What is AI due diligence?
AI due diligence is the use of artificial intelligence to review, extract, analyze, and summarize documents, data, and risks during financial, legal, commercial, and operational due diligence.
It is also referred to as AI-powered due diligence or automated due diligence.
AI due diligence helps teams process large document sets more quickly by automating tasks such as document ingestion, data extraction, contract analysis, KPI detection, and risk identification.
What AI due diligence includes
AI due diligence systems typically support:
- Document ingestion and extraction: Reading PDFs, scans, spreadsheets, and structured files
- Summarization: Producing concise summaries of documents, folders, or entire data rooms.
- Contract clause detection: Identifying key terms such as renewal, termination, indemnification, or change-of-control
- Risk flagging: Highlighting anomalies, inconsistencies, or potential exposure areas
- KPI extraction: Pulling metrics such as revenue trends, customer concentration, churn data, and margin patterns
These capabilities help analysts review large datasets faster and with more consistency.
How AI due diligence works
Although different platforms use different technologies, most AI due diligence workflows follow the same basic steps:
- Ingest documents: The system receives PDFs, spreadsheets, scanned files, data-room folders, or structured exports.
- Classify files: AI identifies document types — financial statements, contracts, HR records, customer lists, tax returns, litigation documents, etc.
- Extract data: Using machine-learning models, the system pulls relevant data points, contract clauses, and quantitative metrics.
- Summarize and flag risks: AI produces summaries, highlights key findings, detects patterns, and surfaces anomalies.
- Provide structured outputs: Outputs typically include tables, summaries, clause lists, trend analysis, or folder-level digests.
- Human review: Analysts validate the findings, interpret context, and make final decisions.
AI accelerates the manual review process but does not replace expert judgment.
Where AI due diligence is used
AI due diligence is used across a wide range of deal and evaluation processes, including:
- M&A transactions
- Private equity diligence
- Venture capital reviews
- Corporate development evaluations
- Lender reviews and risk assessments
Any workflow that requires synthesizing large volumes of documents benefits from AI support.
Benefits of AI due diligence
AI brings four key advantages to traditional diligence workflows:
Speed: AI can process thousands of pages in minutes, accelerating early-stage and late-stage reviews.
Accuracy: Automated extraction reduces manual errors and increases consistency across deals.
Scale: Teams can review more documents, more thoroughly, without adding headcount.
Risk coverage: AI surfaces risks that are easy to miss in long documents or messy file structures.
Limitations of AI due diligence
AI improves efficiency, but it has important constraints that users must understand:
Data quality dependence: Scanned or low-quality documents can reduce extraction accuracy.
Need for human oversight: Analysts must validate AI outputs, especially in financial or legal contexts.
Potential misclassification: Document types or clauses may occasionally be misidentified.
Governance requirements: Organizations must maintain auditability, version control, and clear review procedures.
AI due diligence FAQs
What documents can AI review?
AI can review financial statements, contracts, tax filings, customer lists, HR files, operational reports, litigation documents, commercial data, and most structured or unstructured files.
How accurate is AI due diligence?
Accuracy varies by file quality, document type, and model sophistication. High-quality PDFs and structured files produce the best results. Human review is still required.
Can AI replace human due diligence?
No. AI accelerates document review and surfaces insights, but analysts are responsible for interpretation, judgment, and decision-making.
Does AI work with virtual data rooms?
Yes. AI can ingest complete data-room folders, classify documents, and produce folder-level or file-level summaries.
See how F2 automates the due diligence process for private market investors.