This certificate program equips CPAs with the knowledge and skills to oversee artificial intelligence rather than simply operate alongside the technology. As AI systems take on a growing share of accounting, audit, and finance work, the profession's value shifts from producing output to scrutinizing output: questioning machine reasoning, evaluating system reliability, supervising autonomous agents, and bearing professional responsibility for results no human hand produced.

This program addresses that shift directly. Participants build a disciplined skeptical mindset for AI-augmented work, learn a structured methodology for evaluating AI systems as professional assessors, examine how agentic AI is reshaping audit and assurance engagements, and confront the liability and malpractice exposure that follows when CPAs sign their names to machine-generated work.

Where most AI training teaches CPAs how to use these tools, this program teaches CPAs how to judge them. CPAs will leave this program prepared to serve as the human authority above the machine: the professional who examines, challenges, supervises, and ultimately stands behind the work.

Topics Include:

• Professional Skepticism Reengineered: Apply the profession's core skeptical discipline to AI-generated evidence, analysis, and recommendations, including recognition of automation bias and overreliance.
• Cognitive Traps in AI-Augmented Work: Identify how machine confidence, fluent output, and false precision erode critical thinking, and build habits that preserve independent judgment.
• The CPA as System Evaluator: Learn a structured framework for assessing AI systems, covering training data provenance, model limitations, edge cases, output reliability, and fitness for purpose.
• Evaluation in Practice: Develop testing approaches, documentation standards, and acceptance criteria that translate professional assessment into defensible workpapers.
• Agentic AI in Audit and Assurance: Understand how autonomous AI agents plan, execute, and complete engagement tasks, and where human supervision, review, and sign-off must remain.
• Governance of Autonomous Systems: Design oversight structures, escalation paths, and control frameworks for AI that acts without waiting for human instruction.
• Liability and Malpractice Exposure: Examine how professional responsibility, standards of care, and legal exposure evolve when AI performs the work and the CPA signs the opinion.
• Defensible Practice: Build documentation, disclosure, and engagement practices that protect the practitioner, the firm, and the public when AI sits inside the workflow.