We know AI handles the busy work of data capture and categorization for many businesses, yet the real impact for public accounting is not only about speed; it’s about better conversation around the data.
The early adopters of AI are now beginning to use it to prepare more effectively for client conversations, strengthen audit judgment, and support higher quality advisory work. It moves the focus from processing data to talking about it. These workflows help firms grow advisory revenue per client while keeping compliance work on track. This matters most for partners and managers in public accounting firms looking to scale CAS and advisory work without adding headcount.
1. Pre-engagement simulations to anticipate client questions
Every accountant has sat in a meeting where a client asks a question that reframes the entire conversation. AI helps teams prepare for that moment.
By feeding anonymized context about a client’s situation, industry environment, and common pressure points, practitioners can ask an AI model to simulate the client’s perspective. The goal is not prediction. It is preparation.
This plays out most clearly in quarterly CAS review calls, multi-entity performance walkthroughs, and advisory roadmap discussions.
AI can highlight the questions a CFO might raise during an audit planning session, the pushback a controller might give in a variance discussion, or the clarifications a founder might request during an advisory presentation. For firms handling dozens or hundreds of clients, these simulations help teams show up more prepared and more focused.
The real benefit is clarity. AI gives immediate, structured feedback on where a memo is thin, where assumptions may be misunderstood, or which metrics deserve a stronger explanation. For junior staff, it builds judgment. For senior teams, it sharpens the narrative before the client ever sees a slide or report.
Best used for:
Audit planning discussions
Advisory proposals and presentations
CAS insights and monthly review calls
Preparing junior accountants for client-facing conversations
Keep it safe:
Only use anonymized information, avoid any client-identifiable data, and work inside firm-approved tools with clear governance policies.
2. AI supported anomaly detection across high volume client data
Fraud, error, and unusual activity often sit in small details. Public accounting teams, especially those working with many clients at once, use AI to scan large transaction sets for patterns that deserve a closer look. It gives both auditors and CAS teams a shared starting point for where attention, testing, and follow-up should concentrate.
This is not about replacing auditors or judgment. It improves coverage. AI can surface vendor behavior that looks unusual, expense claims that do not match history, approval sequences that break policy, or transactions that fall at odd intervals. These are areas an auditor or CAS practitioner would investigate anyway. AI brings them to the surface faster.
Financial institutions have used similar technology for years. Banks now rely on real time decisioning engines that score billions of transactions and identify high risk activity. The same concept is becoming available in the tools public accounting teams use, especially across AP, expense, and workflow software.
For firms with growing CAS practices, this is particularly useful. An AI model can screen transactions across multiple clients and flag exceptions without requiring each practitioner to sift through thousands of lines manually.
Best used for:
Audit risk assessment
Substantive analytical procedures
Quarterly or monthly CAS reviews
Identifying potential segregation of duties issues
Detecting unusual patterns before they become engagement findings
The key point is consistency. AI looks at every transaction the same way, which helps teams spend time where professional judgment matters most.
3. Scenario forecasting to support advisory conversations
Volatile economic conditions have made forecasting harder for clients and more central to the work accountants do. AI supported scenario modeling helps practitioners run multiple what if cases quickly, combining client financials with external factors such as supply chain shifts, regulatory changes, or cost volatility.
For CAS and advisory teams, this becomes a core part of planning conversations. Instead of presenting a single forecast, practitioners can walk clients through how their cash position would react under several plausible paths. The insight is not the prediction itself. It is the range of outcomes and the operational decisions that follow. This directly improves client preparedness for board and lender questions that often escalate back to the firm under pressure.
Large financial institutions already see the benefit. Some use AI powered cash flow tools that have reduced manual work by nearly 90 percent across thousands of corporate clients. Public accounting teams can borrow this approach and apply it to client advisory, budgeting support, and board presentations.
Best used for:
Advisory engagements
CAS forecasting cycles
Budget planning sessions
Evaluating liquidity under different risk conditions
4. AI driven control testing to strengthen internal control insights
Public accounting teams spend significant time assessing controls. AI helps firms pressure test these controls before any formal audit work begins.
By modeling anonymized workflows such as approval chains, spending permissions, or role combinations, teams can ask AI to identify theoretical weaknesses. This exposes gaps in segregation of duties, delegation of authority, and other areas that may lead to errors or fraud. It is not a replacement for an audit. It is an early stage diagnostic tool that helps teams focus their procedures more precisely. Clearer audit walkthroughs raise the quality of evidence, and the associated control gaps provide a direct path into remediation and advisory projects.
This also helps advisory and CAS teams who build or review client processes. AI can test edge cases such as what happens when two roles overlap or when thresholds interact in unexpected ways. Once the vulnerabilities are visible, firms can help clients redesign their controls accordingly.
ApprovalMax conducted internal research and found that only one in four businesses has strong financial controls in place. This means most clients benefit from a more rigorous conversation about workflows, permissions, and operational safeguards.
Best used for:
Audit planning and walkthroughs
Controls advisory
CAS process design
Identifying SoD and approval gaps before they become findings
Strong foundations before smart workflows
AI only performs as well as the processes and data it is built on. For public accounting firms, this means working with reliable source data, clear engagement documentation, and well understood client workflows. It also means respecting firm level governance, anonymizing any sensitive information, and using approved tools that meet professional and regulatory standards.
Once these foundations are in place, AI becomes a catalyst for better insight and better client service. It helps practitioners ask sharper questions, detect issues earlier, and support clients with more informed analysis. At the firm level, that translates into more capacity per team and better leverage across the same headcount.
Public accounting is built on judgment, rigor, and trust. AI does not replace those values. It expands the tools firms can use to deliver them. In the next few years, the firms that win will be the ones that treat AI as a partner in judgement, not a shortcut around it.
Dan Schonfeld is the Chief Financial Officer at ApprovalMax. A former lawyer and management consultant turned finance leader and board member, he has led budgeting and BvA processes across multi-entity software companies in eight geographies, with a focus on building pragmatic FP&A foundations on Xero.