Why do organisations that feel confident about protecting machine identities still underinvest in them?

Because confidence often reflects intent, not execution. The study says 88% claim machine identities get the same protection as user identities, but 79% only sometimes include them in IAM planning and 11% rarely do. That gap usually indicates weak governance, incomplete asset understanding, and a human identity bias that leaves machine credentials outside formal security design.

Why confidence diverges from actual machine identity coverage

Organisations often conflate policy intent with operational control. Machine identities are easy to assume are covered because they reuse familiar IAM language, but they behave differently from users: they are created faster, spread across more systems, and often sit outside standard ownership and review processes. That mismatch lets confidence rise even when governance and inventory coverage lag.

Another reason is that teams usually see human access first. Human accounts have clearer owners, approval paths, and audit habits, while machine credential are embedded in apps, pipelines, and infrastructure. When visibility is fragmented, human and non-human identity controls are judged by the same policy language even though the operating model is not the same.

That creates a confidence trap: people believe machine identities are protected because they are not obviously neglected, yet they are not consistently built into lifecycle, exception, and review workflows. The top non-human identity issues are usually not exotic failures, but basic governance gaps that become invisible when the environment is large and distributed.

Where underinvestment shows up in the operating model

Underinvestment is usually visible in three places. First, ownership is unclear, so no team is accountable for discovery, rotation, and offboarding. Second, machine credentials are managed as exceptions instead of as a standard identity class, which means they miss the design assumptions applied to workforce accounts. Third, security work focuses on the systems those identities access, not on the identities themselves.

This is why machine identity protection often looks mature on paper but weak in practice. A team may have secrets vaulting, policy statements, and approval gates, yet still miss service accounts that are not mapped to owners or credentials that never expire. Ownership and accountability are the difference between a controllable population and a hidden one.

It also explains why planning can be superficial. The organisation may claim machine identities are included in IAM, but inclusion means little if discovery, inventory, and renewal logic are incomplete. Service account security is a useful lens because it forces the question of whether those identities are actually governed, not merely acknowledged.

Why human-centric security habits keep machine credentials underfunded

The strongest bias is structural: most identity programs were built around people, so budgets, tooling, and metrics naturally favour workforce authentication and access review. Machine identities do not fit that cadence neatly. They do not attend onboarding sessions, they do not respond to password resets, and they often depend on automation that is owned by engineering rather than security.

That bias leads to underinvestment in the controls that matter most for machine identities, especially discovery, rotation, least privilege, and offboarding. When teams treat these identities as a byproduct of application delivery, they delay hard decisions about ownership, secret lifetime, and dependency mapping. Credential rotation becomes difficult precisely because the organisation has not designed for the scale and coupling of machine credentials.

Practical improvement usually comes from changing the unit of management. Instead of asking whether machine identities are “covered,” ask whether they are discoverable, owned, renewable, and measurable in the same way other critical identities are. The issue is not whether the organisation supports them in principle, but whether it has built the operating discipline to keep them current.

Risk and Threat Considerations

Machine identities create concentrated exposure when they are left outside formal governance, because a single secret or service account can unlock automated access across environments. That makes underinvestment risky even when there is no obvious incident history, since the failure mode is often silent accumulation of stale, shared, or overprivileged credentials.

Failure mechanism: Confidence masks incomplete discovery and weak lifecycle control, so machine credentials remain active, overused, or unowned long after the systems that created them have changed.

Impact: Attackers who obtain one machine credential can often reuse it for lateral movement, data access, or service abuse, while defenders may not notice until the blast radius is already broad.

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 addresses the attack and risk surface, while NIST SP 800-53 Rev 5 and NIST CSF 2.0 set the governance and control requirements practitioners need to meet.

Framework	Control / Reference	Relevance
OWASP Non-Human Identity Top 10	NHI-01 — Improper Offboarding	Machine identities underinvested due to weak lifecycle control create stale, orphaned credentials.
	NHI-05 — Overprivileged NHI	Underinvestment often leaves machine credentials with excess access beyond their real function.
	NHI-07 — Long-Lived Secrets	The gap between intent and execution often leaves machine secrets active for too long.
Recommendation — Inventory machine identities and revoke credentials promptly when the owning system or service changes. Apply least privilege to machine identities and remove unneeded permissions at review. Set rotation and expiry requirements for machine secrets and enforce them consistently.
NIST SP 800-53 Rev 5	IA-9 — Identification and Authentication (Non-Organizational Users)	Machine identities are authenticating non-human actors that need governed authentication controls.
	IA-5 — Authenticator Management	Credential lifecycle is central when machine identities rely on secrets, tokens, or keys.
	AC-6 — Least Privilege	Underinvestment commonly leaves machine identities with broader access than their workload requires.
Recommendation — Enforce strong authentication for non-organizational identities and review trust assumptions regularly. Manage machine credentials through issuance, rotation, storage, and revocation processes. Constrain machine identity permissions to the minimum set needed for each service.
NIST CSF 2.0	GV.RM-01 — Risk Management Strategy	The answer hinges on governance gaps and mismatched investment priorities for machine identities.
	ID.AM-01 — Physical Devices and Systems Inventory	The problem is partly an inventory and visibility failure across machine identities and their dependencies.
Recommendation — Include machine identity risk in the organisation’s formal risk strategy and funding decisions. Maintain an accurate inventory of systems and identity-bearing assets that use machine credentials.

Practitioner Guidance

What to prioritise: Treat machine identities as a governed population, not a special case inside application delivery. Start with ownership, inventory completeness, and credential lifetime, because those three factors determine whether any later control can be trusted.

What to verify: Confirm that every non-human identity has a named owner, a documented purpose, and a reviewable renewal path. If any credential can authenticate without a current owner or expiry expectation, the control is not mature enough to justify confidence.

Common mistake: Do not equate “included in IAM planning” with actual operational coverage. A planning statement is useful only when it produces discoverable assets, measurable rotation, and explicit offboarding.

Practitioner takeaway: Underinvestment usually reflects invisible debt, not lack of concern, so the key test is whether machine identities are managed as living assets with accountable owners and enforceable lifecycles.