a new design pattern in enterprise AI: less episodic chat, more persistent support; less isolated output, more continuity across tasks, context, and decisions. If this model matures, the advantage may not come only from better responses. It may come from reducing the amount of work people have to remember, re-open, and manually restart. Do you think the bigger opportunity is smarter assistants, or AI that can stay productively present between interactions?

Why Copilot Cowork Signals a New Execution Layer for Enterprise AI

#Microsoft365 #Copilot #AI #EnterpriseAI #Microsoft

One of Microsoft’s more important AI moves may be shifting from 𝑟𝑒𝑠𝑝𝑜𝑛𝑠𝑒𝑠 to 𝑑𝑒𝑙𝑒𝑔𝑎𝑡𝑖𝑜𝑛. Copilot Cowork is interesting because it is not positioned as another chat experience. It is designed for long-running, multi-step work: turning an outcome into a plan, grounding that plan in Microsoft 365 context, progressing in the background, and pausing at checkpoints for review and approval. That operating model matters. Microsoft describes Cowork as creating plans, reasoning across tools and files, using built-in skills, and carrying work forward with visible progress. Admin guidance also makes the enterprise posture clear: usage-based billing, plugin controls, model controls, audit visibility, browser governance, and approval flows for shared actions. To me, this points to a bigger shift in enterprise AI. The strategic question is becoming less “can the assistant answer well?” and more “can the system reliably take bounded action across real workflows without losing trust, control, or governance?” In the article, I unpack why Cowork could matter as an execution layer inside Microsoft 365—and why delegated work, not just generated output, may define the next phase of AI adoption. How far do you think enterprises are ready to go from AI assistance to AI delegation?

Why In-Chat App Execution Could Be Microsoft’s Next Enterprise AI Advantage

#Microsoft365Copilot #AI #EnterpriseAI #Microsoft #Copilot #DigitalTransformation

Every enterprise AI demo looks smooth until the user has to leave the conversation to actually do the work. That is why Microsoft’s push to bring business apps directly into Microsoft 365 Copilot is worth paying attention to. The April update is not just about adding more agents. It is about collapsing the gap between 𝑖𝑛𝑠𝑖𝑔ℎ𝑡 and 𝑒𝑥𝑒𝑐𝑢𝑡𝑖𝑜𝑛: surfacing tools like Adobe Express, Figma, Miro, monday.com, Optimizely, Box, Wix, and Dynamics-connected workflows inside Copilot so users can act without constant tab switching and context rebuilding. Strategically, this matters because enterprise AI adoption will not be won by chat quality alone. It will be won by whether AI can sit in the middle of real work and coordinate action across the software stack people already depend on. In the article, I unpack why this could become one of Microsoft’s strongest advantages: not just owning productivity apps, but turning Copilot into the operating surface where cross-app work actually happens. If that model sticks, the most valuable AI product may not be the one with the smartest answers. It may be the one that removes the most workflow friction. What do you think: will enterprise AI value concentrate in the model, or in the layer that connects work across applications?