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Maximilian Kenfenheuer

Manager @ BearingPoint

Maximilian Kenfenheuer

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Why Model Choice in Microsoft 365 Copilot Matters More Than It First Appears

Model choice inside Microsoft 365 Copilot is becoming a more important enterprise signal than it may first appear. Microsoft’s recent addition of Anthropic models in Copilot points to something bigger for Microsoft AI solutions: the platform is evolving beyond a one-model experience toward a governed model layer, where different reasoning strengths can be brought into the flow of work. In the article, I explore why that matters: • why model optionality changes the enterprise AI conversation from access to fit • how different models can better support different kinds of work, from drafting to deeper reasoning • why governance, evaluation, and admin oversight become more important as model choice expands • and what organizations should consider as they move toward a more plural AI operating model inside Microsoft 365 The next phase of enterprise AI may depend not only on having AI available in the tools people use, but on whether the right model can be applied to the right task under the right controls. How important do you think model choice will become as organizations mature their Microsoft AI strategy?

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Why Domain Exclusion Matters More Than It Seems in Microsoft 365 Copilot

Up to 1,000 domains can now be excluded from web grounding in Microsoft 365 Copilot. I think that is more important than it may first appear. For Microsoft AI solutions, this is not just a settings update. It is a signal that 𝑔𝑟𝑜𝑢𝑛𝑑𝑖𝑛𝑔 𝑐𝑜𝑛𝑡𝑟𝑜𝑙 is becoming part of enterprise AI architecture. As Copilot becomes more capable, organizations will need sharper ways to shape what external sources it can and cannot rely on. In the article, I explore why this matters: • why domain exclusion changes the governance conversation from broad trust to source-level control • how web grounding policies affect accuracy, risk, and organizational confidence • why admin tooling now matters just as much as model capability in enterprise AI adoption • and what organizations should consider as they operationalize Copilot more seriously The next phase of enterprise AI may depend not only on what AI can access, but on how deliberately organizations can define the boundaries around that access. How important do you think source-level controls like domain exclusion will become as enterprises scale AI use?

Why Copilot Tasks Matters: The Shift from AI Answers to AI Execution

Copilot Tasks points to a shift that is easy to underestimate. What matters is not just that AI can generate a good response. It is that Microsoft is pushing toward AI that can 𝑐𝑎𝑟𝑟𝑦 𝑜𝑢𝑡 𝑤𝑜𝑟𝑘 in the background across apps, websites, schedules, and recurring routines, while still keeping the user in control. That changes the conversation for Microsoft AI solutions. In the article, I explore why this is strategically important: • why task execution may become a more meaningful measure of AI value than chat quality alone • how recurring, scheduled, and real-world actions change expectations for everyday productivity • why consent, oversight, and operational controls become even more important as AI moves from assistance to action • and what organizations should consider as they prepare for a more execution-oriented AI model The next phase of enterprise AI may depend less on whether AI can respond intelligently, and more on whether it can complete useful work reliably, safely, and at the right moment. How important do you think action-taking AI like Copilot Tasks will become in shaping user expectations for enterprise AI?

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Why Model Choice in Microsoft 365 Copilot Matters More Than It First Appears

#Microsoft365Copilot #MicrosoftAI #AI #Copilot #EnterpriseAI

Model choice inside Microsoft 365 Copilot is becoming a more important enterprise signal than it may first appear. Microsoft’s recent addition of Anthropic models in Copilot points to something bigger for Microsoft AI solutions: the platform is evolving beyond a one-model experience toward a governed model layer, where different reasoning strengths can be brought into the flow of work. In the article, I explore why that matters: • why model optionality changes the enterprise AI conversation from access to fit • how different models can better support different kinds of work, from drafting to deeper reasoning • why governance, evaluation, and admin oversight become more important as model choice expands • and what organizations should consider as they move toward a more plural AI operating model inside Microsoft 365 The next phase of enterprise AI may depend not only on having AI available in the tools people use, but on whether the right model can be applied to the right task under the right controls. How important do you think model choice will become as organizations mature their Microsoft AI strategy?