AI Due Diligence for Mergers and Acquisitions

AI due diligence uses artificial intelligence to review the large document sets behind a deal. In mergers and acquisitions, that means reading contracts, leases, and data-room files to extract terms, flag risks, and summarize findings far faster than manual review.

Adoption has moved quickly. Most large acquirers now use generative AI somewhere in their M&A process, and private equity firms are leading the shift because repeatable, high-volume diligence is core to how they operate.

This guide explains how AI is used across M&A diligence, what the latest adoption data shows, which tools deal teams reach for, the security risks of feeding confidential documents to AI, and why human judgment still decides the deal.

What AI Does in M&A Due Diligence

AI in M&A due diligence automates the document-heavy review work across legal, financial, and commercial workstreams. Diligence involves reviewing hundreds of contracts, leases, and disclosure documents, and that reading is where AI is applied first.

The practical uses are specific. Deal teams use AI to review and classify data-room documents, extract contract terms, flag unusual or risky clauses, and turn long files into structured summaries for the deal committee.

• Contract and lease review: extract key terms and obligations across large contract sets.
• Data-room triage: classify and organize thousands of files so nothing is missed.
• Red-flag detection: surface change-of-control, assignment, and non-standard clauses.
• Financial support: help reconcile and summarize financial and disclosure documents.
• Summarization: compress long documents into findings the deal team can act on.

How Widely Is AI Used in M&A?

AI is now mainstream in M&A, especially among the largest and most active acquirers. The adoption data from 2025 is striking and consistent across independent surveys.

Deloitte reports that 86% of surveyed corporate and private equity organizations have integrated generative AI into their M&A workflows, and 35% of adopters apply it specifically to due diligence. Bain finds that more than 60% of the private equity firms it interviewed already use at least one generative AI tool for sourcing, screening, or diligence, and that about 80% of those users report reduced manual effort.

The time savings are concrete. Bain reports that early adopters using generative AI for diligence spend about one day summarizing data where the same work used to take a week.

AI Due Diligence Tools Deal Teams Use

The tooling splits into two groups: AI contract-review platforms and AI-enabled virtual data rooms. Most deal teams end up using one of each.

On the contract-review side, Harvey, Luminance, and Kira are the names that come up most often for legal diligence, with newer platforms like Diligen and DiligentIQ, now ToltIQ built specifically for private-markets diligence. On the data-room side, Datasite and Ansarada embed AI assistants directly inside the secure deal environment so documents never leave it.

The important distinction is where the AI runs. A tool that reads documents inside a governed data room is very different, from a confidentiality standpoint, than pasting the same text into a public chatbot.

The Security Risk of AI in Deal Diligence

The biggest risk in AI-assisted diligence is confidentiality, not accuracy. Deal documents are among the most sensitive files a company holds, and where they are processed matters as much as how well.

Deloitte found that data security is the leading concern among AI adopters, cited by 67% of them. The concern is well founded: entering confidential information into a public generative AI tool can amount to disclosing it to a third party. The American Bar Association, in Formal Opinion 512, warns that lawyers must get informed client consent before putting confidential information into a self-learning AI tool.

The practical answer is to keep diligence AI inside a governed environment. That means data rooms with AI built in, or private deployments, rather than consumer tools. Our guide on keeping deal documents out of public AI tools covers the controls in detail.

Why Human Judgment Still Decides the Deal

AI does not make the deal decisions in due diligence. It accelerates the review so people can spend their time on judgment, negotiation, and advice.

Materiality calls, the meaning of a negotiated indemnity, and how a discovered liability should change price or terms are human decisions. Both Deloitte and Bain frame AI as augmenting dealmakers rather than replacing them, and the ABA guidance requires lawyers to review AI output rather than rely on it blindly.

For private equity in particular, this is the point. The value of AI is not fewer people; it is closing more deals with the same team by removing the manual reading that used to slow every transaction. The same workflow then repeats across the portfolio, including the real-estate-heavy deals covered in AI for commercial real estate due diligence.