How to Use AI for Due Diligence: A Practical Guide for Lawyers and Businesses
Due diligence is one of the most important steps in any major transaction. Whether you are acquiring a company, assessing an investment, or onboarding a new partner, you need to understand the legal, financial, and operational risks before moving forward.
Traditionally, this work has depended on manual review of large document sets, which is slow, expensive, and easy to get wrong. AI is changing that. Used correctly, it can help legal and business teams review more material in less time, spot issues faster, and focus attention on the highest-risk areas.
For lawyers and deal teams, knowing how to use AI for due diligence is becoming a practical necessity.
Why AI Matters in Due Diligence
Due diligence often involves reviewing thousands of contracts, emails, financial statements, filings, and internal records. That creates several common problems:
- Manual review takes too long
- Important issues can be missed in large data sets
- Different reviewers may assess risk differently
- Costs rise quickly as more hours are required
AI helps address these challenges by automating repetitive work and highlighting information that deserves human review. In practice, it can:
- Speed up document review
- Extract key terms, dates, parties, and obligations
- Flag unusual clauses or missing provisions
- Organize large document sets by topic or relevance
- Support more consistent risk assessment
- Reduce the time and cost of review
AI does not replace legal judgment, but it can make due diligence faster, broader, and more efficient.
Best AI Tools for Due Diligence
Different tools are suited to different types of due diligence work. Some are strong on contract analysis, while others are better for large-scale document review and investigation.
1. Kira Systems
Kira Systems is a contract analysis platform that uses machine learning to extract and analyze information from legal documents.
What it does:
- Identifies clauses, terms, dates, parties, and obligations
- Flags deviations from standard language
- Helps teams review large contract sets more efficiently
Why it is useful:
Kira is a strong fit for M&A and other transactions where the main task is reviewing contracts at scale. It helps teams quickly find key provisions and potential issues without reading every agreement line by line.
Best fit:
- M&A due diligence
- Real estate transactions
- Loan portfolio reviews
- Compliance audits involving contract review
Pros:
- Strong contract review functionality
- Customizable for specific clauses and provisions
- User-friendly interface
- Useful reporting features
- Integrates with other legal tech platforms
Cons:
- Less useful for broader financial or operational due diligence without other tools
- Can be expensive
- Requires setup and training to get the most value
2. RelativityOne
RelativityOne is a cloud-based eDiscovery platform with AI features that are also useful in due diligence.
What it does:
- Supports large-scale document review
- Uses technology-assisted review, conceptual search, and entity extraction
- Helps prioritize relevant documents and identify patterns
Why it is useful:
RelativityOne is well suited to due diligence involving large volumes of unstructured data, such as emails, internal communications, and scanned documents. It can help teams sort material quickly and focus on the most relevant records.
Best fit:
- Large M&A reviews
- Internal investigations
- Regulatory matters
- Due diligence involving large unstructured data sets
Pros:
- Handles very large data volumes
- Strong search, clustering, and review tools
- Secure and scalable
- Suitable for complex matters
- Well-established platform
Cons:
- Can be complex to use
- Primarily built for eDiscovery, so it may need adaptation for due diligence workflows
- Pricing can be significant
3. Everlaw
Everlaw is another cloud-based eDiscovery platform with AI-enabled review features.
What it does:
- Supports predictive coding and clustering
- Helps identify themes, relevant documents, and anomalies
- Makes review and collaboration easier for legal teams
Why it is useful:
Everlaw is a good choice when due diligence involves discovery-like data and teams want a tool that is relatively easy to use. It can speed up document review without requiring a steep learning curve.
Best fit:
- Transactional due diligence
- Internal investigations
- Review of email archives and corporate documents
- Teams that want a user-friendly platform
Pros:
- Easy to use
- Strong collaboration features
- Effective review automation
- Cloud-based and scalable
- Good value for the feature set
Cons:
- Less specialized for contract clause analysis than dedicated tools
- Best suited to eDiscovery-style data rather than structured financial review
4. ThoughtRiver
ThoughtRiver is an AI contract review platform focused on identifying contractual risk.
What it does:
- Reads contracts using natural language processing
- Flags key clauses, risks, and missing terms
- Assesses documents against defined risk policies or playbooks
Why it is useful:
ThoughtRiver is especially helpful when the goal is to quickly assess a large contract portfolio and identify agreements that may carry higher risk.
Best fit:
- Pre-acquisition due diligence
- Post-acquisition contract remediation
- Contract risk management
Pros:
- Strong at contract risk assessment
- Provides actionable insights
- Can be tailored with custom policies
- Efficient for large contract volumes
- Useful for structured risk review
Cons:
- More focused on risk assessment than detailed data extraction
- Requires setup of risk policies
- May be costly for smaller firms
5. Seal Software, now part of DocuSign
Seal Software is now integrated into DocuSign’s contract lifecycle management offering and provides AI-driven contract analytics.
What it does:
- Extracts key data points from contracts
- Identifies risks and compliance issues
- Helps teams understand contractual obligations at scale
Why it is useful:
For due diligence, Seal can help teams quickly review a large contract repository and identify clauses or obligations that need closer human attention.
Best fit:
- M&A
- Regulatory compliance
- Financial due diligence
- Organizations already using DocuSign CLM
Pros:
- Strong contract data extraction
- Useful for risk and compliance review
- Integrates with DocuSign CLM
- Scalable for enterprise needs
Cons:
- More of a CLM-integrated solution than a standalone due diligence tool
- Requires workflow integration
- May be expensive for smaller businesses
6. CognitiveScale
CognitiveScale offers a flexible AI platform that can be used to build custom due diligence applications.
What it does:
- Supports analysis of unstructured data
- Can be used to predict outcomes and automate decisions
- Allows custom workflows and models
Why it is useful:
This option is best for organizations that need a tailored due diligence solution rather than an off-the-shelf product. It can be used to analyze financial reports, market data, news, and internal documents in a customized way.
Best fit:
- Specialized due diligence projects
- Custom risk models
- Non-traditional data sources
- Organizations with in-house AI development resources
Pros:
- Highly flexible
- Can integrate many data sources
- Supports custom applications
- Useful for proprietary workflows
Cons:
- Requires technical expertise
- Not an out-of-the-box due diligence tool
- Can take significant time and resources to implement
7. Verity by Litera
Verity is an AI-powered contract review tool focused on clause identification and comparison.
What it does:
- Finds specific clauses and provisions across large document sets
- Flags deviations and inconsistencies
- Helps teams compare language across agreements
Why it is useful:
Verity is useful when due diligence requires checking for specific terms such as change of control, indemnification, or termination provisions across many contracts.
Best fit:
- M&A due diligence
- Portfolio reviews
- Clause consistency analysis
Pros:
- Strong clause identification and comparison
- Helps assess consistency across documents
- User-friendly review experience
- Integrates with other Litera tools
Cons:
- Narrower focus on contract clauses
- May require training for specific clause definitions
- Can be expensive for smaller teams
How to Choose the Right AI Tool
The right tool depends on the type of due diligence you are doing and the kind of data you need to review.
Consider the following:
- Type of review: contract-heavy work, large document review, or a mix of both
- Data volume: how much material needs to be processed
- Budget: software, training, implementation, and support costs
- Team experience: whether the team needs a simple interface or can manage a more complex platform
- Integration: how well the tool fits with your existing systems
- Functionality: clause extraction, risk flagging, search, comparison, or custom workflows
- Customization: whether the tool can be tailored to your specific review process
A practical approach is to define the due diligence scope first, identify the data sources involved, and then compare tools based on those needs. Demos and pilot projects can be especially helpful before making a decision.
Pricing and Value Considerations
AI due diligence tools are priced in different ways. Common pricing factors include:
- Data volume
- Number of users
- Features and modules
- Implementation and training
- Ongoing support
When comparing cost, think beyond the software price. The real question is whether the tool saves enough time and reduces enough risk to justify the expense.
In many cases, the value comes from:
- Less manual review time
- Faster transaction timelines
- More consistent issue spotting
- Reduced risk of overlooking important terms
- Better use of senior lawyer time
For the right use case, AI can deliver strong return on investment. Many vendors offer custom pricing, so it is worth speaking with them directly to understand the full cost and fit.
Frequently Asked Questions
Can AI replace lawyers in due diligence?
No. AI is best used to support human reviewers, not replace them. Lawyers still need to interpret issues, apply judgment, and advise on legal risk.
What types of data can AI analyze?
AI can analyze contracts, financial statements, emails, internal documents, regulatory filings, news articles, and public web data, depending on the tool.
How accurate is AI for due diligence?
Accuracy is often strong for structured tasks like clause identification and data extraction, but results still need human review and validation.
Is AI due diligence only for large firms?
No. While larger firms were early adopters, many tools are now available to mid-sized firms and smaller businesses as well.
How long does implementation take?
It depends on the tool. Some cloud-based products can be deployed quickly, while enterprise platforms with custom setup may take longer.
How do I protect data privacy?
Choose vendors with strong security controls, encryption, access management, and clear data handling policies. Make sure the platform meets your organization’s compliance requirements.
Conclusion
AI is reshaping due diligence by making document review faster, more scalable, and more consistent. For lawyers and business teams, the main benefit is not replacing judgment, but improving the quality and efficiency of the review process.
Tools like Kira Systems, RelativityOne, Everlaw, ThoughtRiver, Seal Software, CognitiveScale, and Verity each serve different due diligence needs. The best choice depends on the type of data you are reviewing, the size of the project, your budget, and how much customization you need.
For teams looking to improve deal speed and reduce risk, learning how to use AI for due diligence is becoming an important part of modern transactional work.