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.
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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.
Note: No specific AI tool subscription required.
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.