The Last Manual Audit: Agentic AI and the Future of Compliance

By Justin Woody, Co-Founder of Twine

Why are cybersecurity audits universally hated?#

Roughly 70% of large companies conduct annual cybersecurity audits, and they’re widely despised. Compliance teams spend months gathering evidence, working extended hours, and managing operational slowdowns. The process involves auditors requesting documentation with tight deadlines and follow-up demands-nothing innovative or considerate about it.

What does an audit actually feel like?#

The author recounts his experience at IBM’s financial services division during an identity and access management audit. Four auditors submitted 40 requests with a 72-hour deadline and four-hour response requirements. The team assembled in Research Triangle Park to merge massive datasets, cross-reference user accounts against outdated directories, and decode thousands of cryptic logs. They worked late nights racing against closing deadlines in what felt like a poorly designed system destined for failure.

Why are audits like digital archaeology?#

Audits involve reconstructing narratives from digital fragments-logs, permission changes, and decisions buried in historical records. It’s backward-looking investigation, pulling the past into focus while the future has already moved forward.

How will AI digital employees impact audits?#

Unlike mere automation software, AI digital employees function with agency, investigating autonomously and adapting strategies. They’ll transform audits through three mechanisms:

• Proactive Investigation: Identifying potential compliance issues before they become failures
• Dynamic Adaptation: Adjusting investigative approaches in real-time as patterns emerge
• Continuous Monitoring: Maintaining persistent awareness rather than conducting periodic reviews

Why is Context so Important?#

Auditors require narrative alongside evidence. AI systems can construct comprehensive digital twins of environments, providing instant answers and explaining the “why” behind permissions-not just their existence, but their origin, usage patterns, and alignment with enterprise norms.

How do AI Digital Employees uncover hidden risks?#

Verifying terminated employee access would traditionally require genealogical reconstruction of permission inheritance through groups and outdated authorities. AI systems instantly produce lineage documentation while surfacing hidden risks human teams miss under information overload: forgotten contractor access, lingering administrative privileges, and dormant service accounts.

What is the difference between static and living evidence?#

Traditional audits rely on decaying static evidence-screenshots and exported logs. AI digital employees treat evidence as living information that’s continuous and dynamic, building historical records as events occur rather than reconstructing afterward.

Can we trust AI to verify human behavior?#

While concerns exist about non-human verification of human conduct, AI offers consistency: identical rigor without fatigue, shortcuts, or political considerations.

How much do manual audits cost?#

The IBM audit consumed 2,300 hours across eleven people over three weeks, causing project delays and resource depletion-delivering only temporary assurance that expired upon completion.

Why is AI assurance more cost-effective?#

Continuous assurance through AI reduces costs progressively while eliminating frantic travel and endless log processing tasks.

Why will this be the last manual audit?#

As outdated as carbon paper, traditional audits will fade. This transformation represents something fundamentally different: a digital employee that does not wait, that does not forget, that sees the why as clearly as the what. The shift frees human judgment by having AI investigate first and provide fact-based narratives.