Akeyless | Survey report
The 2026 State of AI Agent Identity Security Report
AI agents are moving fast. Identity security is falling behind.
AI agents now access sensitive data, connect to critical systems, and take actions across the enterprise. However, most identity controls were not designed for autonomous identities operating at this speed or scale.
Based on research with 400 security and IT leaders, the report shows where AI agent identity controls are breaking down, what that exposure is costing organizations, and what security teams need to change.
Agent Identity Risk by the Numbers
The 2026 State of AI Agent Identity Security report examines AI agent and machine identity trends and threats, based on a global survey of 400 security and IT leaders across industries.
94%
of organizations use AI agents
84%
admit AI agents can access sensitive data
67%
say AI agents have already accessed data they shouldn’t
$1M+
average spent on AI agent identity and security issues in the past year
state that AI agents can access sensitive data
The AI agent identity gap is already here
AI agents are widely deployed. The controls around them are struggling to keep up.
AI agents have moved from experiments into everyday enterprise systems. In fact, 94% of organizations report some level of AI agent use, and 84% say their agents can access sensitive data.
Yet many organizations still rely on persistent credentials, fragmented identity systems, and controls built for humans and traditional workloads.
The question is whether security teams can see who those agents are, control what they can access, and govern what they do.
What the 2026 data reveals
You cannot secure agents you cannot see
Only 44% know where all the credentials or secrets used by AI agents are stored.
Credentials can sit across cloud services, configuration files, application code, workflows, and CI/CD tools. Without a complete view, security teams may not know which agents have access or whether that access is still needed.
know where all the credentials or secrets used by AI agents are stored
- Cloud-native identity services59%
- IAM platform54%
- Secrets management system (for credentials/ keys/certificates)54%
- Privileged Access Management (PAM) solution52%
- Custom or home-grown identity mechanisms37%
- Manual processes or scripts32%
Existing identity controls are under strain
AI agents still rely heavily on persistent access. That matters because 83% say a single compromised credential could affect multiple major systems or a broad range of systems.
At the same time, organizations manage agent identity across cloud services, IAM, secrets management, PAM, custom tools, and manual processes. Only 46% are fully confident their IAM systems can securely manage AI agents and machine identities.
As access spreads across overlapping systems, maintaining consistent visibility and policy becomes harder.
AI agents move faster than security teams can respond
AI agents can act in milliseconds. Organizations estimate it would take 14 hours on average to detect a compromised AI agent.
Containing and remediating the incident would take an additional six days. That gap changes the security problem: controls need to govern what happens when an agent acts, not only whether it receives access.
- We believe our controls would prevent this from occurring in the first place7%
- Immediately13%
- Within minutes19%
- Within hours38%
- Within a day16%
- Within a week6%
- Within two weeks2%
- More than two weeks0%
- We would likely not detect it0%
$1,068,956
Average spent on AI agent identity and security issues over the last 12 months
The cost is already measurable
Identity issues are already creating financial and operational impact
Organizations with deployed AI agents report spending an average of $1,068,956 over the past 12 months addressing identity or security issues.
Security concerns can also slow adoption. 73% say AI agent adoption could be faster if it was not for potential security risks.
- Gain visibility into agent identities and access.
- Replace persistent credentials with dynamic, tightly scoped access.
- Enforce policy when agents act.
- Establish clear ownership and accountability.
Inside the report
Original research from 400 security and IT leaders examines:
AI agent adoption and access
See where agents are deployed, which systems they reach, and what credentials they use.
Identity control gaps
Understand where credentials are stored, how teams bypass IAM, and where existing controls are under strain.
Active security exposure
Explore evidence of excessive access, suspected credential exposure, and slow incident response.
Four actions security leaders can take now
Get a practical framework for visibility, dynamic access, runtime enforcement, and accountability.
Who this report is for
CISOs and security leaders responsible for AI risk, incident readiness, and enterprise access.
IAM, PAM, and secrets management teams managing machine identities, credentials, and privileged access.
AI platform, DevOps, and cloud teams building agents that connect to production systems.
Risk, governance, and compliance teams that need clear accountability, auditability, and control.
About the research
Akeyless commissioned MRA Research to survey 400 IT decision-makers and security practitioners, including DevOps professionals, in January and February 2026.
Respondents worked at organizations with more than 500 employees across the United States and United Kingdom. The study included both public and private sectors, with a focus on finance and retail.
Participants were recruited through a multi-phase qualification process designed to support relevance and data integrity. Unless stated otherwise, the findings represent the full sample.
Download the 2026 report
See where AI agent identity risk is already emerging
Benchmark your current controls against 400 security and IT leaders. Then use the report’s four-part framework to strengthen identity security as AI agent adoption grows.