Identity for AI Agents: The Missing Layer in Enterprise Access Control
Why AI agents require first-class identity, scoped authorization, provenance, audit trails, and lifecycle management as they gain enterprise access.
Read researchResearch index
Evidence-led analysis of enterprise adoption, governance, AI identity, agentic systems, infrastructure, security, and the changing state of artificial intelligence.
Adoption and operating capability.
Control, evidence and accountability.
Authority, access and audit.
Signals across global markets.
Method
We prioritize primary data, standards, technical documentation, regulatory materials, and reproducible evidence. Observed facts are separated from assumptions, scenarios, and forward-looking judgment.
How to use our research
Research is structured to help leaders move from technical developments to implications for architecture, governance, security, investment, and operating models.
Research utility
Understand material changes in AI capabilities, adoption patterns, policy, infrastructure, and agent systems.
Connect those changes to institutional exposure, readiness, architecture, controls, and strategic options.
Translate research into sharper questions for boards, technology leaders, governance teams, and operating owners.