Notifications
Clear all
Topic starter
24/06/2026 7:01 pm
TL;DR: Artificial intelligence is reshaping identity management expectations, but the source webinar is primarily a high-level discussion rather than a technical roadmap, according to Netwrix. The practical issue is that IAM, PAM, and lifecycle controls must be reassessed wherever AI changes access patterns, accountability, or data exposure.
NHIMG editorial — here’s why we think this discussion matters
Questions worth separating out
Q: How should security teams govern AI-related access without losing accountability?
A: Security teams should treat AI-related access as an identity governance problem, not only a tooling problem.
Q: Why do AI-supported workflows make privileged access harder to manage?
A: AI-supported workflows can multiply the number of actions taken on behalf of one subject, which makes privilege easier to misuse and harder to attribute.
Practitioner guidance
- Map AI-enabled workflows to identity owners Inventory where artificial intelligence changes authentication, approval, or delegated execution.
- Review privileged access boundaries around AI-supported tasks Check whether any task that can be executed with elevated rights has clear session logging, approval logic, and attribution back to a human or system owner.
- Extend lifecycle controls to non-human identities behind AI processes Apply provisioning, rotation, recertification, and offboarding rules to the service accounts, tokens, and certificates that support AI-enabled operations.
What to expect at the briefing
Netwrix's full webinar covers the operational detail this post intentionally leaves for the source:
- Speaker-led discussion of how artificial intelligence is changing IAM decision paths and control ownership.
- Operational examples of where privileged access and lifecycle governance need to be re-evaluated.
- Broader context from Netwrix speakers on how identity teams should think about AI in practice.
- Additional related resources for teams exploring identity management, PAM, and data access governance.
👉 Watch Netwrix's on-demand webinar on artificial intelligence and IAM →
Artificial intelligence and IAM: are your controls keeping up?
Explore further
25/06/2026 4:07 am
AI governance fails first at the assumption that identity activity is still human-paced. The article sits in a space where AI is changing how identity work is evaluated, approved, and monitored. That means existing IAM cadence, PAM oversight, and review models must be re-read against a faster decision loop, not just a larger workload. Practitioners should treat AI as a forcing function that exposes where identity governance still depends on human timing.
A few things that frame the scale:
- Two-thirds of enterprises have endured a successful cyberattack resulting from compromised non-human identities, with a quarter encountering multiple attacks, according to The 2024 ESG Report: Managing Non-Human Identities.
- 72% of organisations have experienced or suspect they have experienced a breach of non-human identities, including 46% confirmed and 26% suspected.
A question worth separating out:
Q: Should IAM teams treat AI as a separate identity domain?
A: No. IAM teams should treat AI as a trigger to reassess existing identity domains, especially NHI, PAM, and access lifecycle management. The underlying controls still apply, but AI changes how quickly decisions happen and how delegation is expressed. The right response is to adapt governance models, not build a disconnected exception path.
👉 Read our full editorial: AI and IAM: what identity teams need to know now
