AI in Accounting: Where It Helps, Hurts, and How to Use It

Western CPE Staff

AI in accounting is no longer a someday topic. In Karbon’s State of AI in Accounting report, 92% of accounting professionals say they now use AI in some form, and 85% say they are excited or intrigued by its potential. Firm employees and firms at large feel real pressure to put it to work, and it is becoming increasingly essential to firm success. It is not a question of whether to use AI. It is knowing how to use AI in your workflows, and where it can create risk if you let it run unchecked. This post walks through both sides so your firm can leverage AI’s capabilities without unnecessary risk.

How is AI used in accounting today

Modern firms apply AI across the core of daily work. The technology handles the gathering and sorting portions of a workflow, while professionals stay responsible for decision-making and execution. Common examples of how AI is used in accounting include:

Data analysis and anomaly detection. Machine learning works through large volumes of transactions, flags unusual entries, and surfaces trends a person would need hours to find.
Document extraction. AI reads invoices, receipts, bank statements, and tax forms, then converts them into structured data, cutting the manual entry that eats up early engagement hours.
Communication and summarization. Drafting and summarizing emails is consistently the most popular use case, with Karbon finding that 77% of accountants turn to AI for communication work.
Tax research. AI tools can search databases of tax guidance and surface answers for a client’s situation faster than a manual keyword search.
Audit analytics. Rather than testing a sample, AI can analyze an entire population of transactions, compare each item against historical patterns, and assign risk scores.
Workflow automation. AI can classify incoming documents, route them to the right team, update engagement status, and flag missing items or approaching deadlines.

The benefits of AI in accounting

The benefits of AI in accounting show up first as time, then as capacity. CPA.com’s 2025 AI in Accounting Report points to firms cutting time on manual tasks by as much as 70%, running review cycles for tax prep and audits up to five times faster, and serving two to three times as many clients without adding headcount. Karbon’s research puts the potential savings at roughly 21 hours per month, per employee.

Used that way, AI answers the question many staff quietly worry about. It is not replacing accountants. AI is absorbing routine work so you can shift toward higher-value advisory engagements. The firms pulling ahead are asking a sharper question: how much advisory work could they take on if routine tasks no longer filled the calendar.

Where AI can hurt you

AI systems can produce a response that reads as authoritative, uses the right terminology, and is simply wrong. This is often called a hallucination, and in professional work it is dangerous precisely because it looks credible.

Picture an AI assistant asked to summarize a revenue recognition rule. It returns a clean explanation that states the rule as an absolute, when the real standard depends on the facts. A reviewer who checks it against the authoritative guidance catches the error. A reviewer who takes it at face value carries a mistake into the workpapers, or into advice a client relies on.

Treat AI output as a draft. There should always be a human in the loop, with the accountant checking and approving the AI’s work rather than producing it from scratch. AI tools trained specifically on accounting and tax content tend to hallucinate less than general chatbots, though none remove the need for a qualified set of eyes.

Protect client data before you experiment

Accounting firms hold some of the most sensitive financial information their clients own, and AI tools introduce a new way for it to leak. In Karbon’s research, 83% of professionals said they are concerned about data security when assessing AI tools. Pasting client-identifiable details into a public AI platform can expose information you are obligated to protect, and some consumer tools feed your inputs back into their own training data.

Set clear boundaries on what data goes into which tools. Favor vetted, profession-specific platforms or private environments that keep information inside your own systems, and look for standards such as SOC 2 and privacy-by-design before you trust a vendor with client files.

How to use AI in accounting without the risk

Two things separate firms that benefit from AI from those that get burned by it: a written policy and real training.

A practical AI governance policy answers a few questions in plain terms:

Which tools are approved, and who may use them.
What data is permitted, with a firm line against entering client-identifiable information into unvetted systems.
Where AI is allowed, such as research or internal drafts, versus where it is not, such as client deliverables without review.
Who oversees it, including how output accuracy is monitored. Recognized frameworks like the NIST AI Risk Management Framework and the OECD AI principles offer a useful starting scaffold.

Training is the other half, and it is where most firms have room to grow. Karbon’s research found that only about 46% of firms actively invest in AI training, even though 85% of professionals are excited or intrigued by the technology. Teams that are trained save meaningfully more time than those left to figure it out alone. That gap is exactly where a firm can build an edge.

The bottom line

AI in accounting and finance rewards firms that already have strong judgment and strong controls. It accelerates the work your people do, but it does not take responsibility for it. Lean on AI for data analysis, document handling, research, and routine coordination. Keep professionals firmly in charge of interpretation, verification, and the final word to the client. Add a clear policy, invest in training, and AI becomes one of the most effective ways to expand your firm’s capacity without compromising the standards your reputation is built on.

Build Your Firm's AI Edge

Knowing how to put AI to work, safely and profitably, is becoming a core firm-management skill. The CPA Firm Optimization Guide by Steven M. Bragg, CPA covers AI use cases and governance alongside the rest of a modern practice: firm economics, constraint and capacity management, service line optimization, client portfolio management, and strategies for scaling.