Summary
- M&A attorneys have long used technology to provide efficiencies and improve the quality of work product in M&A deals
- M&A attorneys are increasingly considering how best to integrate artificial intelligence (“AI”), and in particular generative AI (“GenAI”), in the M&A process
- AI tools present a range of possible benefits in a variety of use cases
- However, M&A attorneys should be aware of the risks of using AI—and especially GenAI—in their legal practice
Use of AI Tools in M&A Transactions
Machine learning AI tools have been used in M&A deals for several years. The primary focus of these tools has been to increase efficiency during due diligence review by, for example, identifying and extracting specific contractual provisions from documents in a virtual data room (“VDR”). However, since the advent of large language models, GenAI has broadened the potential applications of AI tools to legal practice, including on M&A deals. M&A attorneys have been grappling with how to incorporate emerging legal GenAI technology in their workflows in a manner that increases efficiency and improves attorney work product, without sacrificing accuracy or otherwise undermining client confidence, legal judgment, or compliance with professional obligations.
Emerging Uses of AI in the M&A Process
The use of AI tools is emerging in many stages of the M&A process, including for market and legal research, during the due diligence process, in negotiating and drafting transaction documents, and for deal execution. Emerging use cases for AI tools during the M&A process include:
Research
- Market Research. AI tools can be used to research industry and market trends, as well as the target company’s business, challenges, and publicly reported events.
- Legal Research. Standalone AI products or AI features built into existing online legal research tools can help expedite legal research. For example, GenAI-powered legal research tools allow lawyers to ask questions in a conversational style and receive summarized answers with citations to case law and secondary sources.
Due Diligence
- Defensive Profiles. GenAI tools can be used to analyze a target company’s public filings and produce a corporate profile, including a description of the target’s capital structure, board and management teams, and takeover defense measures.
- Contract Identification and Risk Analysis. GenAI technology can be leveraged to identify and extract specific terms (e.g., change-of-control provisions) from an agreement. Attorneys may query GenAI tools to identify specific agreements, or agreements presenting a particular risk, in a VDR.
- Summarization of Diligence Materials. AI tools can also be used to generate summaries of documents, or to assist with drafting diligence deliverables.
Transaction Documentation Drafting and Negotiation
- Drafting Assistance. GenAI tools can assist with preparing initial drafts of agreements and related transaction documents based on standard forms, precedents, and other data sources. They may also be directed to propose thematic changes (e.g., “make the purchase agreement more buyer-favorable”).
- Issues List Generation. GenAI technology can be used to prepare initial drafts of issues lists based on drafts or markups received from the counterparty to guide attorney review and negotiation.
- Market-Standard Benchmarking. AI can be used to support negotiation strategy by identifying market-standard positions and comparing the relevant transaction documents or provisions to the benchmark deal terms.
Deal Execution
- Deal-Process Optimization. AI tools can be used to summarize communications, flag open points, track action items, assist with inbox management, and other procedural tasks.
- Signing and Closing Automation. AI tools can generate signing and closing checklists tailored to the deal structure and timing. They can also assist with execution logistics, including signature page management and closing binder preparation.
Risks of Using AI Tools in M&A practice
Despite the promise of AI, M&A attorneys leveraging GenAI tools should be aware of the various risks presented by AI tools. GenAI tools are prone to making surprising errors and “hallucinations,” which may be phrased in a confident tone but are nonetheless false, misleading, or incomplete. There have been numerous instances of attorneys filing legal documents containing well-formatted case citations to nonexistent cases. AI tools may also miss important clauses or overlook hidden liabilities.
Practitioners should also consider the assurances clients and other stakeholders (e.g., representation and warranty insurers) may seek with respect to the accuracy and completeness of attorney work product (e.g., diligence summaries and reports).
GenAI products may also exhibit biases resulting from the data on which they were trained—for example, a bias in favor of publicly filed transactions, which are more readily available and therefore more commonly included in AI training datasets.
Although AI tools are improving in these regards, we still routinely observe inaccurate, incomplete, misleading or biased output from GenAI tools. Accordingly, all work produced by GenAI should be carefully reviewed by qualified lawyers.
It is also important for attorneys to understand how data provided to AI tools is used by the tools’ developers. Unless appropriate data boundaries (both legal and technical) are put in place, lawyers risk breaching obligations of confidentiality or inadvertently waiving privilege by disclosing confidential or privileged materials to AI tools. Attorneys should also consider both the accuracy limitations of GenAI and applicable regulatory or documentation retention requirements before enabling AI features that automatically summarize calls and other communications.
Additionally, legal practitioners should ensure that their use of AI tools comports with their ethical obligations, including the duties of competence and confidentiality, and remain abreast of any updated rules or guidance that directly address the use of AI for client matters.
Conclusion
AI tools, and particularly GenAI, are beginning to transform the M&A process by streamlining research, due diligence, drafting, and deal execution. Yet these benefits come with risks, including accuracy errors, biases, confidentiality concerns, and ethical obligations. Attorneys should adopt these tools thoughtfully, with rigorous human oversight and clear internal policies.
This post is based on a Sullivan & Cromwell LLP memorandum, “Use of Artificial Intelligence Tools in M&A Transactions,” dated January 12, 2026, and available here.