
AI agents need governance, not just safety pauses—here's the framework
OpenAI's delayed IPO signals a broader truth: enterprises can't wait for perfect AI alignment. They need precise governance controls that work today.
Models, margins and the business decisions behind applied AI. Reporting and analysis from Fathom Tech.

OpenAI's delayed IPO signals a broader truth: enterprises can't wait for perfect AI alignment. They need precise governance controls that work today.

Dario Amodei's proposal to pace AI advancement has split the industry, but coordination alone cannot solve the fundamental challenge: human oversight cannot keep pace with machine-speed systems.

As AI inference costs fall and availability spreads, the technology will follow the path of electricity and cloud computing—driving explosive growth in demand rather than market contraction.

As AI agents move into production and begin delegating tasks across systems, enterprises face a new governance challenge: proving not just what agents did, but what they were authorized to do. The shift demands contextual authorization, cryptographic evidence and sovereign infrastructure.