Artificial intelligence is revolutionizing forensic accounting, giving professionals powerful new ways to trace funds, uncover fraud, and analyze massive volumes of financial data in minutes instead of weeks. In this engaging course, you'll discover how AI can enhance financial investigations, strengthen expert witness reports, and support litigation and discovery efforts. Learn where AI can create strategic advantages in the courtroom, as well as the disclosure, reliability, and admissibility challenges that every expert must understand. Through practical examples and real-world applications, you'll see how AI can uncover hidden patterns, identify critical evidence, and generate actionable insights. Whether you investigate fraud, support litigation, or serve as an expert witness, this course will help you harness AI with confidence, credibility, and defensible results. 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...
- Identify artificial intelligence, machine learning, and large language models, and distinguish agentic AI from traditional generative AI tools.
- Analyze why large language models hallucinate and identify conditions under which AI-generated output may be unreliable.
- Identify practical applications of AI in damages calculations, financial statement analysis, and books-and-records reconstruction.
- Analyze reliability limitations of AI-assisted analysis, including unexplainable outputs, traceability gaps, and stale training data.
- Apply the AICPA Code of Professional Conduct’s competence and due care provisions to AI-assisted forensic work.
- Apply the reasonable-basis standard under SSFS No. 1 to conclusions supported by AI-generated analysis.
- Apply the ACFE Code of Professional Ethics to the use of AI in a fraud examination engagement.
- Identify confidentiality and data privacy risks created by inputting client data into third-party AI platforms.
- Analyze court requirements related to disclosure of AI use, including judicial standing orders and statewide policies.
- Identify disclosure considerations for attorneys and experts when AI is used in litigation.
- Analyze the discoverability of an expert’s AI prompts and outputs under Federal Rule of Civil Procedure 26.
- Determine appropriate preparation considerations for cross-examination related to the use of AI in forming an expert opinion.
- Analyze the evidentiary framework governing AI-generated evidence, including FRE 702, proposed FRE 707, and proposed FRE 901(c).
- Apply a documented, human-in-the-loop verification protocol to AI-assisted forensic work product.
Major Topics
The major topics that will be covered in this course include:
- AI fundamentals: how large language models work, why they hallucinate, and the distinction between generative and agentic AI
- Practical applications of AI in damages calculations, financial statement and ratio analysis, and books-and-records reconstruction
- Professional ethics under the AICPA Code of Professional Conduct, SSFS No. 1, and the ACFE Code of Professional Ethics as applied to AI-assisted work
- Court requirements for disclosure and discovery of AI use, including judicial standing orders, Federal Rule of Civil Procedure 26, and proposed Federal Rules of Evidence 707 and 901(c)
- Preparation for cross-examination on AI use, including how to build and document a defensible AI-assisted workflow.
