AI in Law: Opportunities, Risks, and Litigation Considerations

Artificial intelligence is now embedded in legal workflows — from document review to research tools — yet its rapid adoption has outpaced clarity around governance, compliance, and risk. Law firms and legal departments face a dual challenge: understanding how AI can responsibly support legal work, and ensuring that its use aligns with evolving regulatory, ethical, and privacy requirements.

It is widely accepted that AI-generated outputs require human review. What is less clearly understood, and increasingly important, is whether AI itself can be used to monitor, detect, and manage compliance risks, including those arising from AI use.

Today’s compliance landscape is shifting quickly. HIPAA compliance continues to evolve, states are expanding privacy regimes, and new AI-specific governance frameworks, such as the NIST AI Risk Management Framework and the EU AI Act, are raising expectations around transparency, oversight, and accountability. Meeting these obligations requires continuous monitoring, documentation, and defensible controls: areas where well-designed AI systems can provide meaningful support.

AI in Legal Practice vs. AI for Legal Compliance

Discussions about “AI in law” often conflate two separate concepts that are worth distinguishing.

AI used in the practice of law covers drafting assistance, legal research, summarization, and analytics. This category raises questions about accuracy, professional responsibility, and ethics.

AI used to support legal compliance covers monitoring regulatory obligations, flagging risk, and enabling audit readiness. This category focuses on oversight, controls, and defensibility — particularly when firms must demonstrate compliance to regulators, courts, or clients.

Both are relevant to modern legal teams, but they involve different tools, risks, and governance considerations. This article focuses primarily on the second: AI integrated into compliance workflows, and what firms need to know to use it responsibly.

What AI Can Do for Legal Compliance

Legal compliance increasingly requires analyzing large volumes of data across jurisdictions, systems, and timeframes—tasks that are difficult to scale manually. When implemented carefully, AI can assist with:

• Automated monitoring of regulatory obligations
• Contract and policy review for compliance gaps
• Risk detection and anomaly identification systems
• Workflow automation for audits and reporting

The efficiency gains are real: better pattern recognition across large datasets, scalable oversight as regulations evolve, and stronger documentation and audit trails when systems are properly configured.

It can’t be stated enough that AI supports compliance work—it does not replace legal judgment by skilled professionals. AI-generated insights must be reviewed, validated, and documented by qualified people to remain defensible.

Legal and Ethical Risks of Using AI in Law 

Leveraging AI tools to monitor compliance is considered by some as a “fox guarding the henhouse” scenario. After all, keeping a close eye on the use of AI in the legal industry is a particularly hot compliance topic. 

As such, it’s crucial to be aware of potential risks: 

• Data privacy exposure from AI processing sensitive information
• Algorithmic bias affecting internal investigations or decision-making
• Lack of transparency in automated systems
• Inaccurate or “hallucinated” outputs
• Overreliance on automation without sufficient human review
• AI-generated evidence challenges around authenticity, admissibility, and verification

From a business risk perspective, organizations have already faced significant fines, liability exposure, reputational harm, and operational disruption tied to data privacy failures, bias concerns, and overstated AI claims.¹

Governance and Oversight: Building Defensibility

The standard to aim for is defensibility, governance structures that can withstand regulatory scrutiny or litigation. Best practices include: 

• Defined human oversight and review protocols, particularly for high stakes decisions
• Vendor vetting and third-party risk management
• Documented and actively managed AI governance frameworks 
• Ongoing staff training and policy updates
• Clear policies on approved and prohibited AI tools
• Documentation standards that support defensibility 

Additional considerations may include: 

• Aligning safeguards with risk tiering (such as the EU AI Act’s framework)²
• Developing firm-specific contract and disclosure language
• Being transparent with clients and third parties about how AI is being used

90-Day Path to “Defensible by Design” 

Firms can make meaningful progress toward defensible AI governance within a focused three-month roadmap:

• Days 0 to 30 – Inventory current AI use, create a governance committee, draft policies, and select pilot workflows.
  
• Days 31 to 60 – Complete vendor reviews, implement access controls, conduct staff training, and enable logging and provenance tracking.
  
• Days 61 to 90 – Run pilots with verification processes, measure error rates, finalize disclosures and billing practices, and plan for scale. 

AI Vendor and Tool Checklist

When vetting AI tools and vendors, a strong starting checklist includes:

• Zero-retention inference
• Customer-managed encryption keys
• Security certifications (SOC 2/ISO)
• Business Associate Agreements (BAAs) where required
• Jailbreak and adversarial testing
• Change logs for model updates

Defensible AI Use Starts with the Right Partners

AI can strengthen both legal practice and compliance operations — but only when paired with human judgment, clear governance, and disciplined oversight. Firms should carefully vet AI vendors, establish clear internal policies, and monitor both regulatory developments and vendor claims.

Partnering with litigation support providers that prioritize security, compliance, and responsible technology use can also reduce risk. U.S. Legal Support works with law firms and corporate legal teams nationwide, delivering litigation support services — including records retrieval, court reporting, and trial services — with a careful, compliance-focused approach to technology and AI.

Sources: 

1. Spellbook. How Can AI Help with Regulatory Compliance Review? https://www.spellbook.legal/learn/regulatory-compliance-review
2. Bastion Technologies. EU AI Act Risk Classification Explained. https://bastion.tech/learn/eu-ai-act/risk-classification/

Julie Feller

Julie Feller is the Vice President of Marketing at U.S. Legal Support where she leads innovative marketing initiatives. With a proven track record in the legal industry, Juie previously served at Abacus Data Systems (now Caret Legal) where she played a pivotal role in providing cutting-edge technology platforms and services to legal professionals nationwide.