Artificial intelligence is rapidly transforming the way legal professionals work—enhancing efficiency, improving accuracy, and enabling better outcomes for clients. Over the past several years, we have successfully integrated AI tools into mergers and acquisitions transactions and other legal engagements. This Legal Update highlights seven of the most practical and impactful applications of AI in legal practice, particularly in the areas of comparison, research, summarization, organization, drafting, and review.
1. Preparing Due Diligence Request Lists: AI can streamline this process in several ways:
- Drafting: Start by asking the tool to generate an initial draft based on precedent.
- Benchmarking: Next, have it review other precedents to identify additional extracts for consideration.
- Customizing: Ask it to suggest content or revisions based on the specific industry or deal context.
- Refining: Finally, request a review of your near-final draft to (i) suggest ways to consolidate and organize requests, and (ii) flag any additional items you may want to include.
2. Negotiating NDAs: This use case requires a strong foundation—specifically, a negotiation playbook with your standard and fallback positions, supported by sample provisions. For example, if your standard confidentiality term is 24 months, but you are willing to go down to 18 months for certain strategic bidders, that should be built into the playbook. With this framework in place, the tool can review bidder markups and apply your rules automatically to produce an initial draft of a markup, saving significant time and reducing risk of oversight.
3. Contract Diligence: Contract review is one of the earliest and most widely adopted AI applications in M&A. Whether for buy-side due diligence or sell-side disclosure schedule preparation, tools can identify key provisions such as change-of-control and assignment clauses and summarize relevant or other commercial terms in your preferred format. To go further, consider asking the tool to (i) compare terms across multiple agreements to identify “market” standards within the group, or (ii) catalog agreement features for future reference (e.g., organizing termination rights chronologically).
4. Preparing Executive Summaries of Diligence Findings: You can leverage AI to draft the initial executive summary of a diligence report, as well as highlight issues in the report that may warrant special indemnities. From a sell-side perspective, you can prompt the tool to flag issues in draft disclosure schedules that could raise concerns for a purchaser, thereby helping you anticipate follow-up requests and manage messaging proactively.
5. Analyzing a Purchase Agreement: AI can add value at multiple points in the negotiation process:
- Precedent Analysis for Term Sheet/LOI Preparation: Analyze similar agreements to draft and/or inform your term sheet or LOI.
- Generate an Issues List: Review a purchase agreement markup and generate an issues list to confirm nothing is missing in your own issues list.
- Key Terms Summary: Prepare a summary of key terms in the purchase agreement for internal approvals, including identification of unusually buyer- or seller-favorable provisions, or any provisions of particular importance to management.
6. Drafting a Closing Checklist: Ask the tool to draft an initial closing checklist. You can also ask the tool to review your existing checklist (whether AI-generated or not) against the purchase agreement to identify missing items.
7. Preparing Resolutions and Consents: With the right precedents and understanding of the relevant governance structure, AI can generate initial drafts of board or shareholder resolutions and written consents.
AI does not replace legal judgment. As an LLM stated when I queried a few ways of communicating my core message, “AI imitates the process of thinking without truly understanding or originating ideas.” Or, “AI performs a convincing imitation of thinking, but it’s fundamentally derivative.” That is why experienced lawyers remain essential in M&A - to bring judgment, nuance, strategy, risk assessment and bespoke structuring to the process. But AI can amplify our ability to deliver precision, speed, and value to clients. The key is to use these tools thoughtfully, and always within a framework that ensures accuracy, compliance and confidentiality.
