AI in Accounting and Audit: Practical Use and Professional Judgment

This practical, tool-neutral certificate program helps accounting and audit professionals use AI responsibly across real engagement work, from drafting and research to documentation, validation, and review.

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Ensure Your Staff Is Using AI Responsibly

Understanding how to use AI tools is important to improve efficiency and stay ahead in the industry, but usage isn't the only thing your staff needs to know. Without proper training, polished AI output can obscure unsupported conclusions, reviewers may miss key questions, and client-side AI use can affect evidence before your team sees it.

As part of Becker’s suite of AI learning products, AI in Accounting and Audit: Practical Use and Professional Judgment helps teams build practical AI literacy, apply professional skepticism, recognize client-side implications, and use AI intentionally across engagement work.

Learn More About How Accountants Can Succeed with AI

How are today's accounting professionals and firms using AI? Download our free whitepaper, Realizing the Potential of AI in Accounting Through Responsible Adoption, and discover how accounting professionals can effectively build skills and confidence to leverage AI.

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Realizing AI's Impact in Accounting through Responsible Adoption

What Your Team Will Learn

Becker worked with Tal Goldhamer, former Chief Learning Officer of EY, to develop and teach a six-course program specifically for firms. Each course strengthens judgment your team can apply and defend.

Use AI Responsibly in Accounting and Audit Workflows

Apply practical AI literacy to each step of the engagement cycle, while following firm policy, approved-tool guidance, and confidentiality requirements.

Evaluate AI Output with Professional Skepticism

Recognize inaccuracies, prompt bias, and variable model behavior and how to treat AI-generated content as input to judgment rather than a conclusion.

Validate, Document, and Review AI-Assisted Work

Test AI output against reliable sources, determine when documentation is needed, and ask stronger review questions.

Assess AI's Impact Across the Engagement Lifecycle

Understand how both client and firm AI use can affect risk, controls, reliability, and engagement-level decision making.

Six CPE-Eligible Courses within the AI Certificate Program

How Modern AI Tools Actually Work

1.5 Credits

A foundational course teaching learners the practical AI literacy needed before using, validating, reviewing, or integrating AI into accounting and audit work, including why outputs are probabilistic and where common failure modes come from.

Learners will also complete hands-on exercises that require them to test prompts, compare AI outputs to source materials, identify common failure modes, match tools to appropriate use cases, and classify AI-assisted tasks by risk level.

Using AI in Everyday Accounting and Audit Work

1.5 Credits

In this practical workflow course, learners practice briefing AI, using it within bounded workflows, and keeping source validation and human ownership firmly in place.

Hands-on activities include improving prompts, drafting and reviewing PBC requests, refining walkthrough notes, developing evidence-based hypotheses, outlining research memos, and translating technical accounting issues for nontechnical audiences.

Applying Professional Judgment and Skepticism to AI Outputs

1.0 Credits

This course focuses on accountability and how to practice evaluating, challenging, validating, documenting, or even rejecting AI outputs. Learners shift from using AI to evaluating it, recognizing automation bias, false fluency, and prompt-driven framing along the way.

Learners will identify biased prompts, apply the AI Accountability Loop, identify common reasoning traps, classify AI uses by validation need, and distinguish prompting tactics from independent validation.

Reviewing AI-Assisted Work

1.0 Credits

Learners practice reviewing AI-assisted work for support, validation, documentation, and ownership while identifying when AI changes the review approach, when escalation is needed, and how to ask stronger reviewer questions.

Hands-on activities have learners apply reviewability tests, identify high-risk workpaper gaps, select stronger reviewer questions, rewrite coaching feedback, and determine when escalation is needed.

AI in Client Environments

1.0 Credits

This course shifts from the accountant or auditor's use of AI to the client's use of AI, where learners examine how client AI use may affect risk, controls, estimates, evidence reliability, walkthroughs, and documentation.

Learners will generate walkthrough questions, identify AI entry points in client processes, match AI-related risks to controls, rank evidence reliability, and spot red flags in estimates and management judgments.

Integrating AI into the Engagement Lifecycle

1.0 Credits

In the Capstone course learners integrate what they learn into a structured, repeatable approach to use AI across the engagement cycle.

Hands-on activities have learners build guardrails within an AI use register, place AI uses within the engagement lifecycle, classify risk, select practical team guardrails, sequence corrective steps, and apply a final checklist before relying on AI-assisted work.