Responsible AI Use and Data Handling

Responsible AI Use and Data Handling Course Overview

Responsible AI Use and Data Handling equips finance and accounting professionals to use generative AI with confidence and control. Many tax, legal, and accounting professionals already use generative AI but the line between competent use and material risk is now an individual skill. Through a continuing case study, learners work through the three failure modes behind real-world incidents: truthfulness (hallucinations), security (data leakage), and sensitivity (bias), then build the practical skills to catch each one before it reaches a deliverable, a client, or a regulator. Learners leave with resources they can use the next day: a data traffic-light card, a verification workflow, and an AI decision-authority matrix.

 

Who should take this course?

This course is ideal for finance and accounting professionals such FP&A analysts, controllers, corporate development and M&A professionals, auditors, and credit and risk teams who use, or are beginning to use, generative AI in their day-to-day work. It also suits students and career-switchers preparing for finance roles where responsible, defensible AI use is fast becoming a baseline expectation.

Responsible AI Use and Data Handling Learning Objectives

Distinguish the truthfulness, security, and sensitivity failure modes in a piece of AI-assisted financial work. Apply the AI output verification workflow to catch fabricated or inaccurate AI-generated content before it reaches a deliverable. Apply the data classification framework to determine which AI tool tier is appropriate for a given piece of financial data. Evaluate an AI-supported financial decision for signs of bias or disparate impact and determine when it requires explanation, audit, or override.