How to Use AI for Due Diligence: Streamlining Investigations and Mitigating Risk
In today’s fast-moving business environment, thorough due diligence is essential. Whether you are acquiring a company, investing in a startup, or vetting a potential partner, you need a clear understanding of the risks and opportunities before making a decision.
Traditionally, due diligence has been slow and labor-intensive. Teams often have to review large volumes of contracts, financial records, regulatory filings, and other documents by hand. AI is changing that process. Used well, it can help teams work faster, surface important issues earlier, and make the review process more consistent.
This guide explains how to use AI for due diligence, what it can do well, and how to choose tools that fit your workflow.
Why AI Matters in Due Diligence
For lawyers, financial advisors, and business leaders, due diligence mistakes can be costly. Missed red flags can lead to financial loss, reputational harm, or legal exposure. At the same time, the amount of information involved in modern transactions can overwhelm manual review alone.
AI helps by automating repetitive tasks, analyzing unstructured data, and spotting patterns that may be hard to catch in a first-pass review. In practical terms, it can help you:
- Speed up document review by processing large volumes of material quickly
- Reduce manual errors by applying consistent rules across documents
- Surface hidden issues by identifying patterns, anomalies, and outliers
- Improve risk assessment by organizing findings more efficiently
- Free up human reviewers for judgment-based analysis and strategic decisions
The main value of AI in due diligence is not replacement. It is augmentation. AI handles the heavy lifting so legal and business professionals can focus on higher-value work.
Best AI Tools for Due Diligence
The right tool depends on the type of review you are running. Some platforms are built for contract analysis, while others are better for risk screening, legal research, or financial control review.
1. Kira Systems
Kira Systems is a contract analysis platform that uses machine learning and natural language processing to identify, extract, and analyze key clauses in legal documents.
What it does:
- Identifies provisions in contracts, leases, and financial agreements
- Flags deviations from standard terms
- Summarizes critical information for review
Why it is useful:
Kira is especially helpful when due diligence involves reviewing large sets of similar documents. It can quickly surface change-of-control clauses, termination rights, indemnities, and other terms that may affect a transaction.
Best fit:
- M&A due diligence
- Real estate transactions
- High-volume contract review
Pros:
- Strong clause identification
- User-friendly interface
- Good reporting features
- Effective for standard document sets
Cons:
- Primarily focused on contract review
- Can be costly for smaller firms
- May require setup and customization
2. Luminance
Luminance is an AI platform for legal document review that uses NLP to read and analyze legal text.
What it does:
- Extracts key information from legal documents
- Flags anomalies and unusual language
- Summarizes complex materials
Why it is useful:
Luminance is built to understand context, not just keywords. That makes it useful for identifying risks, obligations, and deviations that may not be obvious in a manual scan.
Best fit:
- Large-scale due diligence
- Regulatory reviews
- Litigation support
- Complex document sets
Pros:
- Sophisticated language analysis
- Strong anomaly detection
- Works well with large volumes of documents
- Integrates with existing workflows
Cons:
- Can have a steeper learning curve
- Often priced at the enterprise level
3. eBrevia
eBrevia is a document analysis platform designed to extract data points and identify clauses across legal and business documents.
What it does:
- Pulls structured data from unstructured documents
- Identifies specific clauses and terms
- Can be configured to search for targeted due diligence information
Why it is useful:
eBrevia is effective when you need to turn document content into structured outputs, such as dates, parties, payment terms, or obligations. That makes it useful for collecting information from leases, contracts, and financial documents.
Best fit:
- Extracting data from mixed document sets
- Real estate due diligence
- Agreement review where specific fields matter
Pros:
- Flexible extraction capabilities
- User-friendly configuration
- Works across a range of document types
- Good for targeted review tasks
Cons:
- May require more setup for specialized use cases
4. LexisNexis Diligence
LexisNexis Diligence is a broader due diligence platform that supports legal and regulatory screening.
What it does:
- Performs entity-level risk assessments
- Helps review regulatory compliance issues
- Flags litigation risk, sanctions concerns, and adverse media
Why it is useful:
This tool combines AI with a large legal and business information database, making it useful for early-stage screening and risk discovery. It can quickly surface public information that may warrant deeper investigation.
Best fit:
- Preliminary due diligence
- Compliance checks
- Background screening
- Reputational risk review
Pros:
- Broad coverage
- Strong database integration
- Useful for risk screening
- Robust reporting features
Cons:
- May be bundled into a larger subscription
- Can be more than needed for narrow review tasks
5. AuditBoard
AuditBoard is primarily an audit and SOX management platform, but it also includes AI-enabled features that support financial and operational due diligence.
What it does:
- Supports risk assessment
- Helps with control testing
- Assists in data analysis for audit-related review
Why it is useful:
When due diligence requires a closer look at financial controls, operational processes, or reporting risk, AuditBoard can help identify weaknesses that deserve follow-up.
Best fit:
- Financial due diligence
- Operational review
- Control and compliance assessment
Pros:
- Strong focus on controls and audit workflows
- Clear dashboards
- Helpful for financial and operational analysis
Cons:
- Less suited to legal document review
- May need to be paired with other tools
6. Casetext (CoCounsel)
CoCounsel is a generative AI legal assistant that can help with legal research and document analysis.
What it does:
- Summarizes cases and documents
- Identifies relevant precedents
- Helps draft legal work product
- Answers questions about large sets of documents
Why it is useful:
For due diligence, CoCounsel can help review transcripts, contracts, and filings more quickly. It is especially useful when the review requires legal research or close reading of complex language.
Best fit:
- Research-heavy due diligence
- Litigation-related due diligence
- Analysis of complex legal text
Pros:
- Strong generative AI capabilities
- Conversational interface
- Useful for research and analysis
- Handles natural language questions well
Cons:
- Outputs require human verification
- Can produce unreliable results if not checked carefully
- Newer than some traditional document review tools
How to Use AI for Due Diligence in Practice
If you are trying to build a due diligence workflow around AI, start with the tasks that are repetitive, high-volume, and rules-based. A practical workflow often looks like this:
- Collect and organize source documents
- Use AI to sort and categorize documents by type
- Extract key fields, clauses, and dates
- Flag unusual terms, missing items, or inconsistencies
- Use human reviewers to verify important findings
- Summarize results into a due diligence report
AI works best when it is applied to well-defined tasks. For example, it can help identify change-of-control clauses across hundreds of agreements, extract obligations from leases, or screen for litigation references in public filings.
How to Choose the Right AI Tool
Selecting the right platform depends on the type of due diligence you are performing and the volume of material you need to review.
Consider the following:
- Scope of review: Are you focused on contracts, financials, compliance, or background risk?
- Document volume: Are you reviewing a small batch or thousands of files?
- Task type: Do you need extraction, classification, anomaly detection, screening, or legal research?
- Workflow integration: Will the tool fit your existing processes and tech stack?
- Budget: Pricing can vary widely depending on the platform and licensing model
- Team experience: Some tools are easier to adopt than others and may require training
In many cases, a combination of tools is the best approach. For example, you might use Kira or Luminance for contract review, CoCounsel for legal research, and LexisNexis Diligence for background screening.
Pricing and Value Considerations
AI due diligence tools are an investment, but they can create value by reducing manual work and improving review quality.
Common pricing models include:
- Subscription-based pricing: Monthly or annual plans based on users or feature access
- Per-project or per-document pricing: Useful for specific reviews or short-term engagements
- Enterprise licensing: Custom pricing for larger organizations with broader needs
When evaluating cost, look beyond the sticker price. A tool that reduces review time, improves consistency, and helps catch one significant issue may be worth the investment. If possible, ask for a demo or pilot before committing to a long-term contract.
Frequently Asked Questions About AI in Due Diligence
Can AI completely replace human reviewers in due diligence?
No. AI should support human reviewers, not replace them. It can automate document processing and highlight issues, but legal judgment and strategic analysis still require people.
How accurate are AI tools for due diligence?
Accuracy depends on the tool, the quality of the training data, and the complexity of the documents. Strong platforms can be very effective, but important findings should always be reviewed by a human.
What types of data can AI analyze for due diligence?
AI can work with contracts, emails, reports, spreadsheets, databases, financial statements, regulatory filings, and public web data.
How long does it take to implement an AI due diligence tool?
Some tools are ready to use quickly after setup. Others need training, configuration, or integration and may take days, weeks, or longer.
Is sensitive due diligence data safe with AI tools?
Reputable vendors usually offer security controls, encryption, and compliance features. Still, you should review the vendor’s security practices and certifications before sharing sensitive data.
What role does machine learning play in AI due diligence?
Machine learning helps AI systems learn from data, improve over time, and adapt to different document types. It is commonly used for clause detection, document classification, and risk identification.
Conclusion
AI is no longer a future concept in due diligence. It is already helping legal and business teams review documents faster, identify issues earlier, and manage risk more effectively.
The best results come from using AI as a support tool, not a substitute for professional judgment. By choosing the right platform, defining the right tasks, and building human review into the process, you can make due diligence more efficient, more consistent, and more useful for decision-making.