The access-trust gap widens as SaaS and AI outpace IAM

At a glance

What this is: 1Password’s annual report argues that the access-trust gap is widening because SaaS and AI adoption are moving faster than traditional IAM can govern.

Why it matters: IAM, IGA, PAM, and identity architects need to treat access as continuous and contextual, because unmanaged apps, shadow AI, and unfederated identities now sit outside the controls many programmes still assume are sufficient.

By the numbers:

• 52% of employees downloaded apps without IT approval.
• 73% of employees were encouraged to use AI.
• 74% of security and IT professionals said SSO is not a complete solution for securing employee identities.
• 30% of apps are left outside SSO.

Context

The access-trust gap is the mismatch between what identity programmes can see and govern, and how people actually use SaaS and AI tools to get work done. In practical terms, traditional IAM assumes a managed application estate, stable sign-on paths, and predictable review points. The article argues that those assumptions no longer hold in cloud-native workplaces.

That matters because unmanaged apps, shadow AI, and unfederated access expand the identity surface beyond SSO and directory-centric control. For practitioners, the issue is not whether employees will adopt new tools, but whether governance can still enforce policy, offboarding, and data protection when access is dispersed across managed and unmanaged services.

Key questions

Q: How should security teams govern AI tools that connect to SaaS data?

A: Treat each AI tool as a non-human identity with an owner, a defined scope, and an expiry path. Require approval for every new integration, limit access to the minimum necessary SaaS objects, and review delegated permissions on a recurring schedule. Governance fails when consent is treated as a one-time event instead of a lifecycle.

Q: Why do unsanctioned AI tools create so much identity risk?

A: Unsanctioned AI tools bypass the directory, policy, and audit paths that make identity governance work. Once users move outside approved access routes, security teams lose visibility into who used what, which credentials were involved, and whether data handling stayed within policy. That turns routine adoption into unmanaged entitlement expansion.

Q: What are the signs that access reviews are no longer keeping up with SaaS sprawl?

A: Common signs include long review backlogs, repeated exceptions, unknown applications in use, and licence data that does not match actual business activity. When those signals appear together, the problem is usually not just staffing. It is that the governance process no longer matches the speed of the environment.

Q: What is the difference between SSO and continuous access assurance?

A: SSO authenticates a user to a service, while continuous access assurance evaluates whether the app, device, data type, and policy state still justify that access. In modern SaaS and AI environments, authentication alone does not prove the access path is sanctioned, monitored, or safe for the data involved.

Technical breakdown

Why SSO no longer covers the full access surface

Single sign-on centralises authentication, but it does not govern every application, device, or workflow where identity is used. When users access consumer SaaS, personal AI tools, or unsanctioned apps outside the SSO path, the control plane loses visibility into who has access, where data moves, and whether offboarding has actually removed the route. That creates an access-trust gap, not just a federation gap. In identity terms, the problem is not authentication failure alone. It is the widening space between authorised entry points and actual business access paths, which leaves governance blind to risk outside the federated boundary.

Practical implication: identity teams need inventory and control coverage for non-federated access paths, not just stronger SSO policy.

How shadow AI changes identity governance assumptions

Shadow AI is a governance problem because the user may be legitimate while the tool path is not. Employees can move company data into unapproved LLMs on personal devices or at work, which bypasses the review and logging models that traditional IAM relies on. That means the trust decision is no longer only about who the user is, but also about which AI service receives the data and under what policy. The article shows that policy awareness alone is insufficient when usage is encouraged but enforcement lags.

Practical implication: governance must extend to approved AI services, data handling rules, and enforcement around unsanctioned AI use.

The access-trust gap is a lifecycle problem, not just an authentication problem

Offboarding, recertification, and entitlement review assume access stays in one place long enough to be found and removed. When workers bypass IT, use unapproved tools, or retain access to prior employer accounts, those lifecycle controls break down because the programme never owned the access path in the first place. That is why the article’s findings point beyond password strength and toward lifecycle blind spots. Access control that starts and ends at login cannot govern the full user journey across SaaS sprawl and AI adoption.

Practical implication: IAM programmes should map lifecycle controls to unmanaged applications and not treat account closure as equivalent to access removal.

Threat narrative

Attacker objective: The practical objective is to obtain data or access through identity paths that security and IT teams cannot fully see, control, or revoke.

1. Entry occurs when employees adopt SaaS or AI tools without IT approval, creating access paths outside the managed identity control surface.
2. Credential or account misuse follows when users sign in with weak passwords, bypass federated paths, or retain access to prior employer systems.
3. Impact emerges as data is shared into unapproved AI services, unmanaged apps, and accounts that security teams cannot reliably govern or revoke.

Breaches seen in the wild

• Salesloft OAuth token breach: hackers stole OAuth tokens to access Salesforce data via Salesloft.
• Klue OAuth Supply Chain Breach: OAuth tokens compromised in Klue integration breach affecting 700+ organisations via Salesforce data access chain.

Read and download The State of NHI & AI Agent Breach Report 2026, covering 200+ breaches impacting Non-Human Identities including AI Agents.

NHI Mgmt Group analysis

Access control has become a boundary problem, not a login problem. Traditional IAM was designed to secure known sign-in flows and centrally managed applications. The article shows that workers now use SaaS and AI tools faster than identity teams can catalogue them, which means the real failure is control-plane coverage. The practitioner conclusion is that access governance has to extend to unmanaged applications and non-federated workflows, not only to the managed estate.

Shadow AI exposes a governance model built for slower adoption cycles. The report’s AI findings are not just about policy awareness, they show that encouraged use and inconsistent compliance can coexist at scale. That breaks the assumption that training plus acceptable-use policy is enough to govern data movement into LLMs. The implication is that AI access policy, data handling, and enforcement need to be treated as one operational control surface.

Access-trust gap is the right name for a wider identity blast radius. The report makes clear that identity risk is no longer confined to federated applications and password hygiene. Unapproved apps, unmanaged devices, and prior-employer access all expand the radius of identity failure beyond what legacy IAM was built to absorb. Practitioners should treat the access trust gap as a programme design issue, not a point control defect.

SSO is necessary infrastructure, but it is no longer a complete governance model. The article’s numbers support a more specific position: federation remains useful, but it cannot represent the full security state of a modern workforce. The field should stop equating successful login with secure access and start measuring whether every material access path is inside the governance envelope. That is the standard identity leaders should apply.

The next identity control objective is continuous access assurance. The report points toward a model where identity decisions must reflect device context, application approval status, and data sensitivity in real time. That does not replace IAM, IGA, or PAM, but it changes how they are judged. Practitioners should expect continuous assurance to become the organising principle for access governance across human, machine, and AI-driven work.

What this signals

Access-trust gap: The useful concept here is not shadow IT on its own, but the widening distance between authenticated identity and governable access. As SaaS and AI adoption accelerates, programmes that still equate sign-in with control will miss where the actual risk now lives.

The operational shift is from access approval to access assurance. That means measuring whether every material application, AI service, and data path is actually inside the governance envelope, not merely whether the user can log in.

This also changes the identity architecture conversation. Continuous context, device state, and app approval status need to become part of access decisions if IAM, IGA, and PAM are going to cover how work gets done now.

For practitioners

• Map unmanaged access paths Inventory the SaaS and AI tools employees use outside federated sign-on, then classify which of those paths carry company data or privileged workflows.
• Extend policy to shadow AI Write enforceable rules for approved AI services, prohibited data types, and personal-device use so policy applies at the point of data entry.
• Treat offboarding as access-path removal Verify that prior-employer accounts, unsanctioned apps, and ad hoc sharing links are removed when a user leaves or changes role.
• Measure SSO coverage gaps Track what percentage of material business applications sit outside SSO and prioritise remediation by data sensitivity rather than convenience.

Key takeaways

• The report’s core message is that identity control is no longer coextensive with authentication, because employees are using tools and data paths that sit outside traditional governance boundaries.
• The evidence points to a broad governance gap, with widespread unapproved app use, AI adoption that outpaces policy compliance, and substantial SSO coverage gaps.
• Practitioners should move from login-centric controls to continuous access assurance that covers unmanaged applications, AI services, and offboarding across the full access surface.

Key terms

• Access-trust gap: The gap between having a policy and actually enforcing it when access is requested. It appears when compliance, HR, or training data sits in separate systems from the access decision, allowing users to reach resources even though a required condition has not been met.
• Shadow AI: AI agents, copilots, or connected tools operating without full visibility or governance from security teams. Shadow AI becomes an identity problem when those systems authenticate with unmanaged tokens, service accounts, or OAuth apps that can reach production resources.
• Continuous Access Control: Continuous access control is the practice of evaluating identity permissions and behaviour in real time instead of relying only on periodic certification. It is especially important for autonomous and machine identities because their access patterns can change faster than quarterly governance cycles can detect.
• Non-Federated Access Path: A non-federated access path is any login or session route that does not pass through the corporate identity provider or trusted federation flow. In AI environments, that often means local accounts, embedded credentials or unmanaged service paths that leave no normal identity event behind.

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