M&A attorneys can use AI as a comparison assistant: give it a controlled, approved set of execution documents and expected closing requirements, ask it to flag candidate differences, and have a designated lawyer verify each exception against the source documents. Useful flags include a missing signature page, a party or entity mismatch, a changed signer capacity, inconsistent document versions, and an absent attachment. The workflow should preserve a source-of-truth checklist, record document versions and permissions, and stop when the tool cannot reliably distinguish a true discrepancy from formatting noise. AI should not authenticate a signature, decide legal validity, authorize release, or replace professional judgment. The output should be a reviewed exception list with evidence links, disposition, and responsible reviewer.
Define reconciliation before opening an AI tool
Start by defining the operational question. The task is not whether a signature is genuine or whether a document is legally enforceable. The task is whether the expected execution set appears to match the files received for closing, and which differences need lawyer review. That boundary prevents a document-comparison exercise from being presented as a legal conclusion.
Write the expected set in a checklist that names each document, party, signer, capacity, exhibit, attachment, and required version. Include the expected number of signature pages only when the transaction record establishes that number. Identify the accountable human reviewer, usually the deal lawyer or another lawyer with authority over closing deliverables. The reviewer owns the final disposition of every flagged item.
Choose the source of truth and preserve versions
A comparison is only as reliable as the records selected for comparison. Designate the approved source-of-truth package, such as the latest execution checklist, the circulated signing version, and the closing deliverables register. Record the file name, version or date, document type, parties, and whether it is an expected template or an executed return. Do not silently mix a draft with an execution version because the text looks similar.
For each returned file, record its receipt location and the version used in the comparison. Keep the original file unchanged. If a PDF contains several signature pages, map each page to its agreement and signer rather than assuming page order is meaningful. A simple manifest makes it possible for the reviewer to reproduce the comparison and explain why a file was included or excluded.
Control confidentiality, access, and tool permissions
Before uploading any representation-related material, review the AI tool's terms of use, privacy policy, retention settings, access model, and reuse of inputs and outputs. ABA Formal Opinion 512 explains that lawyers need a reasonable understanding of the benefits and risks of technology used in a representation, and it identifies confidentiality concerns when representation-related information is entered into some generative AI tools [1]. The opinion also points lawyers to the tool's contractual and privacy terms rather than assuming that a generic setting provides the needed protection.
Use the least amount of information needed for the comparison. If a tool can compare page images, text extracts, or document identifiers without receiving the complete matter file, consider that narrower option. Apply the engagement terms, client instructions, applicable professional-conduct rules, protective orders, and firm policy. Where the intended use raises a consent question, obtain the advice and approval required for the matter and jurisdiction before processing the files. Access should be limited to the assigned matter team, and the AI output should not be treated as a new authority to share documents.
Ask for candidate discrepancies, not a closing decision
The prompt or comparison specification should describe the fields to inspect and the output format. Ask for candidate discrepancies in party names, entity suffixes, signer names, signer capacity, document title, document date, version identifiers, page sequence, blank or missing signature blocks, exhibits, and attachments. Ask the tool to quote or point to the relevant page and to distinguish an observed difference from an inference. Require an explicit unknown or unable-to-compare result when the file is scanned, incomplete, password protected, illegible, or outside the approved set.
Do not ask the tool to state that a signature is authentic, that an agreement is effective, that a condition to closing is satisfied, or that a document may be released. Those requests turn a bounded comparison into an unsupported legal or operational decision. A useful output says, for example, that the expected attachment is listed in the checklist but no matching attachment was found in the supplied package. It does not say that the closing must be delayed or that the missing item is legally material.
Test the comparison with known exceptions
Before using the workflow on a live closing, run it on a controlled sample containing deliberately known differences. Include a changed signer capacity, a missing page, a renamed entity, a different document version, an attachment that is present under a different file name, and a formatting-only change. The point is not to produce a performance percentage. It is to see whether the output exposes the differences the reviewer cares about and whether it creates distracting false positives.
Set stopping criteria in advance. Stop the pilot if the tool invents a document or attachment, repeatedly confuses page order, fails to identify a known missing page, cannot preserve document references, or exposes data outside the approved permission boundary. Also stop if reviewers cannot reproduce a flag from the cited source page. Reconfigure the process, use a narrower tool, or revert to manual comparison. Do not expand the scope merely because the initial output appears plausible.
Use a structured exception list for lawyer review
Convert candidate findings into an exception list with at least these fields: item identifier, expected record, received record, discrepancy type, source-page references, AI observation, human verification, disposition, reviewer, and review date. Useful dispositions include confirmed discrepancy, explained difference, duplicate flag, unable to verify, and escalated for transaction-team decision. Keep the AI observation separate from the lawyer's conclusion so later readers can see what the tool actually reported.
The reviewer should open the original expected and received documents, compare the cited pages, and check related schedules or attachments. For a signer-capacity flag, verify the expected capacity against the approved transaction record rather than guessing from a signature image. For a missing attachment flag, search the controlled closing package and record the search boundary. For a version flag, compare the operative document identifier and revision history where available. Each exception should end with a human disposition, not an automatic pass or fail.
Document human oversight and retain the audit trail
Retain the comparison specification or prompt, the input manifest, tool and model version if available, output, reviewer comments, and final exception list under the matter's records policy. NIST's Generative AI Profile says that generative AI use may warrant additional human review, tracking, documentation, and management oversight, and it recommends documenting data provenance, versions, human oversight roles, and sensitive-data considerations [2]. NIST's broader AI Risk Management Framework is voluntary, but it provides a useful governance reference for incorporating trustworthiness considerations into the use and evaluation of AI systems [3].
Record what the workflow did not assess. For example, it may compare text and page structure but not determine whether a signer had authority, whether a condition was waived, or whether a signature was applied by the named individual. A short limitation statement reduces the risk that a later user mistakes a reconciliation record for an authentication report or legal opinion.
Make the closing decision outside the AI workflow
After review, the responsible lawyer decides which exceptions require correction, confirmation, escalation, or no further action under the transaction's governing documents and instructions. The AI tool should not contact counterparties, negotiate a cure, approve a waiver, authorize release, or send a closing communication. If outreach is needed, the authorized matter team should prepare and approve it through the usual process.
The practical deliverable is a reviewed execution-set exception list. It should let another lawyer identify the expected record, inspect the received file, understand the discrepancy, and see who made the disposition. Acquivo is a software platform that delivers the entire sell-side M&A process, valuation, marketing materials, buyer matching, and deal management, on one platform for business owners, M&A attorneys, and boutique investment banks. In this workflow, software remains user-operated: the attorney controls the records, permissions, review, and closing decision.
Key Points
- Define reconciliation as a comparison of expected and received closing materials, not signature authentication or a legal-validity determination.
- Use an approved source-of-truth checklist and preserve document names, versions, pages, parties, signer capacities, exhibits, and attachments.
- Review confidentiality, retention, access, client instructions, and applicable professional rules before entering representation-related information into an AI tool [1].
- Ask AI to generate candidate discrepancies with page-level evidence and an explicit unable-to-compare outcome, then have a designated lawyer verify every flag.
- Pilot with known exceptions and stop when the tool invents records, misses known differences, loses source references, or exceeds the permission boundary.
- Retain the input manifest, comparison output, human dispositions, and limitations so the final exception list is reproducible [2] [3].
Sources and references
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Educational information, not individual legal, tax, or investment advice. Consult qualified professionals for your circumstances. Acquivo provides software, not representation or negotiation on your behalf.