In part two of the conversation with Puzzle co-founder and CEO Sasha Orloff, the Accounting Technology Lab examines how accounting professionals can begin adopting artificial intelligence without abandoning their existing knowledge, systems, or professional judgment.
Orloff recommends starting with a difficult but low-risk problem rather than using AI only for trivial experiments. Accountants should remove client-identifying information, use personal or anonymized data, and practice explaining a task as clearly as they would to a highly capable new employee who lacks accounting experience. A prompt, in this context, becomes much like a detailed checklist: it defines the expected steps, safeguards, and outcome.
The discussion also distinguishes helpful AI assistance from uncontrolled automation. Puzzle’s approach allows agents to prepare work while requiring human approval before anything is posted to the ledger. Randy Johnston emphasizes that the profession does not need technology that eliminates accountants; it needs technology that makes accountants more effective.
Orloff argues that firms creating a safe culture of experimentation will improve productivity, profitability, and client service. Brian Tankersley closes with a challenge to accounting leaders: become sufficiently familiar with AI to evaluate solutions intelligently, guide employees, and lead clients through change. The central message is simple—AI adoption does not require reckless transformation, but it does require action.
Key Episode Themes
- Begin with meaningful work. Testing AI on an authentic, complicated problem reveals more than asking it to perform a novelty task.
- Use low-risk information. Remove client names, confidential information, personally identifiable information, and other sensitive data before experimenting.
- Treat prompts as process documentation. AI performs better when instructions describe each step, decision, constraint, and expected output.
- Keep accountants in control. AI can draft transactions, reconciliations, analyses, and journal entries, but accountable professionals should review and approve the results.
- Create a culture of experimentation. Firm leaders should give employees permission and guardrails to explore AI safely.
- Leadership requires firsthand knowledge. Accountants do not have to adopt every AI product, but they need enough experience to distinguish practical capabilities from marketing claims.
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