14 March 2026
14
March 2026

Can AI be used in tandem with Forensic Accounting?

AI and advanced discovery software have revolutionized how attorneys handle early data review. Does that mean forensic accountants in early discovery are a thing of the past? Not so fast.

With the right tools, massive datasets can be sorted, flagged, and summarized in hours rather than weeks. But even as technology makes early discovery faster and more efficient, one truth remains: You still need the insight of an experienced forensic accountant, even (and in some ways especially) during discovery.

The Promise & The Pitfall of Technology

Modern discovery platforms can do remarkable things. They can detect anomalies in accounting data, trace missing documents, identify unusual transaction patterns, and even highlight shifts in communication tone among key employees. For litigation attorneys managing complex financial disputes, these capabilities are a game-changer.

But you, as a non-tech professional, can’t begin to understand fully how AI does what it does and what its limits are. And therein lies the rub. David A. Shargel, partner at Bracewell LLP and leader of the firm’s ePractice department, explains in Reuters how litigation attorneys using AI as some sort of magic button during discovery can get themselves into major hot water. 

“While AI seems to have permeated all facets of our lives, with society placing ever-increasing weight on its output, practitioners using AI discovery tools cannot do so blindly. Attorney ethical rules make that clear,” he explains, pointing to rules that require understanding the benefits and risks associated with technology and making reasonable efforts to ensure that the tools utilized satisfy professional obligations.

“This means that lawyers must take steps to understand how a given AI tool is making decisions, such as whether a document is relevant or not. Most AI discovery tools will provide a rationale for a given decision output — such as by pointing to a part of a document underpinning the determination — and lawyers must take additional human steps of confirming the AI prediction is correct.” 

One area under debate these days is whether AI can truly understand context. Can it spot intent, not just data deviations? While it might flag transactions that look odd, can it assess whether the irregularity reflects a timing issue, a clerical mistake, or potential fraud? That’s where the value of forensic accountants in early discovery becomes readily apparent.

Why Early Expert Witness Involvement Matters

Waiting until late in discovery to involve a forensic accountant can limit their effectiveness. At that point, key data may already have been filtered out, or time-consuming rework may be required to address overlooked discrepancies. Early collaboration avoids that risk.

When engaged early, a forensic accountant can help attorneys:

  • Define the right data universe. They can identify which systems, accounts, and timeframes are most relevant, ensuring that important financial evidence isn’t left out of the initial extraction.
  • Guide search logic and parameters. AI tools need well‑crafted prompts. Forensic accountants can help fine‑tune searches, recognize relevant details, and flag areas worth closer review.
  • Interpret red flags strategically. What looks like a simple data anomaly to software could signify a deeper financial manipulation—or nothing at all. Forensic accountants know how to tell the difference and direct the case narrative accordingly.

Can AI and Forensic Accounting be Used in Tandem?

Essentially, AI can dig through mountains of information, but a forensic accountant knows how to identify the treasure. Can the two be used in tandem? Absolutely. But engage forensic accountants in early discovery to best understand how to leverage technology for efficiency while relying on their analysis for direction and meaning. 

This collaboration also enhances the defensibility of findings. When a forensic accountant helps design and document the discovery process from the start, it’s easier to demonstrate the reliability of methods and the chain of data integrity. That’s especially critical when testimony or expert reports face scrutiny in court.


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Date 14/03/2026

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