A risk operating model in which security, privacy, compliance, engineering, and third-party risk manage different parts of the same system without one shared view of exposure. In AI environments, this fragmentation hides dependencies and slows response to change.
Expanded Definition
A fragmented risk program exists when different teams assess the same environment through separate lenses, using separate inventories, severity models, and response paths. In NHI and agentic AI environments, that split is especially damaging because service accounts, secrets, API access, and model-connected tools create shared exposure across domains that are often governed independently.
Definitions vary across vendors and operating models, but the core issue is consistent: no single risk view connects identity, application, infrastructure, privacy, and third-party dependencies. That makes it harder to see how a weak secret, an overprivileged NHI, or an external integration can become a systemwide event. NHI Management Group aligns this concern with the broader need for unified exposure management, as discussed in the Ultimate Guide to NHIs - Key Challenges and Risks and the NIST Cybersecurity Framework 2.0.
The most common misapplication is treating fragmented ownership as a reporting problem rather than an exposure problem, which occurs when teams share metrics but not decisions, inventory, or remediation authority.
Examples and Use Cases
Implementing a unified risk model rigorously often introduces process friction, requiring organisations to weigh faster local decision-making against slower but more accurate cross-functional coordination.
- A security team flags an overprivileged service account while engineering tracks it as a deployment dependency and compliance tracks it as a control exception, leaving no one accountable for remediation.
- Privacy reviews identify a third-party data flow, but IAM and cloud teams do not map the related API keys and token lifetimes, so the true blast radius remains hidden.
- An AI agent gains access through a connected tool, yet application risk, vendor risk, and NHI governance each record the issue separately, preventing a full incident picture.
- A platform team rotates secrets on schedule, but third-party risk does not know which downstream integrations depend on them, causing a service outage that was never modelled in the risk register.
- The Top 10 NHI Issues often surface in programs where one team owns secret storage, another owns access policy, and a third owns incident response, but no shared workflow ties them together.
That fragmentation is exactly why the control logic in the NIST Cybersecurity Framework 2.0 matters for cross-domain dependencies, even when no single team claims full ownership.
Why It Matters in NHI Security
Fragmented risk programs are dangerous because NHI exposure is rarely isolated. A single compromised secret can affect pipelines, cloud workloads, service accounts, and AI tools at once, while each team only sees its own slice of the event. NHI Management Group research shows that only 5.7% of organisations have full visibility into their service accounts, and that visibility gap becomes much worse when risk ownership is split across functions.
The operational consequence is delayed containment. Organisations may keep approving exceptions, renewing tokens, or onboarding integrations without understanding how one dependency changes the risk posture of several others. That is why the Ultimate Guide to NHIs emphasises unified governance, and why the Ultimate Guide to NHIs - Why NHI Security Matters Now frames NHI risk as an enterprise-wide resilience issue, not a narrow credential problem. Two-thirds of enterprises have endured a successful cyberattack resulting from compromised non-human identities, which makes shared risk ownership a practical necessity rather than a reporting preference.
Organisations typically encounter the cost of fragmentation only after a breach, outage, or audit finding reveals that no one could reconstruct the full chain of exposure, at which point the fragmented risk program becomes operationally unavoidable to address.
Standards & Framework Alignment
This section maps relevant standards and security frameworks to the operational risks and controls described in this guidance.
OWASP Non-Human Identity Top 10 and CSA MAESTRO address the attack and risk surface, while NIST CSF 2.0, NIST Zero Trust (SP 800-207) and NIST AI RMF set the governance and control requirements practitioners need to meet.
| Framework | Control / Reference | Relevance |
|---|---|---|
| NIST CSF 2.0 | GV.RM-01 | Risk management requires shared governance and consistent enterprise-wide visibility. |
| NIST Zero Trust (SP 800-207) | SC-7 | Zero Trust depends on continuous assessment across identity and dependency boundaries. |
| OWASP Non-Human Identity Top 10 | NHI-01 | NHI risk grows when ownership, visibility, and governance are split across teams. |
| CSA MAESTRO | GOV-02 | Agentic AI governance needs coordinated oversight of tools, identities, and downstream risk. |
| NIST AI RMF | GOVERN | AI risk governance calls for accountability, mapping, and oversight across the lifecycle. |
Centralize NHI inventory and remediation so overprivileged or exposed identities are addressed consistently.
Related resources from NHI Mgmt Group
- How should security teams build an integrated risk management program that moves from fragmented reporting to consistent governance?
- How should security teams reduce privileged access risk when identity tools are fragmented?
- How should security teams reduce risk from fragmented IAM controls?
- Why do fragmented cryptographic inventories create operational risk?
Deepen Your Knowledge
Reviewed and updated by the NHIMG editorial team on August 28, 2026.
NHI Mgmt Group — the #1 independent authority on Non-Human Identity, IAM, and Agentic AI security. nhimg.org
