This course provides a concise overview of the AI Decision Governance System (AI-DGS), a pre-flight decision framework that helps accountants stress-test AI-influenced work before it is signed, sent, released, or relied upon. Participants learn how AI redistributes judgment through fluent narrative, how liability now moves faster through language than numbers, and why traditional controls miss the “moment of reliance.” Using the aviation checklist metaphor, the course shows how to operationalize repeatable cockpit discipline across everyday artifacts (emails, memos, advisories, and press releases). Learners will apply a six-layer governance lens—representation integrity, judgment ownership, capability integrity, velocity, drift, and assurability—supported by practical “Gem” workflows and the Human Judgment Record. The emphasis is not on using AI better, but on governing AI-shaped conclusions so they remain human-owned, defensible, and replayable under scrutiny.

Topics Covered:

• The “Quiet Shift” and why AI became a governance condition

• Narrative risk vs. numerical risk in professional deliverables

• AI-DGS Quick Start and the Human Judgment Record

• Six-layer cockpit lens: representation, ownership, capability, velocity, drift, and assurability

• Caloric vs. structural work and cognitive atrophy risk

• Documentation trails as “flight data recorders” for defensibility

• Scaling AI-DGS across artifacts and high-stakes releases

Target Audience:

Accountants, auditors, tax professionals, and finance leaders who use (or review) AI-assisted outputs and need a defensible governance protocol before others rely on their work.