How to Use AI for Due Diligence: A Practical Guide for M&A and Legal Teams
In mergers, acquisitions, financing rounds, and other high-stakes transactions, due diligence is essential. It helps teams uncover material facts, identify risks, and confirm whether a deal is worth pursuing. But traditional due diligence is often slow, manual, and resource-intensive.
AI is changing that. For legal professionals, M&A advisors, and in-house teams, AI can help review documents faster, surface risks sooner, and reduce the burden of repetitive analysis. Used well, it does not replace human judgment. It supports it.
Why AI Matters in Due Diligence
Due diligence often involves large volumes of contracts, emails, reports, financial records, and compliance materials. Manually reviewing all of that takes time and increases the risk of missed issues.
AI helps by:
- processing large document sets quickly
- identifying patterns, anomalies, and missing information
- extracting key clauses and data points
- reducing repetitive review work
- helping teams focus on strategic analysis rather than manual screening
For law firms and legal departments, this can mean faster turnaround, better issue spotting, and more efficient use of senior time. It can also improve consistency across reviews, especially in large transactions.
Best AI Tools for Streamlining Due Diligence
Several AI-powered platforms can support different parts of the due diligence workflow. The right choice depends on your use case, document volume, and budget.
1. Luminance
Luminance is an AI-powered legal transaction platform built for reviewing large volumes of legal documents. It uses natural language processing and machine learning to identify key clauses, risks, and deviations from standard terms.
What it does:
- reviews thousands of documents quickly
- flags clauses, obligations, and anomalies
- highlights provisions such as change of control, indemnities, and force majeure
- helps teams compare terms across multiple agreements
Why it is useful:
Luminance reduces the time spent on manual contract review and helps identify issues that may be missed in a traditional review process.
Best fit:
- M&A transactions
- real estate due diligence
- large-scale contract review
Pros:
- fast and accurate
- user-friendly
- strong at identifying inconsistencies across documents
Cons:
- premium pricing
- focused mainly on legal document review
2. Kira Systems (now part of Litera)
Kira is another AI platform designed for contract analysis and due diligence. It is especially useful for extracting specific provisions and data points from legal documents.
What it does:
- extracts clauses, dates, parties, renewal terms, liabilities, and other key data
- supports diligence checklists and issue spotting
- can be trained to identify custom clause types
Why it is useful:
Kira automates the extraction of information that teams would otherwise need to find manually, which can save substantial time in large transactions.
Best fit:
- M&A due diligence
- commercial real estate
- contract portfolio review
Pros:
- strong accuracy
- customizable clause identification
- useful reporting features
- integrates with other legal tech tools
Cons:
- learning curve for new users
- best suited to contract analysis rather than broader diligence needs
3. Relativity
Relativity is a leading e-discovery platform with AI features that can also support due diligence. It is well suited to large, complex data sets.
What it does:
- uses technology-assisted review and clustering
- organizes and categorizes documents
- surfaces likely relevant materials
- helps teams manage large volumes of unstructured data
Why it is useful:
Relativity makes large document collections more manageable and can significantly reduce the time spent on manual review.
Best fit:
- large legal matters with a due diligence component
- regulatory investigations
- large-scale document review
Pros:
- scalable
- strong analytical capabilities
- handles diverse data types well
Cons:
- can be complex to administer
- better for relevance review than clause extraction
4. Everlaw
Everlaw is another e-discovery platform that uses AI to streamline document review and analysis.
What it does:
- clusters similar documents
- supports predictive coding
- helps prioritize review of relevant materials
- highlights patterns and inconsistencies
Why it is useful:
Everlaw helps legal teams move faster through large data sets and identify important information earlier in the process.
Best fit:
- complex litigation with a diligence component
- regulatory reviews
- large unstructured document sets
Pros:
- intuitive interface
- strong collaboration features
- effective for relevance review
Cons:
- less specialized for detailed clause extraction than contract-focused tools
5. Crayon
Crayon is not a legal due diligence platform, but it can support market and competitive analysis during a transaction.
What it does:
- monitors company websites, news, social media, and industry sources
- tracks competitor activity
- identifies market trends and positioning
Why it is useful:
Strategic due diligence often requires a clear view of the market landscape. Crayon can help teams understand competitive risks, opportunities, and potential synergies.
Best fit:
- M&A strategic due diligence
- market entry analysis
- competitive intelligence
Pros:
- broad view of the competitive landscape
- automated market monitoring
- useful strategic insights
Cons:
- not designed for legal document review
- should be paired with other tools for full due diligence coverage
6. AuditBoard
AuditBoard is a cloud-based platform for audit, risk, and compliance management. While it is primarily used for internal audit and SOX compliance, it can support operational and financial due diligence.
What it does:
- organizes audit and risk workflows
- tracks controls and compliance efforts
- helps assess internal control environments
Why it is useful:
For financial or operational due diligence, understanding a target’s control environment and risk management processes can be critical. AuditBoard helps structure that review.
Best fit:
- operational due diligence
- financial control assessment
- regulated industries
Pros:
- structured risk and control workflows
- strong collaboration features
- useful for compliance-oriented reviews
Cons:
- geared toward internal audit
- not built for legal document review or deep financial analysis
How to Choose the Right AI Tool for Due Diligence
The best tool depends on what kind of due diligence you are running and what you need the AI to do.
Consider the following:
- Nature of the review: Are you focused on legal contracts, financials, market research, or operational controls?
- Volume of data: Large document sets may require e-discovery platforms like Relativity or Everlaw.
- Type of AI capability: Do you need clause extraction, predictive coding, pattern detection, or market monitoring?
- Workflow integration: The tool should fit into your existing legal tech stack and review process.
- Budget and ROI: Compare the cost of the tool against the time saved, risk reduced, and efficiency gained.
- Ease of use: Some platforms are intuitive, while others require more training and configuration.
In many cases, a single tool will not cover everything. A legal team might use Luminance or Kira for contract review, Crayon for market intelligence, and internal expertise for financial and strategic analysis.
Pricing and Value Considerations
AI due diligence tools range from relatively affordable subscription products to enterprise platforms with significant implementation costs.
Common pricing models include:
- Subscription pricing based on users, data volume, or features
- Per-project fees for specific transactions or reviews
- Implementation and training costs for setup, customization, and onboarding
When assessing value, look beyond the sticker price. The real return on investment often comes from:
- reduced manual review time
- improved accuracy and consistency
- faster transaction timelines
- better identification of risks before closing
For legal teams, AI can also help optimize resource allocation by freeing senior professionals from repetitive document review and allowing them to focus on higher-value analysis and client advice.
Frequently Asked Questions About AI for Due Diligence
Can AI completely replace human due diligence professionals?
No. AI is an assistant, not a replacement. It can accelerate review and uncover patterns, but human judgment is still necessary to interpret findings and make decisions.
What kind of data can AI tools process?
AI tools can process unstructured documents like contracts, emails, and reports, as well as structured data such as financial records and databases. Capabilities vary by platform.
How accurate is AI in due diligence?
Accuracy depends on the tool, the training data, and the task. Leading platforms can be highly effective at spotting clauses, anomalies, and patterns in large document sets.
Is AI secure enough for confidential due diligence work?
Reputable vendors typically offer security and confidentiality controls, but teams should still review each provider’s safeguards carefully before use.
How long does implementation take?
Simple tools may be ready quickly, while enterprise platforms can take weeks or months to configure and train.
What are the biggest challenges?
Common challenges include cost, training, change management, privacy concerns, and ensuring the output is understandable and useful to reviewers.
Conclusion
AI is becoming an important part of modern due diligence workflows. For legal and M&A teams, it can speed up document review, improve issue spotting, and reduce the burden of repetitive manual work.
The most effective approach is to match the tool to the task. Luminance and Kira are strong options for contract analysis. Relativity and Everlaw work well for large-scale document review. Crayon supports strategic market analysis, and AuditBoard can help with control and risk assessment.
AI does not replace legal judgment, but it can make due diligence faster, more consistent, and more manageable. For teams that handle frequent transactions or large document volumes, that can be a meaningful competitive advantage.