How Should M&A Attorneys Use AI to Track Signing and Closing Checklist Items?

Approve the task and confidentiality choices before uploading records

Define the task narrowly: identify evidence that may change an existing checklist item and prepare a proposed update for review. Do not ask the model to decide whether the transaction can close. Before using live records, the matter’s supervising attorney should review applicable professional rules, engagement terms, client instructions and the proposed tool’s handling of confidential information.

ABA Formal Opinion 512, issued in July 2024, addresses competence, confidentiality and supervision under the ABA Model Rules. It calls for understanding the specific tool and evaluating disclosure risks before entering representation-related information. Those Model Rules and the opinion are not a blanket statement of governing law in every jurisdiction; counsel must check the rules applicable to the matter. [1]

Document which records may be processed, who may access inputs and outputs, retention settings, provider access and whether content may be used for training. Resolve required consent or disclosure with counsel under the applicable rules. If those questions remain unanswered, use wholly synthetic trial records instead. Removing client names alone should not be treated as approval to upload matter information. [1]

Build each checklist row around an approved requirement

Use one counsel-controlled checklist as the working source of truth for item definitions. Give each row a stable identifier, the required deliverable or action, the relevant agreement provision where applicable, the responsible functional role, the reviewing role and the evidence needed for completion. Separate signing items from closing conditions and post-closing obligations so that one milestone does not silently satisfy another.

Link the row to the approved agreement version, relevant schedules, closing instructions and authorized communications. For each proposed status, capture the evidence file identifier, version, page or clause, short supporting passage and observation time. Keep the time evidence was received separate from any stated effective date. A document title or an email subject line is not enough to establish which item the evidence supports.

Preserve the current human-approved status beside the AI proposal. Include an unresolved-question field and the reviewer’s disposition. NIST’s July 2024 generative AI profile recommends verifying sources and citations in generated outputs during testing and ongoing monitoring. An evidence link therefore needs to open the actual supporting record, not merely display a plausible filename. [2]

Track received, reviewed, executed, effective and released separately

Define these as operational fields, not universal legal conclusions. Received means the identified record has arrived in the approved location. Reviewed means the assigned reviewer has examined that version for the specified purpose and recorded any reservations. Receipt is not review, and a review of a draft should not carry forward automatically to a revised execution copy.

Executed should identify the document version and required signatories whose execution counsel has confirmed. Effective records counsel’s conclusion about when the instrument takes effect under its terms and applicable law. Released records the authorized instruction and the actual release action. Keep permission to release separate from evidence that release occurred. AI may surface supporting records, but it should not populate these decision fields as final determinations.

The distinction has a concrete professional precedent: a joint Law Society and City of London Law Society note from May 2009, amended in February 2010, describes certain English-law virtual signing procedures in which pre-signed pages are held pending approval of the final version and authority to attach, date and release them. This is jurisdiction-specific historical guidance, not a universal execution procedure. [3]

Add a separate condition-disposition field for satisfied, waived or unresolved, with the authorized human decision and its basis. Counsel determines the legal assessment within the engagement; the client or other entitled party makes approvals or waiver decisions within its authority. A collection of received documents must never become an AI-generated authorization to close.

Assign functional owners and restrict what each role can change

The checklist coordinator maintains row identifiers, reconciles incoming records and checks that proposed evidence links work. The responsible M&A attorney reviews contract requirements, versions and legal status. A specialist reviewer handles an assigned subject, such as tax or employment, without an AI summary substituting for that review. The client’s authorized decision-maker handles business approvals within documented authority.

Assign a release coordinator to carry out approved document-release instructions, where the matter uses that role. Record a backup role and an escalation route before the closing window. Each item should have one accountable owner even when several contributors supply evidence. Functional ownership makes it clear who must resolve a question without putting personal staff names into reusable workflow templates.

Use read-only AI access to the smallest approved source set. Let a coordinator submit proposed changes to a review queue, but reserve acceptance and release fields for the designated humans. Disable autonomous messages, disclosure, negotiation and approval actions. ABA Opinion 512’s discussion of policies, training and supervision supports defining these responsibilities rather than treating a tool subscription as sufficient oversight. [1]

Constrain AI updates to evidence and unresolved questions

A useful extraction instruction is specific: for the listed item identifiers, identify relevant evidence only in the authorized records; return the source locator, observed fact, proposed administrative status, conflicting evidence, dependency and reviewing role. Require an unknown result when the evidence is missing. Tell the model not to infer satisfaction, authority or release from a favorable tone or a general statement that everything is ready.

For an illustrative landlord-consent item, the authorized records might contain a PDF and an email saying the consent is attached. AI can propose received, point to that PDF and flag that the attachment refers to an earlier agreement date. The responsible attorney then checks the required consent against the operative transaction documents. The example describes a workflow, not a real transaction or a conclusion about any consent’s sufficiency.

Retain the original evidence and mark the proposed update as AI-assisted. Ask for a short evidence-based explanation, not a confident narrative about why closing is safe. NIST identifies fabricated content and fabricated citations as generative AI risks, so a fluent explanation cannot replace opening the record and checking its meaning. [2]

Surface conflicting versions and dependencies instead of hiding them

Check whether the cited record concerns the correct entity, item, document version and milestone. Verify page references and attachment identity, particularly when scanned documents or incomplete email threads are involved. Compare the supporting passage with nearby exceptions and qualifications. A message confirming one party’s signature should not populate every signatory’s execution field.

When sources conflict, preserve both references and send the item to the reviewing attorney. Do not let the newest timestamp win automatically: a later forwarded message may describe an older document. Keep an earlier approval attached to the version actually reviewed, then flag subsequent changes for reconsideration. Record whether the affected status is stale, disputed or awaiting evidence rather than forcing it into complete.

Represent dependencies explicitly. An illustrative release item could depend on final document approval and an authorized release instruction. The AI proposal should identify which dependency lacks evidence without deciding whether it may be waived. Require reviewers to check critical dependencies directly before accepting a consequential update. This applies NIST’s source-verification recommendation to checklist transitions; it is a recommended control, not a promise that errors will be eliminated. [2]

Run a controlled trial with clear stopping conditions

Start with synthetic records, then use approved matter records only after the confidentiality review permits it. Have the coordinator and responsible attorney establish a manually reviewed baseline. Include deliberately difficult cases: missing attachments, obsolete execution copies, partial signatures, qualified approvals and instructions withholding release. Compare the AI proposals with that baseline item by item, not only through an overall accuracy impression.

Evaluate whether every citation opens the correct source, whether the model preserves uncertainty and whether it leaves human decision fields untouched. Record rejected proposals and why they failed. NIST recommends empirical evaluation, cautions against extrapolating from narrow anecdotal assessments and includes monitoring and decommissioning when performance falls outside defined limits. Its profile supplies risk-management guidance, not a certification of the workflow. [2]

Stop the pilot immediately for unauthorized access, cross-matter content, invented evidence, an unapproved external action or a transition from receipt to satisfaction or release without human authority. Pause the affected workflow if version conflicts cannot be resolved or reviewers cannot inspect cited sources. Return to manual tracking, investigate the cause and require supervising-attorney approval before resuming. Recheck the trial when the tool, permissions or document processing changes.

Prepare a human-reviewed closing handoff

Before the signing or closing meeting, create a review snapshot showing accepted statuses, pending proposals, unresolved dependencies and items awaiting authority. The responsible attorney checks the operative conditions and document versions. The authorized decision-makers provide their approvals through the agreed channels. The release coordinator verifies the specific instruction before acting; an AI digest or a green dashboard is not that instruction.

After authorized actions occur, record the evidence of what actually happened and reconcile the checklist with the executed document set. Preserve unresolved post-closing items rather than erasing them when the transaction milestone changes. Limit each handoff to its intended recipients and keep restricted advice out of broader administrative summaries. This is a recommended operating framework, not transaction-specific legal advice; qualified matter counsel must determine applicable formalities and authority.

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.

Acquivo is user-operated software with no success fee. The workflow described here is an implementation framework, not a claim that every control is a built-in Acquivo feature. Software does not represent the client or replace counsel’s judgment. The intended result is an evidence-linked checklist whose completion and release decisions remain with authorized reviewers.