This course explores how autonomous agents are transforming internal and external audit functions. Agentic AI is redefining how auditors perform risk assessments, gather evidence, test controls, and issue reports. Participants will examine real-world examples, including audit bots from Big Four firms, and consider the impact on assurance quality, auditor judgment, and documentation standards. Key frameworks from the PCAOB, ISA, and AICPA will be discussed, along with governance strategies to ensure audit agents operate reliably, securely, and ethically. This redefines the CPA's role in ensuring the integrity and reliability of audit evidence when leveraging AI agents, impacting audit quality and professional skepticism.
Learning Objectives
- Describe how Agentic AI can be applied to automate key aspects of audit and assurance
- Analyze the risks and limitations of relying on autonomous systems in assurance engagements
- Apply PCAOB and ISA standards to agentic workflows in evidence collection and testing, understanding how these impact the auditor's professional judgment
- Design controls to validate, monitor, and document agent behavior during audits
- Understand how audit teams can collaborate with AI agents to enhance assurance quality
Major Topics
- Audit use cases: automated sampling, real-time analytics, evidence gathering
- Case studies: Big 4 agent-driven assurance platforms
- Agent reliability, explainability, and audit documentation
- PCAOB AS 1105, ISA 330, and agent-auditor integration
- Governance: SOC 1/SOC 2 controls for audit AI tools
