Prepare M&A documents for AI review
Deal materials remain sensitive even after party names disappear. Financial combinations, product details and timing may reveal a transaction, while access to a data room does not automatically authorize uploading its contents to an AI service.
For Transaction teams and corporate development operations
Synthetic example: diligence request structure
A fictional corporate-development team wants to reorganize a diligence request list. The example uses invented entities and categories and is not a live transaction, a customer story or a recommendation about valuation.
What you are working with
- An XLSX request tracker with counterparties, owners and data-room links.
- A DOCX briefing containing deal-specific commercial assumptions.
- Comments and filenames exposing the transaction codename and advisors.
A safer approach
- Create a synthetic request list with category, owner role and status fields.
- Remove deal links, actual counterparties and unnecessary commercial assumptions.
- Keep the approved review artifact separate from data-room originals and mappings.
Expected outcome: The assistant proposes an organizational structure and identifies ambiguous request wording. The deal team reviews the structure without disclosing the transaction or delegating diligence conclusions.
Work through the procedure
Confirm the sharing boundary
Identify who controls the material and which receiving environments are authorized. Define the permitted task and excerpt rather than relying on general access to the data room. If approval cannot be established, prepare a wholly synthetic request list without exporting deal content.
Separate structure from substance
For a request-list task, preserve category relationships, dependencies and status definitions while replacing real owners with roles. Omit valuations, customer concentration and deal-specific strategic assumptions unless expressly needed and approved. Reducing the task may preserve its usefulness without sharing the transaction.
Review indirect transaction clues
Inspect codenames, advisor names, filenames, document properties, comments and embedded links. Consider combinations of industry, geography and timing, not just names. Review every sheet and attachment in the prepared artifact; a short visible extract may still include a full hidden tracker.
Retain decision ownership
Ask the assistant to explain proposed grouping changes and flag missing definitions. Verify against the authorized diligence process before reuse. Do not let a formatting answer become an assertion that a diligence area is complete or a material risk has been resolved.
What to check before proceeding
1. Explicit purpose
- Ready when
- The transaction owner has approved this material, purpose and destination.
- If the check fails
- Use an invented example or keep the work inside the approved environment.
2. Deal recognition
- Ready when
- The review copy excludes unnecessary direct and indirect transaction clues.
- If the check fails
- Narrow the excerpt further; replacing entity names alone is insufficient.
3. Workflow completeness
- Ready when
- Reorganized requests preserve owners, dependencies and unresolved items.
- If the check fails
- Restore the authoritative structure and review the proposed changes manually.
Common mistakes to avoid
- A transaction codename can identify the deal just as effectively as the legal entity name.
- An assistant may remove apparently duplicate diligence questions that have different scopes or responsible reviewers.
Evaluate this workflow with Aona
Where Aona can help
Evaluate Aona's configured prompt and file policies with synthetic transaction documents. Supported DOCX, XLSX and PDF formats need verification on the chosen provider, browser or native path before operational use.
What to confirm
Aona does not infer every material non-public fact, interpret deal restrictions or authorize data-room exports. Its regional managed processing must be included in the approved data flow; it is not local-only review.
Managing this document workflow across a team?
Review your AI tool, document format and data-handling requirements. Use a synthetic example to discuss supported controls and the checks your team still needs to perform.