How to Use AI for Compliance Review: A Practical Guide for Legal and Business Teams
As regulations become more complex and the volume of business data keeps growing, compliance review has become harder to manage manually. Legal teams, compliance officers, and business leaders are often expected to review contracts, emails, policies, filings, and internal communications quickly and accurately, even as the regulatory environment changes.
This is where AI can help. Used well, AI can speed up compliance review, reduce manual workload, and make it easier to identify risks before they become problems. It is not a replacement for legal judgment, but it is a powerful way to improve efficiency and consistency.
Why AI Matters in Compliance Review
Compliance is not just a routine check. It is a core part of risk management. Missed issues can lead to fines, reputational harm, legal disputes, and operational disruption. The challenge is that traditional review methods are slow, expensive, and vulnerable to human error, especially when the material is unstructured and high volume.
AI changes the process by helping teams:
- review large document sets faster
- flag unusual language or missing provisions
- identify patterns across contracts and communications
- prioritize records that need human attention
- support more consistent review decisions
For legal teams, this means less time spent on repetitive review tasks and more time on analysis and strategy. For compliance teams, it means better visibility into risk and a more scalable review process.
How to Use AI for Compliance Review
The most effective approach is to treat AI as a workflow tool, not an autopilot system. A practical compliance review process usually looks like this:
1. Define the compliance question
Start with a clear objective. For example:
- Are contracts missing required clauses?
- Do internal communications contain potentially problematic language?
- Are documents aligned with a specific regulation or internal policy?
The clearer the review goal, the better the AI can be configured.
2. Gather the relevant data
Collect the documents, emails, agreements, reports, or other records that need review. AI works best when the input set is organized and scoped correctly.
3. Choose the right review method
Different compliance tasks require different tools:
- contract review platforms for clause extraction and risk spotting
- eDiscovery tools for large-scale document review and investigations
- legal research assistants for issue spotting and drafting support
4. Train or configure the system
Some tools use pre-built models, while others allow custom tagging or training. Make sure the AI is aligned with your review standards, key risk categories, and escalation criteria.
5. Review AI outputs carefully
AI can flag likely issues, but those outputs still need human validation. A legal or compliance professional should confirm the findings before any decision is made.
6. Document the process
Keep records of how the AI tool was used, what was reviewed, and how issues were resolved. This is especially important for auditability and internal accountability.
Best AI Tools for Compliance Review
The right tool depends on the type of compliance work you do. Some platforms are better for contract analysis, while others are better for eDiscovery, investigations, or broader document review.
1. Relativity
What it does: Relativity is a widely used eDiscovery platform with AI and machine learning features for reviewing large volumes of electronic data. Its Active Learning capability helps classify documents, identify relevant records, and prioritize them for review. It also supports compliance, investigations, and legal hold workflows.
Why it is useful: Relativity is well suited to legal teams that need to process large datasets efficiently. It can reduce the number of documents that require manual review and help teams identify potentially relevant or privileged material more quickly.
Best fit/use case: Large law firms, corporate legal departments, and government teams handling litigation, investigations, regulatory response, or large-scale document review.
Pros:
- Highly scalable
- Strong eDiscovery functionality
- Effective Active Learning review workflows
- Secure hosting and integration options
Cons:
- Can be complex to implement and learn
- Premium pricing
- May require specialized administration
2. Casetext, now part of Thomson Reuters
What it does: Casetext is best known for AI-powered legal research, but its CoCounsel assistant also supports document analysis and contract review. It can summarize documents, extract key provisions, identify contract risks, and assist with drafting.
Why it is useful: It helps teams review legal documents faster and spot deviations from standard language or compliance requirements. This makes it especially useful for in-house teams working under tight deadlines.
Best fit/use case: Law firms and corporate legal departments that want a tool for legal research, contract analysis, and document review.
Pros:
- User-friendly interface
- Strong legal research and document analysis
- Useful for contract review and due diligence
- Practical for everyday legal workflows
Cons:
- Less specialized for very large-scale regulatory data review than dedicated eDiscovery tools
- Pricing may be a barrier for smaller firms
3. Kira Systems, now part of Litera
What it does: Kira is a contract analysis and due diligence platform that uses machine learning to identify and extract key clauses and data points from legal documents. It includes pre-trained models and also supports custom model training.
Why it is useful: Kira is especially effective when compliance review depends on finding specific provisions across a large contract set, such as privacy language, indemnities, IP clauses, or regulatory commitments.
Best fit/use case: Corporate legal departments, M&A teams, compliance officers, and law firms handling due diligence, contract abstraction, and contract portfolio review.
Pros:
- Strong clause extraction and contract analysis
- Customizable for specific review needs
- Efficient for high-volume due diligence
- Accurate for targeted contract review
Cons:
- Focused mainly on contracts
- Less suitable for emails or broader unstructured data
- Custom model training may take time to set up
4. Everlaw
What it does: Everlaw is a cloud-native eDiscovery platform with AI features such as predictive coding and clustering. It also includes litigation hold, case management, and collaboration tools.
Why it is useful: Everlaw helps teams quickly make sense of large document sets and collaborate on review. It is useful when compliance work overlaps with investigations, litigation, or regulatory requests.
Best fit/use case: Mid-sized to large law firms and corporate legal departments looking for a user-friendly eDiscovery platform with AI support.
Pros:
- Intuitive interface
- Strong collaboration features
- Effective AI for relevance and pattern detection
- Good for case management and document review
Cons:
- More focused on eDiscovery than broad compliance automation
- May be less specialized for non-litigation compliance workflows
5. Luminance
What it does: Luminance is an AI-powered legal platform built for document review, particularly in due diligence and transaction work. It analyzes contracts, identifies key clauses, and flags deviations from expected positions or compliance requirements. It also supports multiple languages.
Why it is useful: Luminance can accelerate review by quickly surfacing the clauses and exceptions that matter most. This is especially helpful in transactions where compliance risk needs to be assessed across many agreements.
Best fit/use case: Law firms and in-house legal teams handling M&A, high-volume contract review, and due diligence.
Pros:
- Strong for transaction review
- Good at identifying deviations and risks
- Multi-language support
- Easy to use
Cons:
- Primarily contract-focused
- Less suitable for broader compliance work involving communications or filings
6. DISCO AI
What it does: DISCO AI is a legal technology platform that supports eDiscovery, legal holds, and document review. Its AI features include clustering, categorization, and predictive coding to help teams work through large datasets more efficiently.
Why it is useful: DISCO AI helps legal teams handle investigations and regulatory matters more efficiently by highlighting themes, outliers, and potentially important documents.
Best fit/use case: Law firms and corporate legal departments that need a single platform for litigation, investigations, and compliance-related document review.
Pros:
- Strong eDiscovery and review tools
- User-friendly interface
- Integrated case management
- Scales well for large data sets
Cons:
- Less specialized for non-litigation compliance automation
- Dedicated compliance features may be limited compared with niche tools
How to Choose the Right AI Tool
The best platform depends on your review needs, data types, and internal resources. Before choosing a tool, consider the following:
- Scope of review: Are you focused on contracts, investigations, regulatory requests, or internal communications?
- Data volume and format: Are you reviewing a few hundred contracts or millions of emails and records?
- Integration needs: Will the tool fit into your existing legal and compliance workflow?
- Ease of use: Can your team adopt it without heavy training?
- Budget and pricing model: Does the pricing structure match your expected usage?
- Regulatory focus: Does the tool support the specific rules or compliance areas that matter to your organization?
- Vendor support: Does the provider offer implementation help, training, and ongoing support?
Pricing and Value Considerations
When evaluating AI for compliance review, look at total value, not just upfront cost. A more expensive tool may still be the better choice if it saves time, reduces risk, and improves review quality.
Key value factors include:
- Cost reduction: Less manual review means lower labor costs.
- Risk mitigation: Better issue detection can help avoid fines, disputes, and reputational damage.
- Efficiency gains: Faster review cycles support quicker decision-making and response times.
- Scalability: AI tools can handle more data without requiring the same increase in headcount.
Common pricing models include:
- Subscription pricing: Monthly or annual licensing, often based on users or features
- Per-project or per-document pricing: Useful for discrete review matters
- Enterprise licensing: Custom agreements for larger organizations with ongoing needs
When comparing vendors, include implementation costs, training time, and any IT integration work in your total cost estimate.
Frequently Asked Questions
Can AI replace human compliance professionals?
No. AI is best used to support compliance work, not replace it. It can identify patterns, extract data, and flag issues, but human judgment is still necessary for interpretation, escalation, and final decisions.
How accurate is AI for compliance review?
Accuracy depends on the tool, the quality of the training data, and the complexity of the review task. Strong systems can be very effective, but human oversight is still essential.
What kinds of data can AI review?
AI can review contracts, policies, emails, chat logs, financial records, and other text-based materials. Some platforms can also handle audio or video, depending on their features.
Is AI hard to implement for compliance review?
It depends on the platform. Some cloud-based tools are relatively easy to deploy, while others require more setup, training, and integration work. Many vendors provide onboarding support.
How does AI help with data privacy compliance?
AI can help identify personal data, flag potential issues in documents and communications, support data subject access requests, and review agreements for privacy-related risks. It is especially useful when teams need to search large volumes of records quickly.
Conclusion
AI is becoming an important part of modern compliance review. It can reduce manual work, improve consistency, and help legal and compliance teams find issues faster. It is not a substitute for professional judgment, but it is a practical way to make review processes more efficient and scalable.
For organizations evaluating how to use AI for compliance review, the key is to match the tool to the task. Contract analysis, eDiscovery, regulatory response, and internal investigations all call for different capabilities. With the right workflow and the right platform, AI can turn compliance review from a slow manual burden into a more structured, data-driven process.