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07/06/2026 9:19 pm
TL;DR: Agentic AI digital employees could shift audits from periodic evidence collection to continuous investigation, context-building, and live assurance, according to Twine Security’s analysis of manual audit pain points. That changes the compliance assumption from human-paced reconstruction to machine-paced review, which is a governance model shift rather than a productivity tweak.
NHIMG editorial — based on content published by Twine Security: The Last Manual Audit, Agentic AI and the Future of Compliance
By the numbers:
- 70% of large companies go through cybersecurity audits every year according to CFO magazine.
Questions worth separating out
Q: How should security teams prepare identity data for agentic audit review?
A: Teams should make identity records machine-readable, complete, and linked across provisioning, approvals, ownership, and expiry.
Q: Why do agentic audit systems expose weak IAM governance so quickly?
A: They expose weak governance because they can compare evidence continuously rather than waiting for a scheduled review cycle.
Q: How do organisations know whether audit evidence is ready for AI-led review?
A: Evidence is ready when it is current, linked, and explainable without manual stitching.
Practitioner guidance
- Make entitlement lineage machine-readable Store approval source, inheritance path, owner, and expiry state in a form that can be queried across HR, IAM, PAM, and service-account systems.
- Normalize audit evidence into living records Replace one-off screenshots and exports with continuously updated records that preserve identity state, permission changes, and review outcomes.
- Unify human and non-human access history Track contractor access, manager role changes, and dormant integrations in the same governance model so reviewers can see lifecycle drift consistently.
What's in the full article
Twine Security's full blog covers the operational detail this post intentionally leaves for the source:
- The IBM audit story in full, including the 2,300-hour labour estimate and the operational breakdown behind it.
- The article's narrative examples of forgotten contractors, promoted managers, and phantom integrations as audit findings.
- Twine Security's framing of AI digital employees as continuous audit workers and the workflow changes that follow.
- The author's explanation of how a digital employee could answer auditor questions instantly during a live review.
👉 Read Twine Security's analysis of agentic AI and the future of compliance →
Agentic AI and compliance audits: what changes for IAM teams?
Explore further
08/06/2026 9:13 am
Agentic AI does not just speed up audits, it breaks the assumption that evidence review must be human-paced. Traditional compliance programmes assume auditors gather fragments, then reconstruct a defensible story after the fact. That assumption fails when the reviewer can chase multiple threads, follow lineage in real time, and adapt its inquiry as new facts appear. The implication is that audit governance must be designed around continuous machine-readable evidence, not periodic human reconstruction.
A few things that frame the scale:
- 91.6% of secrets remain valid five days after the targeted organisation is notified, showing a critical gap in remediation procedures, according to Ultimate Guide to NHIs.
- Only 20% of organisations have formal processes for offboarding and revoking API keys, and even fewer have procedures for rotating them.
A question worth separating out:
Q: What should IAM and NHI teams do when audit processes become continuous?
A: They should govern identity data as a live control surface, not a periodic reporting output. That means aligning lifecycle events, access approvals, and entitlement ownership so a continuous reviewer can see changes as they happen. The goal is not more screenshots. The goal is auditable identity state that survives real-time scrutiny.
👉 Read our full editorial: Agentic AI audit workers expose compliance limits in manual review
