The agentic AI playbook for internal audit
Autonomous control testing: The new operating model for internal audit.
The greatest risk for internal audit is not a control gap, but the risk of failing to use AI to work more intelligently. Whilst most teams use generative AI to summarise data, the real breakthrough lies in agent-based AI – a technology that not only describes the work but also carries it out.
Our new playbook explores why the labour-intensive model of control testing has reached its limits and how autonomous control testing offers the first credible solution. In it, you’ll learn more about:
The greatest risk for internal audit is not a control gap, but the risk of failing to use AI to work more intelligently. Whilst most teams use generative AI to summarise data, the real breakthrough lies in agent-based AI – a technology that not only describes the work but also carries it out.
Our new playbook explores why the labour-intensive model of control testing has reached its limits and how autonomous control testing offers the first credible solution. In it, you’ll learn more about:
- The mechanisms behind the transition from generative summaries to the autonomous execution of workflows.
- Strategies for building AI expertise and transitioning your team to a ‘reviewer-first’ model.
- A step-by-step implementation plan for audit leadership to expand the scope of audit work whilst maintaining rigorous governance.
Stop merely ticking boxes and start interpreting risks. Download the guide to discover how autonomous testing is transforming the economics, talent model and strategic role of internal audit.
プロバイダー: Optro, Inc. | サイズ: 7.41MB | 言語: 英語