Habits, Not Headcount: Talent Takeaways from the Boomer Circle Summit

The Talent conversations at the 2026 Boomer Circle Summit moved past training budgets and CPE hours into questions accounting firms haven’t had to answer before, like “What happens to a career path built on entry-level work when AI does that work first?” and “What do team members owe HR, and what does HR owe them, when a chatbot becomes a confidant?”

Several sessions offered answers, even if those answers aren’t necessarily comforting.

Upskilling must become a habit, not a headcount metric

Sandra Wiley, of Sandra Wiley Strategies and Consultant for Boomer Consulting, opened her session, the Rapid Upskilling Playbook, by challenging how firms measure AI progress. Most leaders track the number of licenses they buy or platforms they roll out. Wiley recommends tracking daily habits instead. Her framework moves team members through five stages, from awareness to transformation, using a crawl-walk-run structure that assigns different challenges to partners, delivery managers and individual contributors.

Wiley's four-week rollout playbook builds from individual use to team sharing to redesigning the work itself. Firm leaders need to ask what humans should stop doing and what still requires human judgment. Firms that skip this step, she said, end up with team members freelancing with AI out of curiosity rather than direction, a pattern that increases risk instead of reducing it.

What your team members are already telling AI

Marc Staut and Jacqueline Lombardo of Boomer Consulting delivered one of the Summit's most sobering sessions, What Employees Are Telling Your AI (And What That Means for Your Firm). They shared that team members increasingly treat enterprise AI tools like a trusted advisor, disclosing things they would never say to HR, because the interface feels private and judgment-free. Plus, it’s available at 11 p.m. on a Sunday.

That perception doesn’t match reality. Enterprise platforms log every prompt, response and uploaded file, and tie the record to a named employee. Retention varies by firm, and IT and eDiscovery teams can access the record. Lombardo walked through how an AI conversation can trigger ADA accommodation requirements, NLRA protections and eDiscovery obligations, even if the firm never asked for the disclosure and has no process to handle it.

They recommend attendees give each function a specific job. IT audits admin access against the firm’s written policy. HR maps who can see what before drafting new policy language. Leadership sponsors a governance review that puts both functions in the same room, rather than treating this as another acceptable-use policy refresh.

Developing early-career talent when AI removes easy work

Amy Plent, Director of Learning and Development at Withum, raised a question few firms have confronted directly in her session, Always-On Learning. What happens to career development when AI eliminates the routine tasks that used to build it? Plent noted that early, repetitive work like data entry, drafting financial statements and first-pass reviews historically served as a confidence builder and a safe place to fail. Remove that work, and what remains skews toward review, exception handling and client conversations. These tasks require judgment and emotional maturity that take years to develop.

Plent separates skill from readiness. AI can compress the time between a new hire's first day and their first advisory conversation, but the cognitive and emotional development that supports sound judgment under pressure follows its own timeline. She recommends a learning strategy based on four requirements:

1. Rapid content development

2. Learning built into the flow of work

3. Meaningful shadowing opportunities

4. Safe spaces to fail

Firms that want to measure the impact of this work need to look past CPE hours and start making judgment itself visible and assessable.

What this means for your firm

A single idea served as a connecting thread across all talent sessions. The accounting profession's advantage depends on developing team members who can use AI with judgment, and on being honest about what that development, and that trust, requires.

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