This course provides a concise overview of agentic artificial intelligence and its emerging role in audit and assurance. Participants will examine how AI agents differ from traditional generative AI by planning tasks, using software tools, taking actions, and completing multi-step workflows with limited human intervention. The course explores current audit applications, including substantive procedures, confirmations, risk assessment, disclosure testing, and continuous monitoring, while addressing new risks involving autonomy, permissions, prompt injection, multi-agent systems, and accountability. Participants will also examine regulatory developments, professional standards, controls, evidence requirements, ethics, liability, and the strategic implications of agentic AI for audit firms. This event may be a rebroadcast of a live event and the instructor will be available to answer your questions during the event.
Learning Objectives
After attending this presentation, you will be able to...
- Explain how agentic AI differs from traditional generative AI
- Identify current applications of AI agents in audit and assurance
- Analyze risks arising from autonomous and multi-agent workflows
- Compare regulatory approaches to agentic AI across major jurisdictions
- Apply relevant audit, assurance, and AI governance frameworks
- Evaluate controls for logging, permissions, human review, and rollback
- Assess the ethical, liability, talent, and strategic implications of agentic AI
Major Topics
The major topics that will be covered in this course include:
- Agentic AI and levels of autonomy in audit
- Agentic AI applications across audit workflows
- Agent failures, prompt injection, and emerging threats
- US, Canadian, UK, and international regulatory developments
- Audit and assurance standards for agentic systems
- Controls, logging, permissions, evidence, and human oversight
- Independence, ethics, liability, talent, and firm strategy
