Ethics in the World of AI: An Accountant’s Guide to Managing the Risks

Learning Objectives

Upon completion of this program, participants will be able to:

1. Apply prompt engineering principles to create AI queries that maintain professional skepticism and ethical accountability when analyzing complex accounting scenarios such as revenue recognition, inventory valuation, internal controls, and going concern assessments.
2. Differentiate between appropriate and inappropriate AI use cases by evaluating the 10-component AI policy framework (purpose/scope, governance, approved uses, data security, quality controls, compliance standards, internal controls, bias testing, training requirements, and incident response) against real-world financial decision-making scenarios.
3. Analyze AI-generated outputs using a structured critical thinking process (Question/Doubt, Investigate, Validate, Decide) to identify gaps, anomalies, bias, and hallucinations that could compromise financial reporting accuracy or regulatory compliance.
4. Compare the outcomes produced by AI-assisted analyses versus human professional judgment in three practical case studies (pricing decisions, automated controls testing, and financial forecasting) to determine when AI should augment versus when human expertise must override automated recommendations.

Major Topics

• Ethical challenges in AI adoption for accounting professionals, including accountability, transparency, regulatory compliance, psychological impacts, and the risks of AI-generated errors in tax and financial reporting.
• The 10-component AI policy framework for establishing governance, approved uses, data security, quality controls, compliance standards, internal controls, bias testing, training requirements, and incident response protocols.
• Professional skepticism and critical thinking techniques for auditing AI outputs, including the Question/Doubt-Investigate-Validate-Decide process for identifying hallucinations, bias, and accuracy issues.
• Prompt engineering best practices for accounting applications, with hands-on exercises covering revenue recognition, inventory valuation, internal controls assessment, and going concern evaluation.
• Risk assessment frameworks adapted from NIST for evaluating AI implementation probability and impact, including strategies for managing regulatory lag, cross-border complexity, and evolving professional standards.

Who Should Attend

This program is designed for accounting and finance professionals navigating AI integration in their organizations, including:

• CPAs and Staff Accountants who prepare financial statements, conduct accounting research, or analyze complex transactions and need to understand how to responsibly leverage AI tools while maintaining professional standards.
• Internal and External Auditors responsible for assessing controls, evaluating audit evidence, and maintaining professional skepticism when AI-generated data or automated testing is part of the audit process.
• Controllers and Financial Reporting Managers who oversee financial close processes, regulatory compliance, and the implementation of new technologies affecting financial reporting accuracy.
• FP&A Professionals and Financial Analysts who develop forecasts, perform scenario planning, and provide decision support where AI tools may assist with data analysis and predictive modeling.
• Tax Professionals who need to identify and correct AI-generated tax errors, ensure compliance with jurisdiction-specific regulations, and maintain quality control over tax advice and planning.
• Audit Committee Members and Finance Executives responsible for governance, risk management, and establishing AI policies that balance innovation with organizational integrity and regulatory compliance.

Fields of Study

Prerequisites

Participants should have a foundational understanding of accounting or finance principles and prior exposure to professional ethics concepts. Familiarity with emerging technologies, such as data analytics or artificial intelligence, is helpful but not required.

CPE Credits

Level