How to Use AI for Due Diligence: Streamlining Investigations
Due diligence is a core part of sound business decision-making, especially in legal, financial, compliance, and M&A contexts. It involves thoroughly investigating a business or individual before entering into a contract or transaction.
Traditionally, this work has been time-consuming, labor-intensive, and expensive, with teams manually reviewing large volumes of documents, data, and communications. AI is changing that by helping professionals automate repetitive review tasks, surface risks faster, and work through more information in less time.
This guide explains how to use AI for due diligence, which tools are commonly used, and how to choose the right solution for your workflow.
Why AI-Powered Due Diligence Matters
For lawyers, financial analysts, compliance officers, and M&A teams, due diligence often means reviewing years of contracts, financial statements, regulatory filings, and other records. Doing that manually can take weeks or months and usually requires significant staff time.
AI helps by processing large datasets quickly and identifying patterns, anomalies, and issues that may be missed in a manual review. For example, AI tools can:
- flag contract clauses that deviate from standard language
- identify unusual obligations, indemnities, or termination rights
- surface missing or inconsistent provisions
- highlight possible compliance issues
- detect unusual financial activity or outliers in records
The main value of AI is not just speed. It also improves consistency and allows professionals to spend more time on analysis, judgment, and client advice instead of repetitive document review. In practice, that can support faster deal execution, lower review costs, and better risk detection.
Best AI Tools for Due Diligence
The AI due diligence market includes tools for contract review, legal research, document analysis, audit workflows, and deal management. The right choice depends on the type of diligence you are doing and how your team works.
1. Relativity
What it does: Relativity is an eDiscovery and review platform that uses AI and machine learning for document analysis. Although it is best known for litigation support, it also works well for due diligence. Its features include Technology Assisted Review (TAR), conceptual search, and near-duplicate identification, which help sort and prioritize large document sets.
Why it is useful: Relativity reduces the time and cost of manual review. It can help identify important documents, privileged material, and relevant patterns across large collections. Its analytics and visualization tools also make it easier to understand the overall document population.
Best fit/use case: Best for large-scale M&A transactions, regulatory reviews, and internal investigations involving large amounts of electronic data.
Pros:
- Highly scalable for large datasets
- Strong AI features for document review
- Useful analytics and reporting tools
- Integrates with other legal tech systems
Cons:
- Can be complex for new users
- Often priced for larger firms or enterprise teams
- May require more infrastructure and setup than simpler tools
2. Kira Systems
What it does: Kira Systems, now part of Litera, focuses on AI-powered contract analysis. It extracts and analyzes key provisions, clauses, and data points from legal documents, helping teams review contracts at scale.
Why it is useful: Kira automates the manual review of large contract sets and helps teams find issues more consistently. It is especially useful for identifying change of control clauses, indemnification language, termination rights, and other important obligations or risks.
Best fit/use case: Well suited to M&A due diligence, real estate transactions, and any project involving high-volume contract review.
Pros:
- Strong accuracy for contract extraction and review
- User-friendly for legal teams
- Pre-trained models for common clauses and data points
- Good for identifying contract risks and obligations
Cons:
- More specialized for contract analysis than general document review
- Can be expensive for smaller firms or occasional use
- May require training and validation for unusual contract sets
3. Luminance
What it does: Luminance is an AI platform built for legal document review and analysis. It uses machine learning to understand legal language and review large volumes of documents quickly, identifying clauses, anomalies, and potential risks.
Why it is useful: Luminance helps legal teams work through due diligence more efficiently across a range of document types, including contracts, leases, and transaction documents. It also supports document comparison and discrepancy detection.
Best fit/use case: A strong option for M&A, corporate law, and other matters involving complex legal documents across multiple formats.
Pros:
- Fast review of large document sets
- Designed with legal language in mind
- Effective at flagging anomalies and unusual clauses
- Easy to use for legal teams
Cons:
- May require setup and training on specific datasets
- Pricing can be a factor for smaller firms
- Best suited to legal text analysis rather than broader business workflows
4. Casetext with CoCounsel
What it does: Casetext, through its AI assistant CoCounsel, provides tools for legal research, drafting, summarization, and document analysis. In a due diligence workflow, it can help research legal issues, summarize lengthy materials, and support preliminary factual analysis.
Why it is useful: CoCounsel can save time on research and summarization, helping lawyers quickly understand relevant case law, regulatory context, or factual issues tied to a transaction. That makes it useful when diligence requires more than just contract review.
Best fit/use case: Best for legal due diligence involving research-heavy questions, case law, regulations, or document summarization.
Pros:
- Strong legal research and analysis capabilities
- Useful for summarizing complex legal text
- Helps contextualize legal risks and issues
- Continues to expand its feature set
Cons:
- Still evolving as a product
- Less focused on structured contract extraction than dedicated review tools
- May need to be paired with other platforms for a full due diligence workflow
5. AuditBoard
What it does: AuditBoard is a cloud platform for audit, risk, and compliance management. It is not a document review tool in the same way as Kira or Luminance, but it supports due diligence by helping teams assess controls, compliance, and risk posture.
Why it is useful: AuditBoard can help teams evaluate internal controls and identify operational risks, which are important in financial and operational due diligence. It is useful when the goal is to understand how a target company manages compliance and risk internally.
Best fit/use case: Good for financial due diligence, operational due diligence, and control environment assessments, especially for private equity and corporate development teams.
Pros:
- Strong risk and control management features
- Streamlines audit and compliance processes
- Improves visibility into internal control environments
- Good workflow and reporting tools
Cons:
- Not designed for direct contract or document extraction
- Requires implementation and internal data input
- Better for risk management than transactional review
6. Intapp DealCloud
What it does: DealCloud, part of Intapp, is a deal and relationship management platform with AI-driven analytics. It helps teams manage deal pipelines, track relationships, and coordinate due diligence workflows.
Why it is useful: DealCloud centralizes deal information and helps teams track tasks, assess historical deal data, and coordinate diligence across stakeholders. It is especially useful where process management is as important as document review.
Best fit/use case: Best for investment banking, private equity, and corporate development teams managing multiple deals at once.
Pros:
- Centralized deal and relationship management
- AI-driven insights for deals and market trends
- Helps coordinate teams and tasks
- Gives a broader view of the deal lifecycle
Cons:
- Less focused on detailed document analysis
- Often positioned as an enterprise platform
- Works best when integrated with other data sources
How to Choose the Right AI Tool for Due Diligence
Choosing the right tool depends on the type of diligence you perform, the volume of material you review, and how your team operates.
Consider the scope of the work
Are you reviewing contracts, financial records, regulatory filings, or a mix of documents? For contract-heavy diligence, tools like Kira or Luminance are strong options. For broader document review, Relativity may be a better fit. If your work depends heavily on legal research and summarization, CoCounsel may be more useful.
Assess the volume and complexity of the data
Large transactions and complex reviews require tools that can handle massive datasets reliably. If the project involves only a smaller, more focused document set, a specialized tool may be enough.
Evaluate your team’s technical expertise
Some tools are designed for legal and business users with little technical background. Others require more training, setup, or IT support. Make sure the tool fits your team’s workflow and capabilities.
Check integration requirements
Look at how the tool will work with your existing systems, such as document management platforms, CRM tools, or matter management software. Better integration usually means less manual work and fewer handoff issues.
Review budget and pricing
Pricing can vary widely based on features, data volume, and usage. Some tools are subscription-based, while others are priced by project or enterprise agreement. Ask about demos, implementation support, and training before making a decision.
Pricing and Value Considerations
AI due diligence tools can range from relatively accessible subscriptions to significant enterprise investments. The right way to evaluate cost is by comparing it with the time saved, the reduction in review risk, and the potential value of faster deal execution.
For smaller firms or teams new to AI, a phased approach often makes sense. Start with one high-impact use case, such as contract review or legal research, then expand as your team becomes more comfortable with the workflow.
Also consider support and implementation. Training, onboarding, and customer service can make a major difference in whether a tool delivers value in practice.
Frequently Asked Questions
What types of due diligence can AI assist with?
AI can support legal due diligence, financial due diligence, operational due diligence, and compliance due diligence. Common tasks include contract review, litigation risk assessment, fraud detection, internal control review, and regulatory analysis.
How accurate is AI in due diligence?
Accuracy depends on the tool, the use case, and the quality of the underlying data. AI can be highly effective for repetitive review tasks, but human oversight is still important, especially for nuanced issues and final decision-making.
Can AI replace human due diligence professionals?
No. AI is best used as an assistive tool. It can automate repetitive work and speed up review, but professionals still need to apply legal, financial, and strategic judgment.
What are the main benefits of using AI for due diligence?
The main benefits are faster review, lower costs, greater consistency, improved risk detection, and the ability to handle larger and more complex document sets.
Is AI for due diligence expensive?
It can be, depending on the tool and scope of use. Enterprise platforms may be costly, but there are also more affordable options for smaller teams. The right comparison is not just price, but overall value.
What data privacy and security issues should you consider?
Before using any AI due diligence tool, review how the vendor stores, processes, and protects data. Make sure the solution fits your confidentiality requirements and complies with applicable data protection rules such as GDPR or CCPA where relevant.
Conclusion
AI is now a practical part of modern due diligence, not just a future possibility. Used well, it can help legal, financial, and business teams review documents faster, identify risks more reliably, and focus more attention on strategic analysis.
The best results come from choosing tools that match your workflow, document types, and budget. Whether you need contract extraction, legal research, audit support, or deal management, AI can make due diligence more efficient and more effective when paired with human oversight.