Insights
Why Large Language Models Hallucinate
LLMs generate probable text, not guaranteed facts. Learn why hallucinations occur and how auditors should control, validate, and use AI outputs.
RAG for Internal Audit Knowledge
RAG can ground AI in audit methodology, policies, standards, and prior reports. Its value depends on source governance, access, freshness, and validation.
Who Is Accountable When AI Makes Decisions?
AI can automate decisions, but not accountability. Define ownership, human oversight, decision rights, and third-party responsibilities.
What Good AI Incident Management Looks Like
Good AI incident management links detection, escalation, containment, investigation, reporting, remediation, recovery, and learning.
AI Risk Is More Than Technology Risk
AI risk extends beyond IT into strategy, operations, compliance, fraud, people, and reputation. Internal audit needs an enterprise-wide view.
Using AI to Analyze Audit Evidence
How to use AI to extract, compare, and synthesize audit evidence without losing traceability, professional skepticism, or human review.