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09/07/2026 1:40 pm
TL;DR: Security and technology trends are converging on a single point: identity is becoming the control plane for AI systems, trusted access abuse, and operational resilience, according to Imprivata’s analysis. The practical shift is away from broad experimentation and toward governed permissions, continuous verification, and tighter lifecycle control across human and machine identities.
NHIMG editorial — based on content published by Imprivata: Breaking down recent security and technology trends and what they reveal about the future of identity, access, and risk
By the numbers:
- 85% of hospitals experienced vendor-related disruptions over the past year.
- 85% of organisations lack full visibility into third-party vendors connected via OAuth apps.
Questions worth separating out
Q: How should security teams govern AI systems that can access enterprise data and workflows?
A: Treat those systems as governed identities, not just applications.
Q: Why do valid credentials create such a large attacker advantage?
A: Because they let attackers blend into normal activity.
Q: What breaks when identity continuity is not part of resilience planning?
A: Access recovery becomes as fragile as the outage itself.
Practitioner guidance
- Map AI system permissions before production use Inventory every AI-connected workflow that can read data, call tools, or trigger actions.
- Reduce the value of valid credentials Shift detection and control design toward session behaviour, privilege scope, and token persistence.
- Stress-test identity continuity during disruption Run outage exercises that include emergency access, third-party dependencies, and approval bottlenecks.
What's in the full article
Imprivata's full blog post covers the operational detail this post intentionally leaves for the source:
- Specific discussion of how AI systems are changing enterprise governance priorities as digital workers.
- The healthcare and public-sector disruption signals that underpin the resilience argument.
- The incident patterns behind token theft, persistence, and trusted access abuse across modern environments.
- The article's broader framing of security maturity, modernization, and operational readiness.
👉 Read Imprivata's analysis of AI identity oversight, healthcare resilience, and trusted access risk →
AI identity oversight and trusted access: what should IAM teams change?
Explore further
09/07/2026 1:44 pm
AI governance has become an identity governance problem before it becomes an AI governance problem. Once AI systems are allowed to retrieve data or execute workflows, the core question is no longer model quality but who or what is allowed to act. That means IAM becomes the control plane for AI-enabled business processes, not a downstream administrative layer. Practitioners should treat AI access design as part of identity architecture, not as a separate innovation track.
A few things that frame the scale:
- Only 1.5 out of 10 organisations are highly confident in their ability to secure NHIs, compared to nearly 1 in 4 for securing human identities, according to The State of Non-Human Identity Security.
- 85% of organisations lack full visibility into third-party vendors connected via OAuth apps, with 38% reporting no or low visibility and 47% reporting only partial visibility.
A question worth separating out:
Q: Who is accountable when AI or vendor access causes disruption?
A: Accountability sits with the organisation that granted the access and accepted the dependency. Vendor incidents may trigger the disruption, but internal teams still own access design, review cadence, and emergency revocation. That is why governance, contract boundaries, and identity ownership need to be explicit before production use.
👉 Read our full editorial: AI identity oversight, healthcare resilience, and trusted access risks
