At A Glance
- Insufficient access controls, specifically non-human identity management, is the top security concern cited by CISOs and CTOs deploying AI.
- 85% of organizations are now actively evaluating or exploring new approaches to non-human identity, a combined figure that signals this has moved from awareness to active buying decision.
- CTOs are exploring new approaches at a notably higher rate than CISOs, suggesting this is increasingly viewed as an engineering problem as much as a governance one.
For the past few years, non-human identity has been the kind of problem security teams acknowledged in a slide but rarely funded. That’s changing. New survey data from 200 CISOs and CTOs shows this has quietly become the top named security concern in AI deployments, and more importantly, organizations are no longer just worried about it. They’re actively shopping for a fix.
NetFoundry commissioned Global Surveyz Research to survey 200 senior security and technology leaders, CISOs, CTOs, CAOs, and CIOs, at companies with 1,000 or more employees, across finance, healthcare, tech, retail, and industrial sectors, on how they’re navigating the security risks of AI deployment.
What Is Non-Human Identity?
Non-human identity refers to a distinct, verifiable identity assigned to an AI agent, API, service, or other machine workload, rather than that workload inheriting a shared credential or the identity of the human who deployed it. Human identity and access management matured over the last decade around a simple assumption: every connection has a person behind it who can be authenticated. AI breaks that assumption. Agents, models, and the services that support them don’t have identities in the way humans do, which means most organizations can’t reliably govern, monitor, or audit what a given agent is doing, or tell one agent’s actions apart from another’s.
Why Are Security Leaders Naming This Their Top AI Security Concern?
When asked about their primary security concerns related to AI deployments, insufficient access controls, meaning the non-human identity gap described above, topped the list. That’s a notable shift. For most of the last decade, the headline security concerns in enterprise IT have centered on human-facing risk: phishing, credential theft, endpoint compromise. Non-human identity outranking those concerns signals that security leaders see this as the more structurally unresolved problem, not just a newer one.
It tracks with what’s sitting underneath it: only 8% of organizations describe their current identity systems as very sufficient for securing or monitoring non-human workloads. The tooling most organizations have simply wasn’t built for this.
Why Are Organizations Actively Evaluating New Non-Human Identity Approaches Now?
This is where the story moves from concern to action. A combined 85% of organizations are now actively evaluating or exploring new approaches to secure non-human identity. That’s not a “someday” number. It’s a signal that this has crossed the threshold from a known gap into an active budget line and vendor evaluation process at a majority of organizations surveyed.
Interestingly, CTOs are exploring new approaches at a meaningfully higher rate than CISOs. That’s worth sitting with for a moment: the people building and maintaining AI infrastructure are moving faster on this than the people traditionally responsible for security governance, which suggests non-human identity is increasingly being treated as an engineering problem to solve at the architecture level, not just a policy problem to manage through oversight.
What Should CISOs and CTOs Look for in a Non-Human Identity Solution?
Given how many organizations are actively in this evaluation process, it’s worth being specific about what actually closes the gap versus what just monitors it. A few things worth prioritizing:
- Identity, not just visibility. Monitoring tools can tell you an agent did something. They can’t tell you whether that agent should have been able to do it in the first place. Look for solutions that assign each machine workload its own distinct, verifiable identity, not just better logging on top of shared credentials.
- No reliance on IP-based access control. NAT, DHCP, and ephemeral IPs make consistent tracking by network address nearly impossible at AI scale. Identity needs to travel with the workload, not the network location.
- Reduced dependency on standing secrets. Static credentials that persist indefinitely and carry excessive permissions are a primary source of the blind spots security teams are trying to close. Favor architectures that minimize long-lived secrets rather than just rotating them faster.
That’s not an exhaustive checklist, but it’s the difference between a solution that reduces this risk and one that just gives you a better dashboard for watching it happen.
How to Choose a Non-Human Identity Solution
The organizations moving fastest on non-human identity right now aren’t waiting for a perfect industry standard to emerge. They’re evaluating architectures that solve the identity problem at its root: giving every agent, API, and workload its own governable identity rather than layering more monitoring on top of shared secrets. That’s the approach behind NetFoundry’s Identity-First Reachability™, which assigns verifiable, non-human identity to every AI agent, MCP server, and machine workload, with no open inbound ports, no VPNs, and no standing credentials to manage.
If your organization is one of the 85% currently in this evaluation process, or getting ready to be, the full survey findings break this down further by industry, role, and company size, useful benchmarking if you’re building the case internally for where this sits on the roadmap.
Download the Full 2026 State of Secure AI Connectivity Report
Frequently Asked Questions
What is non-human identity?
Non-human identity refers to a distinct, verifiable identity assigned to an AI agent, API, service, or machine workload, separate from any human identity that deployed it. We treat non-human identity as foundational to Zero Trust, since without it, organizations can’t reliably govern or audit what an autonomous system is doing.
Why is non-human identity a growing security priority?
Non-human identity has emerged as the top-named AI security concern among CISOs and CTOs, ahead of more traditional risks like credential theft or endpoint compromise. This reflects a recognition that most identity systems were built for human users and don’t translate cleanly to machine-to-machine connectivity.
How is non-human identity different from traditional identity and access management?
Traditional identity and access management authenticates a person, then grants access. Non-human identity requires a different approach because machine workloads don’t have identities in that same sense, and IP-based tracking is unreliable due to NAT, DHCP, and ephemeral addressing.
What should organizations look for in a non-human identity solution?
Look for solutions that assign each machine workload its own verifiable identity rather than just improving visibility into shared credentials, and that reduce reliance on long-lived static secrets. We approach this through Identity-First Reachability™, which eliminates the need for standing credentials and open inbound ports altogether.
