Non-human identity management is shifting from secrets to governance

At a glance

What this is: This is a vendor summary of KuppingerCole’s Leadership Compass for Non-Human Identity Management, which argues that NHI governance is shifting from secrets storage to lifecycle control, auditability, and policy enforcement.

Why it matters: IAM, PAM, and NHI teams need to treat machine identities as governed actors, because growth in automation and AI makes static secret handling too narrow for secure access oversight.

By the numbers:

• Non-human identities now outnumber human identities 144 to 1 by some estimates.

👉 Read Akeyless’s analysis of non-human identity management shifting from secrets to governance

Context

Non-human identity management now sits at the point where access governance, secrets handling, and automation control meet. The article argues that environments built for stable human users no longer match the reality of machine identities, service accounts, pipelines, and AI-driven systems that authenticate and act continuously.

KuppingerCole’s Leadership Compass is used here as a signal that NHI governance is becoming a distinct category rather than an extension of human IAM. The article frames the issue as one of lifecycle control, auditability, and ownership across cloud, hybrid, and on-prem environments, not just credential storage.

Key questions

Q: What breaks when secrets management is separated from identity governance?

A: When secrets management is separated from identity governance, credentials can outlive approvals, regions, or vendor relationships. That creates a mismatch between who is supposed to control access and who actually can. The result is weak revocation, poor auditability, and higher risk in distributed estates.

Q: When should organisations prioritise policy-bound access over long-lived machine credentials?

A: They should prioritise policy-bound access when identities are embedded in cloud pipelines, Kubernetes, DevOps workflows, or AI-driven systems that act continuously and change quickly. Long-lived machine credentials create reuse and audit problems that static rotation alone cannot solve. Short-lived issuance becomes the better control when access must follow the task, not the account.

Q: What are the signs that non-human identity governance is starting to slip?

A: Warning signs include reliance on manual upgrade paths, ad hoc secret handling, and fragmented access management across tools and environments. The article mentions caveats, dispatch limits, SSO support, and automated update channels, all of which point to the need for controlled operational discipline. When teams cannot explain how identities are provisioned, updated, and constrained, governance is already weaker than it should be.

Q: How should IAM teams govern human, non-human, and AI identities together?

A: Start by separating the identity types in policy, ownership, and review cadence, then define where controls can be shared and where they must remain distinct. Human users, service identities, and AI systems do not fail in the same way, so the governance model has to preserve that difference while still producing one audit trail.

Technical breakdown

Why static secrets models fail for non-human identity

Traditional secrets management assumes credentials are relatively stable, can be rotated on schedule, and are tied to predictable operators. Non-human identities break those assumptions because they scale faster, change more often, and are embedded in code, pipelines, Kubernetes, and infrastructure workflows. That creates drift between where access exists and where it is governed. The result is not just exposure of a secret but loss of lifecycle control over who or what is using it, for how long, and under what policy. Practical implication: treat NHI access as an identity lifecycle problem, not a vaulting problem.

Practical implication: govern NHI access as a lifecycle and policy problem, not only as credential storage.

How lifecycle governance changes the control model

Lifecycle governance for non-human identity covers creation, use, rotation, ownership, audit, and decommissioning. That matters because non-human actors often outlive the workflow or application that created them, especially when ownership is unclear or delegated across teams. In practice, governance has to bind each identity to an accountable owner and a revocation path, otherwise credentials persist after the business need has changed. This is where auditability and reporting become controls, not just evidence. Practical implication: if the identity cannot be traced to an owner and a retirement point, it is not truly governed.

Practical implication: require owner mapping and decommissioning controls for every non-human identity.

Why policy-bound access matters more than long-lived credentials

The article’s core architectural point is that dynamic environments need short-lived, policy-bound access rather than reusable credentials that sit in pipelines or infrastructure for extended periods. That changes the control boundary from secret possession to access issuance and enforcement. For machine identities, the decisive question becomes whether access is issued only when the workload, pipeline, or automation task needs it, and whether the policy can be enforced consistently across cloud and on-prem environments. Practical implication: move enforcement earlier in the access path, before credentials become broadly reusable.

Practical implication: issue short-lived, policy-bound access instead of relying on reusable machine credentials.

Threat narrative

Attacker objective: The objective is to leverage unmanaged machine access to perform unauthorized actions while avoiding detection through weak lifecycle governance.

1. Entry occurs when machine credentials, tokens, or certificates are embedded in code, pipelines, or infrastructure workflows and become accessible outside the intended runtime boundary.
2. Privilege is then sustained through long-lived or poorly governed non-human identities, allowing access to continue after the original operational need has changed.
3. Impact follows when overexposed machine access enables unauthorized actions across cloud, hybrid, or on-prem environments, while audit and ownership gaps delay containment.

Breaches seen in the wild

• Salesloft OAuth token breach: hackers stole OAuth tokens to access Salesforce data via Salesloft.
• Hugging Face Spaces breach 2024: Unauthorised access to Hugging Face Spaces may have exposed secrets users stored for AI apps; tokens were revoked and org tokens removed.

Read and download The State of NHI & AI Agent Breach Report 2026, covering 150+ breaches impacting Non-Human Identities including AI Agents.

NHI Mgmt Group analysis

Non-human identity management is no longer a secrets subdiscipline. The article reflects a category shift: machine access has become a governance problem with ownership, lifecycle, and audit requirements that mirror, but do not duplicate, human IAM. Secrets storage can hide credentials, but it cannot by itself define who is accountable for a service account, when access should end, or how policy should follow the workload. Practitioners should treat NHI as a control plane problem, not a vault-only problem.

Lifecycle status reporting is becoming a control, not a dashboard feature. KuppingerCole’s emphasis on auditability and reporting signals that evidence of creation, use, rotation, and decommissioning is now part of the control set. In automated environments, the absence of lifecycle telemetry means the identity programme cannot prove ownership or timely retirement. The practical conclusion is that governance teams need machine identity evidence that is as reviewable as human access certification.

Short-lived, policy-bound access is replacing the assumption of durable machine privilege. Static credentials were designed for actors that authenticate in predictable ways and retain access long enough to be reviewed. Non-human identities in modern pipelines and AI-driven systems do not fit that pattern, so governance must shift from credential durability to issuance discipline. That change affects how teams think about policy, revocation, and operational trust across distributed environments.

Identity-to-owner mapping is the missing accountability layer for NHI programmes. The article’s focus on delegated lifecycle management points to a common failure mode: a non-human identity exists, but no one can explain who owns it, what business function it serves, or how it is retired. That is not a tooling gap alone. It is an accountability gap that weakens every downstream control, including audit, review, and incident response.

Zero-knowledge architecture matters because governance without exposure control still leaves residual trust debt. The article’s architectural notes show that reducing central exposure can support governance, but only if lifecycle controls remain intact. The broader lesson is that NHI security now sits at the intersection of cryptographic containment and administrative control. Practitioners should evaluate both dimensions together, because one without the other leaves the programme incomplete.

From our research library:

• NHIs outnumber human identities by 25x to 50x in modern enterprises, according to the Ultimate Guide to NHIs.
• Read next: Ultimate Guide to NHIs

What this signals

Lifecycle governance is the new boundary for machine identity programmes. Teams that still rely on secrets storage as the main control will keep missing the real problem, which is whether a machine identity can be created, owned, reviewed, rotated, and retired as a governed asset. That is why ownership mapping and retirement logic now matter as much as credential protection.

Non-human identity programmes will increasingly absorb AI-driven actors. Once autonomous or AI-driven systems authenticate and act inside production workflows, they stop looking like edge cases and start looking like a core identity population. The governance model has to expand to include issuance discipline, audit evidence, and policy enforcement for actors that do not fit human access rhythms.

Identity blast radius: the practical measure of NHI risk is not how many secrets exist, but how many systems can act on them before governance catches up. Programmes that cannot connect each identity to an owner and a retirement point will continue to accumulate trust debt across cloud and automation layers.

For practitioners

• Map all non-human identities to named owners Build an inventory that ties each service account, token, certificate, or pipeline identity to a business owner, technical owner, and retirement trigger.
• Replace durable access with short-lived issuance Reduce reuse by issuing access only when a workload, pipeline, or automation task needs it, and enforce expiry at the point of issuance.
• Extend audit trails to lifecycle events Record creation, use, rotation, delegation, and decommissioning events so review teams can verify what happened to each identity over time.
• Classify AI-driven systems as governed identity actors When autonomous or AI-driven systems authenticate and act, place them under the same ownership, policy, and review discipline as other non-human identities.
• Close the gap between secrets and governance Do not let vaulting stand in for governance. Align secrets handling, access policy, and lifecycle retirement in one operating model.

Key takeaways

• The article shows that non-human identity risk is fundamentally a governance problem, not just a secrets storage problem.
• The source cites 144 to 1 as one estimate for the ratio of non-human to human identities, underscoring how quickly machine access now scales.
• Teams need owner mapping, lifecycle evidence, and short-lived access if they want to govern non-human identities rather than merely store their credentials.

Key terms

• Non-Human Identity (NHI): A digital identity assigned to a non-human entity such as a software application, service account, API key, bot, machine, or AI agent that enables it to authenticate and interact with systems without direct human involvement. NHIs now outnumber human identities in most enterprises by 25 to 50 times.
• Identity Lifecycle Governance: Identity lifecycle governance is the set of processes that create, change, review, rotate, and revoke access across human and non-human identities. It matters because access risk usually increases when lifecycle events are slow, incomplete, or disconnected from the systems that rely on them.
• Policy-Backed Access Boundary: A policy-backed access boundary is the point where an identity claim becomes an enforceable data access rule. It matters because least privilege is only real when the system that owns the data, not just the application, can deny unsafe access.
• Identity-to-Owner Mapping: Identity-to-owner mapping links each non-human identity to a responsible person or team that can approve, review, and retire it. Without that mapping, auditability weakens and the identity can remain active long after its original purpose has ended.

What's in the full analysis

Akeyless's full article covers the operational detail this post intentionally leaves for the source:

• The report criteria behind KuppingerCole’s leadership assessment and how it evaluated NHI platforms
• The integration patterns for cloud, Kubernetes, DevOps, and CI/CD environments
• The lifecycle reporting, delegated management, and identity-to-owner mapping capabilities discussed in the article
• The architectural discussion of Distributed Fragments Cryptography and zero-knowledge design

👉 The full Akeyless article covers the KuppingerCole Leadership Compass criteria, lifecycle capabilities, and architectural signals in more detail.

Deepen your knowledge

NHI governance, agentic AI identity, and machine identity lifecycle are core topics in our NHI Foundation Level course, the industry's only accredited NHI security programme. If you are building or maturing an IAM programme, it is worth exploring.