AI Platform Evaluation Checklist

Texas Bar Books Staff

  1. Define Goals and Use Cases
    • Purpose: Identify specific tasks the AI will assist with, such as document review, contract analysis, legal research, or predictive analytics.
    • Scope: Define the boundaries of the AI’s role to ensure alignment with the firm’s or department’s needs.
  2. Assess Features and Functionality
    • Accuracy: Evaluate the platform’s ability to deliver precise and reliable results, particularly for complex legal tasks.
    • Customizability: Check if the platform can be tailored to your jurisdiction, practice area, and specific requirements.
  3. Evaluate Legal and Ethical Compliance
    • Confidentiality: Assess how the platform handles sensitive client data to ensure compliance with attorney-client privilege.
    • Data Ownership: Clarify who owns the data inputs and outputs, especially for proprietary legal analysis or content.
    • Jurisdictional Issues: Ensure the platform complies with data protection laws and regulations in your jurisdiction.
  4. Data Security and Privacy
    • Encryption: Confirm robust encryption for data storage and transmission.
    • Data Retention Policies: Understand how long the platform retains user data and whether it can be deleted upon request.
    • Access Control: Evaluate controls to restrict unauthorized access, such as user authentication and role-based permissions.
  5. Review Ethical Considerations
    • Bias and Fairness: Investigate whether the AI is free from biases that could negatively impact decision-making or case strategy.
    • Transparency: Assess the platform’s explainability — can it provide clear reasoning for its outputs?
    • Professional Obligations: Ensure the platform aligns with legal ethics rules.
  6. Vendor Due Diligence
    • Reputation: Research the vendor’s reputation, history, and client testimonials.
    • Support: Evaluate the availability and quality of technical support, training, and onboarding services.
    • Insurance: Inquire about insurance coverage for AI-related losses or claims.
    • Updates: Confirm that the vendor provides regular updates to keep the platform current with legal changes.
  7. Conduct Technical Assessment
    • Integration: Assess how well the platform integrates with existing systems (e.g., case management, billing, and document storage).
    • Scalability: Verify the platform can handle your workload as your practice grows.
    • User Experience: Test the interface for ease of use.
  8. Cost-Benefit Analysis
    • Pricing Model: Understand subscription costs, licensing fees, and any additional charges for upgrades or support.
    • Return on Investment: Estimate potential savings in time and resources versus the platform’s costs.
  9. Test Performance
    • Pilot Program: Run a small-scale trial to evaluate performance on real-world tasks.
    • Benchmarks: Compare the platform’s performance against human lawyers or competing tools on metrics, like speed, accuracy, and comprehensiveness.
  10. Legal Risks and Liability
    • Error Handling: Assess how the platform addresses errors in its analysis or output.
    • Indemnification: Review the vendor’s liability clauses in case of failures or inaccuracies.
    • Compliance Monitoring: Ensure the platform provides tools to help monitor ongoing compliance with legal standards.
  11. Seek Feedback
    • User Input: Gather feedback from other lawyers or staff who will use the platform.
    • Client Impact: Consider how the platform might affect client services, confidentiality, and trust.
  12. Continuous Monitoring
    • Post-Adoption Review: Periodically assess the platform’s performance, costs, and compliance to ensure it continues to meet your needs.
    • Emerging Trends: Stay updated on advancements in legal AI to ensure you’re not falling behind.