AI’s Due Diligence Applications Need Rigorous Human Oversight

Artificial intelligence is becoming a value-enhancing tool in private equity transactions. Mergers and acquisitions require meticulous due diligence to assess opportunities, risk, and compliance. The deployment of AI has revolutionized this landscape and improved speed, accuracy, and cost efficiency.

Yet wholesale reliance on AI diligence or failure to thoroughly investigate AI-generated output could give rise to common post-closing claims, including fraud, breach of representations, and diminished value of the business.

AI tools can review thousands of documents, provide concise summaries of material, analyze complex financial metrics, and operate in virtual data rooms. These positive attributes contribute to AI’s growing use in due diligence summarizing company financials, pending litigation, and M&A information extraction.

AI isn’t new to legal practice or due diligence-like exercises. Predictive coding and technology-assisted review are instructive precedent. Using technology-assisted review increases efficiency and identification of relevant documents in the discovery process.

But while AI can meaningfully assist with these tasks, it can’t replace attorney judgment in assessing risk, data bias, or pending litigation—or identify potential legal landmines.

Courts over the last few years have sanctioned lawyers for employing AI in legal research resulting in fake citations and inaccurate case law to support their position. Overreliance on AI tools creates risk when they generate “hallucinated” data leading to inaccurate assessments of the target company, increasing the likelihood of post-closing litigation.

For example, if the buyer discovers after closing that the seller materially overstated the company’s financial performance because AI didn’t assess the numbers accurately, it could lead to a material misrepresentation claim. It’s critical that attorneys understand the AI platform used and its operational scope and limitations before relying on any output to avoid inaccuracies.

Companies and law firms should vet AI vendor selection, conduct training, increase scrutiny of AI-generated results, and establish AI protocols to reduce the potential for hallucinations.

The Securities and Exchange Commission has ramped up enforcement against claims of “AI-washing” by scrutinizing companies’ public marketing materials, regulatory filings, and social media posts regarding AI. AI-washing occurs when companies seek to attract investment by mischaracterizing their AI capabilities and making false claims about the use of AI tools. AI-washing increases the risk of securities class actions brought against the company making such misstatements.

Enforcement against AI-washing must coexist with the Trump administration’s focus on championing AI development. The administration has set aside previous consent orders against AI companies regarding their products and even issued an executive order in January 2025 calling on federal agencies to avoid stymieing AI innovation, which became part of the subsequent July 2025 AI Action Plan directing reduced enforcement.

Attorneys must identify and confirm a company’s claimed AI capabilities using data-backed evidence and materials regarding their technology. A component of any due diligence should focus on the seller’s use of AI in their operations to ensure accurate reporting.

The heightened scrutiny of AI usage will continue extending to due diligence in the transactional space. For example, evaluating and assessing litigation risk is a critical part of due diligence and requires knowledge and context of pending lawsuits and the potential financial impact on business.

Any review of a proposed transaction’s underlying litigation risk must include understanding the nature of the company’s business, potential avenues for litigation, cost of defense, and verdict risk. It also must contemplate the impact of any sociopolitical issues that affect the client’s case evaluation, risk management, or posture.

AI can’t mirror the core functions performed by an attorney. The American Bar Association’s Formal Opinion 512 points out that generative AI tools “lack the ability to understand the meaning of the text they generate or evaluate its context.” Its contextual understanding is limited, as only an attorney can pick up on nuanced risks and subtle ambiguities.

AI may not recognize the impact of serial litigation, jurisdictional nuances, reputation of counsel, impact on change in product formulation, placement of warnings, competitive significance of a non-compete clause, or underreporting of disclosed litigation.

Claims for fraud, misrepresentations, breach of warranties, and issues with intellectual property can result from AI-powered tools absent sufficient oversight and verification.

Certain AI platforms are intentionally general or focused on early-stage contract platforms and trained using standard commercial contracts (non-disclosure agreements, service and vendor agreements), which only help in identifying missing standard clauses and reviewing a high volume of contracts and amendments. Such platforms will fail to detect nuances or subtle legal risks in highly specialized or niche contract provisions.

Confirming data reliability is a critical requirement, as it ensures accuracy, consistency and trustworthiness for decision-making in deals.

Post-closing claims typically arise from pre-closing issues rather than unforeseen events. Claims arise from deal structures that failed to anticipate the possible points of liability. Buyers, sellers, and counsel must reframe their views and use of AI in due diligence and avoid mistaking fluency for accuracy.

AI-enabled analytics can enhance and support the diligence process as an insightful amplifier for critical analysis—but it’s not a decision-maker.

This article does not necessarily reflect the opinion of Bloomberg Industry Group, Inc., the publisher of Bloomberg Law, Bloomberg Tax, and Bloomberg Government, or its owners.

Author Information

Jennifer L. Filippazzo is a partner at McDermott Will & Schulte whose practice focuses on complex litigation matters.

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