Beyond the Chatbot: What It Actually Takes to Deploy AI Safely in Your Firm
General AI chatbots are everywhere in accounting firms today, approved or not, but they hit a wall fast: every new conversation means rebuilding context from scratch, and every upload is a judgment call about security.
This session breaks down the real difference between general-purpose AI and a platform-native system built with firm data already in context, including what recent IRS guidance means for how firms should be reviewing AI-assisted work.
We’ll ground the discussion in a live look at Coworker, Canopy’s native AI execution layer, and the human-in-the-loop framework that keeps your team in control of every output before it reaches a client.
Learning Objectives
By the end of this course, participants will be able to:
- Identify the limitations of general-purpose AI tools when handling firm and client data
- Differentiate the security tradeoffs between connecting outside AI to client data via API versus a closed, platform-native system
- Understand how recent IRS guidance on AI use affects review requirements for AI-assisted work
- Apply a human-in-the-loop review framework, from always-allow to review-required, to reduce risk in AI-assisted workflows
- Explore practical, firm-wide automation use cases, including file routing, scope creep detection, and client
Ready to get started?
Your future self will thank you.