Start From Trust: An Evidence-Based Approach to AI Adoption

Description

AI is now built into software that CPA firms already use, and the pressure to have a position on it keeps rising. For most small and midsize firms the question is not whether these tools matter, but how to engage with them on terms that fit a practice built on trust, confidentiality, and professional judgment.

This course makes an evidence-based case that professional skepticism is an asset in technology decisions, provided it is aimed at the right target. Drawing on research in trust calibration, human and AI decision making, cognitive offloading, and professional identity, it examines why experienced professionals discount sound algorithmic advice, what that discounting costs in accuracy, and where reasonable caution turns into accidental delay. Participants locate their firm on the AI Trust and Usage Quadrant, apply five trust questions to vendor claims, and review bounded first steps designed to protect independent judgment during a pilot. The course is vendor neutral and recommends no product.

This event may be a rebroadcast of a live event and the instructor will be available to answer your questions during the event.

Objective

After attending this presentation, you will be able to... Distinguish calibrated trust from overtrust and undertrust, and identify the professional judgment risks each one creates. Identify a firm's current position on the AI Trust and Usage Quadrant and the governance implications of unstructured tool use already occurring inside the firm. Apply five vendor trust questions covering permission, uncertainty, audit trail, explainability, and change control to evaluate an AI-enabled product. Select bounded first steps and rollout rules that protect independent professional judgment during a technology pilot.

Attendee Information

Leeland Rogers, Ph.D.

Required Knowledge

None

Who Should Attend

Partners, firm leaders, and practitioners at small and midsize CPA firms, along with anyone who has a say in the firm's technology decisions. No technology background is needed.