Blog

Maximilian Kenfenheuer

Manager · Microsoft 365 & AI Transformation @ BearingPoint

Maximilian Kenfenheuer

Featured

Measuring Completed Work: Baselines, Assisted Hours and Business Outcomes

A team can generate thousands of prompts without improving a single core process. Another uses AI rarely but saves hours in contract review. Microsoft increasingly measures Copilot value by completed work and assisted hours instead of activity. Its internal guidance recommends baselines for painful processes before the rollout. In this article, I describe a three-layer measurement model of adoption signals, time and effort indicators and business outcomes, and explain why role-based deployment makes value measurable.

Continue reading

Posts tagged #AITransformation

Measuring Completed Work: Baselines, Assisted Hours and Business Outcomes

#Microsoft365Copilot #MicrosoftAI #Copilot #AITransformation #FutureOfWork

A team can generate thousands of prompts without improving a single core process. Another uses AI rarely but saves hours in contract review. Microsoft increasingly measures Copilot value by completed work and assisted hours instead of activity. Its internal guidance recommends baselines for painful processes before the rollout. In this article, I describe a three-layer measurement model of adoption signals, time and effort indicators and business outcomes, and explain why role-based deployment makes value measurable.

Frontier Tuning: Reinforcement Learning Inside the Compliance Boundary

#Microsoft365Copilot #MicrosoftAI #CopilotStudio #EnterpriseAI #AITransformation

Microsoft introduced Frontier Tuning at Build. It applies reinforcement learning inside the organization's compliance boundary, using its own data, conventions and workflows. The results are tuned models, skills, orchestration logic and a runtime harness that inherit existing access policies. Frontier Tuning comes to Copilot Studio and Microsoft Foundry. Pearson, EY, Bristol Myers Squibb and McKinsey are among the early users. In this article, I explain how tuning differs from prompting and retrieval and which questions organizations should answer before tuning agents.

Work IQ as Context Infrastructure for Copilot and Agents

#MicrosoftAI #Microsoft365Copilot #CopilotStudio #EnterpriseAI #AITransformation

For many organizations, access to a capable model is no longer the problem. The problem is whether the model has enough business context to be reliably useful. Work IQ turns signals from email, meetings, files, chats and business systems into context for Copilot and agents. It works permission-aware and user-scoped, with central logging and policy enforcement. In this article, I explain why this infrastructure layer may matter more than the next interface feature and what organizations should prepare in information architecture and governance.

The Legal Agent in Word: Citations, Tracked Changes and Playbooks

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

In most business processes, a rough first draft is acceptable. In legal work it is not: every clause, citation and redline carries risk. Microsoft's Legal Agent in Word summarizes, reviews and redlines legal documents. It cites passages with numbered references, proposes edits as tracked changes and turns internal playbooks into reusable review skills. In this article, I explain why legal work is a demanding test case for enterprise AI and which lessons transfer to finance, compliance or procurement.

Copilot Tuning and Multi-Agent Orchestration: Adapting AI to the Organization

#Microsoft365Copilot #MicrosoftAI #CopilotStudio #EnterpriseAI #AITransformation

A law firm has its own drafting style, a consulting company its own industry playbooks. General-purpose models do not know either. With Microsoft 365 Copilot Tuning, organizations tune models with their own data, workflows and processes in Copilot Studio, low-code and without a data science team. Multi-agent orchestration lets HR, IT and marketing agents share work, for example during onboarding. In this article, I explain why organizational fit may become a stronger advantage than access to the most powerful general model.