Microsoft just released their Agent Factory framework, and it's forcing a rethink of how we approach AI governance. These aren't the AI tools we've been building policies around—they're autonomous agents that plan workflows, execute across organizational systems, and collaborate in ways that break our existing oversight models.
Take Fujitsu's sales agents. They're building complete proposals by calling APIs, assembling documents, and cutting production time by 67%. When that agent submits a proposal, who actually submitted it? The traditional answer would be the human operator, but there's no human in this loop. The agent is conducting business directly, which means our contract approval workflows and signature authority frameworks need to be rebuilt from scratch.
Microsoft's multi-agent orchestration raises more complex questions. JM Family's BAQA Genie coordinates specialized agents across requirements, coding, documentation, and quality assurance—turning weeks-long development cycles into days. That's powerful, but it creates governance gaps I'm not sure we know how to fill. When agent teams make decisions at machine speed across multiple business functions, how do you maintain the audit trails and accountability structures that legal frameworks require?
The ReAct pattern complicates this further. These agents reason and act in real time, adapting to situations where "the best path forward isn't clear." That's exactly when human judgment becomes valuable, yet these agents are designed to operate autonomously in those ambiguous moments. By the time an IT support agent escalates to humans, it's already made decisions about data access, system configurations, and business operations.
Azure AI Foundry removes the technical barriers that might have slowed adoption. We're no longer talking about experimental deployments—Microsoft has created a production-ready platform that makes agentic AI deployment straightforward. Legal teams need to recognize that we're moving from governing individual AI tools to orchestrating oversight across AI teams that reason, plan, and act across entire organizations.
The governance frameworks we've built assume AI tools that respond to human direction. These agents collaborate, make autonomous decisions, and execute business processes without human intervention. We need new approaches to accountability, new audit processes, and new ways to ensure these agent teams operate within legal and ethical boundaries while still capturing their productivity benefits.
Yina Arenas
