Diligence teams do not need AI to “read documents” in the abstract. They need faster movement from a messy data room to a defensible issue list, workstream memo, or partner summary.
A useful diligence workflow starts with the firm’s playbook: what document types matter, which clauses or terms should be extracted, which risks should be escalated, and what the final memo needs to contain.
The data-room workflow
- Classify documents by type, business function, entity, date, and relevance.
- Extract key terms from contracts, reports, policies, board materials, management files, and operating documents.
- Compare findings against the firm’s diligence checklist or risk taxonomy.
- Flag red flags, missing documents, unusual terms, and inconsistent representations.
- Draft memo-ready findings with source file, page, section, and reviewer note.
The reviewer problem
Diligence review breaks down when analysts produce summaries that partners cannot verify quickly. Source citations are not a nice-to-have. They are the difference between a useful draft and a liability.
Why custom matters
Every diligence team has a different risk lens. A private equity operating diligence team, cyber diligence team, legal diligence team, and commercial diligence team will not use the same issue taxonomy. That is why the workflow should be built around the firm’s checklist and escalation language.
The practical first pilot
Pick one document class and one memo section. For example: vendor contracts and change-of-control findings, security policies and compliance gaps, management reports and operational risk signals, or customer contracts and concentration concerns. Prove the workflow there before expanding across the full data room.
Research notes and sources
- KPMG Workbench is described as a multi-agent AI platform supporting client delivery across KPMG service lines, including advisory: https://kpmg.com/us/en/capabilities-services/ai/kpmg-workbench.html
- KPMG’s Workbench announcement says the platform underpins KPMG Digital Gateway, KPMG Velocity, and KPMG Clara: https://kpmg.com/xx/en/media/press-releases/2025/06/kpmg-launches-a-multi-agent-ai-platform-transforming-client-delivery-and-ways-of-working-across-the-global-organization.html
- DataSnipper’s audit-grade AI discussion emphasizes evidence, citations, audit logs, human review, and workflow integration as requirements for regulated verification work: https://www.datasnipper.com/resources/what-audit-grade-actually-means-ai-excel-agents