How to Use AI for Due Diligence: Streamline Investigations with Intelligent Tools
In today’s fast-moving business and legal environment, due diligence needs to be both thorough and efficient. Whether you are evaluating an acquisition, assessing an investment, onboarding a client, or reviewing compliance risk, the process often involves large volumes of documents and time-sensitive decisions.
Traditionally, due diligence has been labor-intensive, repetitive, and prone to human error. AI is changing that by helping teams review documents faster, surface risks earlier, and organize information more effectively. For lawyers, compliance teams, investors, and business leaders, learning how to use AI for due diligence is quickly becoming a practical necessity.
This guide explains how AI supports due diligence, which tools are commonly used, and what to consider when choosing the right solution.
Why AI Matters in Due Diligence
The amount of information involved in due diligence can be overwhelming. A mergers and acquisitions deal may include contracts, financial statements, employee records, intellectual property filings, regulatory approvals, emails, and internal reports. Reviewing all of that manually takes significant time and resources.
AI helps by analyzing large sets of structured and unstructured data, extracting key terms, flagging unusual patterns, and prioritizing documents for review. Depending on the tool, it can also summarize content, identify potential risks, and organize findings into a more usable format.
Key benefits include:
- Speed and efficiency: AI can process documents in hours instead of days or weeks.
- Improved accuracy: Automation reduces the chance of missed details in large review sets.
- Lower costs: Less manual review means less time spent on repetitive work.
- Better risk detection: AI can highlight anomalies, missing information, and potentially problematic clauses.
- Stronger decision-making: Teams get faster access to more organized and actionable information.
For transactional lawyers, compliance professionals, and deal teams, AI is becoming an important part of modern due diligence workflows.
Best AI Tools for Due Diligence
Different tools are designed for different parts of the due diligence process. Some focus on contract analysis, while others are built for document review, compliance, or data room analysis.
1. Kira Systems
Kira Systems is an AI-powered contract analysis platform that uses machine learning to review and extract information from legal documents.
What it does:
- Identifies and extracts clauses and provisions from contracts
- Supports a wide range of document types
- Can be trained to recognize custom data points
Why it is useful:
Kira is especially helpful in M&A due diligence, where teams need to review large numbers of contracts quickly. It can flag items such as change of control clauses, assignment provisions, termination rights, and other terms that may affect a transaction.
Best fit:
- M&A due diligence
- Real estate transactions
- Large-scale contract review
Pros:
- Strong clause identification
- User-friendly interface
- Customizable training
- Good integrations
Cons:
- Can be expensive
- Focused mainly on contract review, so broader due diligence may require other tools
2. RelativityOne
RelativityOne is a cloud-based e-discovery and analytics platform with AI features that support document review and analysis.
What it does:
- Processes and reviews large datasets
- Uses predictive coding and clustering to organize documents
- Helps identify relevant, privileged, or anomalous content
Why it is useful:
RelativityOne is a strong option when due diligence involves large collections of emails, internal documents, and data room materials. It can help teams prioritize review and surface important themes more efficiently.
Best fit:
- Large-scale due diligence
- Corporate investigations
- Internal audits
- Pre-transaction data room review
Pros:
- Highly scalable
- Strong analytics
- Advanced AI-driven review tools
- Secure and enterprise-ready
Cons:
- More complex than some transaction-focused tools
- Often requires familiarity with e-discovery workflows
- Can be a significant investment
3. AuditBoard
AuditBoard is a cloud-based platform for risk, compliance, and audit management with AI features that support due diligence work.
What it does:
- Automates risk and audit workflows
- Helps track control deficiencies and regulatory changes
- Connects risks to operational activities
Why it is useful:
AuditBoard is useful when due diligence is focused on compliance posture, internal controls, and operational risk. It can help assess whether a target company has effective compliance processes and where weaknesses may exist.
Best fit:
- Compliance due diligence
- Risk assessments
- Regulated industries
- Internal control reviews
Pros:
- Broad risk and compliance functionality
- Useful for ongoing monitoring
- Streamlined workflows
Cons:
- Less specialized for contract analysis
- Not built primarily for deep transactional document review
4. Everlaw
Everlaw is a cloud-based e-discovery platform that uses AI to streamline legal review and document analysis.
What it does:
- Supports document processing and advanced search
- Includes AI-powered review tools
- Offers data visualization and collaboration features
Why it is useful:
Everlaw can speed up review in due diligence projects with large electronic document sets. Its analytics and visualization tools can help teams spot patterns, connections, and areas that need closer attention.
Best fit:
- Complex due diligence with large data volumes
- Investigations
- Legal review requiring collaboration and quick issue spotting
Pros:
- Intuitive interface
- Strong search and analytics
- Good collaboration tools
- Useful visual reporting
Cons:
- Built around e-discovery, so it may feel unfamiliar for transactional users
- May require some onboarding for teams new to the platform
5. Seal Software, now part of DocuSign
Seal Software was an AI contract discovery and analytics solution that is now part of the DocuSign ecosystem.
What it does:
- Finds, extracts, and analyzes contract data
- Identifies key terms, obligations, and risks
- Supports review across large contract repositories
Why it is useful:
For due diligence involving many agreements, Seal’s capabilities can help identify expirations, renewals, liabilities, and change-of-control provisions across a contract portfolio.
Best fit:
- Large contract portfolios
- M&A due diligence
- Organization-wide contract and compliance review
Pros:
- Strong contract analysis features
- Useful for identifying risks and obligations at scale
Cons:
- Features are integrated within DocuSign
- Standalone functionality may be less distinct than dedicated platforms
6. Disclosed
Disclosed is an AI platform built specifically for transactional due diligence and data room review.
What it does:
- Processes and understands data room content
- Extracts key information
- Flags risks and creates summaries
Why it is useful:
Disclosed is designed to reduce the time spent reviewing data rooms by automating much of the initial analysis. It is especially relevant for deal teams that need fast, reliable issue spotting.
Best fit:
- M&A due diligence
- Private equity
- Venture capital
- Structured data room review
Pros:
- Purpose-built for transactional work
- Efficient for data room review
- Produces useful summaries and issue flags
Cons:
- Newer than some established competitors
- More narrow in scope than broader legal review platforms
7. Hyperscience
Hyperscience is an intelligent document processing platform that is useful when due diligence involves scanned or hard-to-process documents.
What it does:
- Extracts data from unstructured and semi-structured documents
- Handles scanned PDFs, images, and handwritten forms
- Prepares data for further analysis or review
Why it is useful:
When due diligence includes legacy paper files or scanned records, Hyperscience can convert that content into usable data more efficiently than manual review alone.
Best fit:
- Legacy document review
- Financial services
- Real estate
- Historical corporate due diligence
Pros:
- Strong extraction accuracy
- Handles difficult document types
- Scales to high-volume workflows
Cons:
- Primarily a data extraction layer
- Usually needs to be paired with other tools for deeper analysis
How to Choose the Right AI Tool for Due Diligence
The right tool depends on the type of due diligence you are running and the data you need to review. Consider the following:
- Nature of the data: Are you reviewing contracts, emails, financial records, or scanned files?
- Scope of the project: Is this for M&A, compliance, risk review, or regulatory assessment?
- Depth of analysis needed: Do you need clause extraction, document classification, anomaly detection, or summarization?
- Integration requirements: Will the tool need to work with your document management system or other legal tech?
- Ease of use: Can your team adopt the platform without a steep learning curve?
- Scalability: Can it handle the size of your current and future reviews?
- Budget: Does the pricing fit the expected value of the project?
In many cases, a combination of tools works best. For example, you might use Hyperscience to digitize scanned documents, Kira to extract contract terms, and RelativityOne to review emails and supporting records.
Pricing and Value Considerations
AI tools for due diligence vary widely in cost. Pricing may range from monthly subscriptions to enterprise licensing, depending on the vendor and deployment.
Common pricing models include:
- Subscription-based pricing: Often tied to users, data volume, or feature levels
- Per-document or per-project pricing: Common for specialized review projects
- Enterprise licensing: Used by larger organizations with broader or ongoing needs
When assessing cost, focus on value rather than price alone. A well-chosen tool can deliver return on investment through:
- Time savings from reduced manual review
- Lower risk from earlier issue detection
- Faster deal timelines
- Better-informed decisions
Before committing, request a demo and, if possible, run a pilot project to confirm that the platform fits your workflow and delivers practical results.
Frequently Asked Questions About AI for Due Diligence
Can AI replace human reviewers in due diligence?
No. AI is best used to support human review, not replace it. It can handle repetitive tasks, surface patterns, and flag issues, but lawyers and other professionals still need to make judgment calls and interpret complex findings.
How accurate are AI tools for due diligence?
Accuracy depends on the tool, the task, and the quality of the input data. Some platforms perform very well at specific tasks like clause extraction, but results still need human validation.
What types of data can AI analyze?
AI can review contracts, financial statements, emails, internal reports, regulatory filings, public records, and other structured or unstructured data.
Is it difficult to implement AI tools for due diligence?
It depends on the platform. Many cloud-based tools are designed for straightforward deployment, but more advanced integrations or custom training may require specialized support.
How do I protect confidentiality and security?
Choose vendors with strong security controls, clear data handling policies, and relevant compliance standards. Look for features such as encryption, access controls, and audit trails.
Conclusion
AI is making due diligence faster, more organized, and more effective. By automating repetitive review tasks and surfacing important risks sooner, it helps legal and business teams work with greater speed and confidence.
From contract analysis platforms to e-discovery and compliance tools, there are AI solutions for many different due diligence needs. The best choice depends on your data, your workflow, and the type of review you need to complete.
For teams handling large volumes of documents or tight deal timelines, AI is no longer just a helpful add-on. It is becoming a practical part of modern due diligence workflows.