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Maximilian Kenfenheuer

Manager @ BearingPoint

Maximilian Kenfenheuer

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Why Connected Apps Inside Microsoft 365 Copilot Matter More Than Another AI Feature

One of the biggest AI adoption problems is still surprisingly simple: the answer shows up in one place, but the work still has to happen somewhere else. That is why Microsoft’s move to bring business apps directly into Microsoft 365 Copilot deserves more attention. When agents can surface experiences from tools like Dynamics 365, Adobe Express, Figma, Box, or monday.com inside the Copilot flow, the value is not just convenience. It is a shift in operating model. AI becomes more useful when it can stay connected to the systems where teams actually create, update, approve, and execute work. In the article, I explore why this matters for Microsoft AI solutions: • why reducing context switching is becoming a strategic design goal • how in-chat app experiences can narrow the gap between insight and execution • why connectors, agents, and governance now matter together • and what organizations should think about as Copilot becomes a more connected work surface The next phase of enterprise AI may depend less on generating another good answer, and more on whether that answer can move work forward across the tools the business already depends on. How important do you think connected app experiences will be in turning AI from assistance into real execution?

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Why Microsoft’s Copilot Redesign Matters More Than It Seems

The interface layer of enterprise AI is becoming a strategy decision. Microsoft’s redesign of the Microsoft 365 Copilot app may look, at first glance, like a product UX update. I think it is more significant than that. When Copilot becomes cleaner, faster, and more embedded across Microsoft 365, the real shift is not visual. It is operational. AI moves closer to the flow of work, which changes adoption, trust, and ultimately business value. In the article, I explore why this matters for Microsoft AI solutions: • why user experience is becoming part of enterprise AI architecture • how a more unified Copilot surface can reduce friction between insight and action • why design consistency matters when agents, apps, and workflows start to converge • and what organizations should think about as AI becomes a more persistent layer of daily work The next stage of AI adoption may depend not only on model capability, but on how naturally that capability fits into the way people already work. Do you think enterprise AI adoption will be shaped more by what the model can do, or by how well the experience fits into everyday work?

Why Source Control Will Matter More in Microsoft 365 Copilot Than Many Teams Realize

Trust in enterprise AI is not only about what the model can do. It is also about what the organization can control. That is why Microsoft’s work on domain exclusion for Microsoft 365 Copilot caught my attention. Even with the recent rollback of the feature as originally announced, the direction is strategically important: giving admins more control over which external web domains can influence Copilot responses. For Microsoft AI solutions, that matters because grounded AI is only useful at scale if it is also governable at scale. In the article, I look at why this issue deserves more attention: • why web grounding controls are becoming part of the enterprise trust model • how domain-level policy can shape quality, compliance, and risk • why this is bigger than one feature release or rollback • and what it says about the next phase of governed AI adoption in Microsoft 365 The future of enterprise AI will not be defined by capability alone. It will also be defined by how precisely organizations can shape the information boundaries around that capability. How important do you think source-level control will become as companies scale AI across everyday work?

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Why Connected Apps Inside Microsoft 365 Copilot Matter More Than Another AI Feature

#Microsoft365 #Copilot #MicrosoftAI #AI #EnterpriseAI

One of the biggest AI adoption problems is still surprisingly simple: the answer shows up in one place, but the work still has to happen somewhere else. That is why Microsoft’s move to bring business apps directly into Microsoft 365 Copilot deserves more attention. When agents can surface experiences from tools like Dynamics 365, Adobe Express, Figma, Box, or monday.com inside the Copilot flow, the value is not just convenience. It is a shift in operating model. AI becomes more useful when it can stay connected to the systems where teams actually create, update, approve, and execute work. In the article, I explore why this matters for Microsoft AI solutions: • why reducing context switching is becoming a strategic design goal • how in-chat app experiences can narrow the gap between insight and execution • why connectors, agents, and governance now matter together • and what organizations should think about as Copilot becomes a more connected work surface The next phase of enterprise AI may depend less on generating another good answer, and more on whether that answer can move work forward across the tools the business already depends on. How important do you think connected app experiences will be in turning AI from assistance into real execution?