Introduction
AI identity management: Okta-commissioned research summarizes how rapid AI agent adoption outpaces security, affecting access, privacy and governance practices.
Context
Okta asked AlphaSights to survey 260 executives (CTOs, CISOs, CIOs and peers) across nine countries to map AI agent usage, benefits and concerns.
Why AI identity management matters
Quick definition: AI identity management covers provisioning, permissioning and governance for non-human identities used by AI agents to access systems and data.
Key findings
The study highlights several practical insights:
- 91% of organizations use AI agents, averaging about five use cases per organization
- 84% report productivity gains; 60% cite cost savings
- Data privacy (68%) and security (60%) are top concerns
- 85% view IAM as vital for AI adoption
- Only 10% have a well-developed roadmap for managing non-human identities
The challenge
AI agents need broad, sometimes privileged access, short-lived credentials and nonstandard authentication, increasing exposure and complicating audits.
Solution / Practical approach
Recommended actions from the report include:
- Make IAM for NHIs a priority with rapid provisioning and automatic revocation
- Build dedicated visibility and logging for agents
- Create centralized governance with CISO, CIO, legal and data leaders
- Apply secure-by-design principles for APIs, authentication and RAG workflows
"In my experience, successful AI adoption and integration require a clear strategy aligned with business outcomes … Avoid generic ‘AI for AI’s sake’ initiatives."
Vice President, Technology, Canada
Conclusion
Okta's commissioned research shows broad AI agent adoption but a governance gap; strengthening identity controls, visibility and cross-functional governance is essential to reap benefits safely.
FAQ
What is AI identity management?
It is the process of provisioning, permissioning and governing non-human identities used by AI agents to access systems and data.
Why is IAM vital for AI agents?
Because agents often require temporary privileged access; IAM prevents prolonged exposure through granular, time-bound permissions.
What top risks did the Okta study find?
The main concerns are data privacy and security, driven by limited visibility and immature governance for non-human identities.
What practical steps does the report recommend?
Prioritize IAM for NHIs, add dedicated logging, adopt centralized governance and follow secure-by-design for APIs and RAG.