CPA firms recognize the importance of artificial intelligence, but the challenge lies in its effective implementation. FloQast’s 2026 research reveals a significant gap: while 85% of accounting teams consider AI a strategic priority, only 10% utilize it extensively. This disparity highlights the need for an AI adoption playbook that focuses on human behavior as much as technology.
AI in Accounting: From Pockets of Success to Firmwide Adoption
AI is already integrating into accounting workflows. A 2026 CPA.com and Blue J survey of over 1,000 tax professionals found that 60% use AI-powered tax research weekly, up from 33% the previous year. This rapid adoption demonstrates the potential for AI tools that solve specific problems and align with professionals’ work.
However, scaling successful AI pilots across tax, audit, advisory, and firm operations presents challenges. Middle-market research identifies barriers like data quality, integration, security, and workforce readiness.
Addressing Resistance: Beyond Training
Firm leaders often attribute uneven adoption to a lack of training. While training is essential, employees frequently understand the technology enough to form emotional judgments about its impact.
One group fears economic displacement. If employees believe AI will eliminate jobs, leadership’s enthusiasm can be perceived as threatening. RSM’s 2026 Middle Market AI Survey found that 85% of respondents reported greater enthusiasm for AI among executives than employees. This gap makes firmwide adoption a trust issue before it becomes a skills problem.
Firms should, when credible, commit to using AI-driven productivity gains for growth, client service, higher-value work, and redeployment rather than immediate headcount reduction. They should also emphasize that professionals who learn to supervise AI, test its output, and use it responsibly become more valuable as workflows evolve.
Another group perceives AI as a threat to their professional identity. Accountants have honed expertise in research, analysis, writing, review, and judgment. When AI performs these tasks rapidly, emphasizing efficiency can overlook their concerns about the value of their expertise.
A more effective approach involves involving professionals in workflow redesign. Firms should identify repetitive, low-value tasks, areas requiring judgment, and where human interaction benefits clients. CPA Practice Advisor stresses the importance of focused use cases, clear oversight, and tying AI learning to real engagement scenarios. These practical guardrails help professionals see AI as a tool that removes friction while allowing them to focus on exceptions, recommendations, and client interactions.
Clarity and Governance: Making Responsible Use the Easy Choice
Ambiguity surrounding AI usage can lead to “shadow AI”, where employees experiment with unapproved tools. CPA Practice Advisor reported that one-third of professionals in accounting, law, and compliance used AI without organizational approval, with higher rates among those perceiving slow adoption.
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Firms need clear, actionable rules for AI use. They should:
- Name approved tools.
- Define permissible data for AI input.
- Specify when outputs require verification or review.
- Outline tasks that require human judgment.
- Establish an escalation process for uncertain cases.
This governance framework empowers teams to use AI responsibly while maintaining visibility, accountability, and review. It aligns with professional obligations like Circular 230, which sets standards for tax professionals practicing before the IRS.
Creating an environment where employees feel safe expressing uncertainty about AI outputs is essential. Amy Edmondson’s research on psychological safety highlights its importance in supporting learning behaviors, such as speaking up and discussing errors during AI experimentation. This allows managers to provide guidance and ensure accuracy before outputs reach clients.
Peer Influence and Measurable Change
Firmwide adoption relies on more than just policies. Peer influence plays a significant role. Seeing respected colleagues successfully integrate AI into familiar workflows is more persuasive than vendor demonstrations.
Firms should select peer champions based on credibility and understanding of the work, not just enthusiasm. These champions should demonstrate both the benefits and limitations of AI within real workflows and provide feedback to leadership.
Managers must reinforce desired behaviors through performance reviews. Discussions should focus on how AI was used, its effectiveness, verification processes, and areas for improvement. This integrates AI use into the firm’s learning culture.
Measuring success goes beyond tracking licenses, logins, and training attendance. Thomson Reuters’ 2026 AI in Professional Services Report highlights the need to assess whether AI is embedded in targeted workflows, if outputs are verified, how review corrections change, and how saved time is utilized. Pulse surveys can gauge employee confidence in using approved tools, understanding data restrictions, and feeling safe reporting AI-assisted drafts that need revision.
The goal is to support a system where experimentation is encouraged, mistakes are identified early, and successful practices are shared. This approach is reflected in industry recognition for firms that combine AI deployment with governance and tangible outcomes.
CPA firms face pressure to adopt AI quickly, but speed without considering human behavior leads to inconsistency. A practical approach addresses resistance, clarifies expectations, leverages peer influence, and measures real change. This transforms AI from isolated experiments into a firmwide capability.
