Navigating AI-Driven Change in Insurance (On-Demand)

Course Description

This program examines how AI is affecting the legal landscape for both insurers and policyholders. As AI tools are increasingly used in underwriting, claims handling, fraud detection, and customer interactions, they introduce new efficiencies—but also significant legal risks. The program explores how traditional doctrines such as bad faith, unfair discrimination, and coverage interpretation apply when decisions are driven or influenced by algorithmic systems, and highlights emerging regulatory expectations around transparency, governance, and fairness. In that context, the course explores litigation issues such as AI-related discovery, evidentiary challenges, and evolving strategies for both insurer-side and policyholder counsel. The program also explores the impact of these developments on the insurance marketplace and identifies future risks and developments to monitor.

Principles

• Existing legal principles still govern AI-assisted insurance decisions.
• Responsible AI requires governance, transparency, and human accountability.
• AI is reshaping insurance litigation, discovery, and evidentiary practice.
• Attorneys must anticipate evolving regulatory expectations and emerging legal risks.

Syllabus

1. Introduction to artificial intelligence in the insurance context
   • Definitions and key concepts relevant to legal practitioners
   • Overview of AI adoption across the insurance lifecycle
2. Use of AI in insurance operations
   • Underwriting and pricing models
   • Claims handling and automation
   • Fraud detection and customer-facing tools
3. Legal implications for insurers
   • Bad faith risk in AI-assisted claims decisions
   • Unfair discrimination and disparate impact concerns
   • Explainability and transparency challenges
   • Vendor management and third-party liability
   • Data privacy and cybersecurity obligations
4. Legal implications for policyholders
   • Challenging AI-driven claim determinations
   • Discovery and evidentiary issues involving algorithms
   • Privacy considerations related to data collection and use
   • Coverage interpretation and reliance on automated tools
5. Litigation considerations and emerging trends
   • Common causes of action involving AI
   • Discovery strategies and disputes over proprietary models
   • Role of expert testimony in AI-related cases
6. Regulatory landscape and compliance considerations
   • State insurance regulatory developments
   • Federal regulatory developments
   • International regulation
   • NAIC guidance and principles
7. Impact of AI on Insurance Products
   • Considerations for “traditional policies”
   • Development of new insurance products
8. Practical guidance for attorneys
   • Advising insurer clients on AI governance and compliance
   • Representing policyholders in AI-related disputes
   • Best practices for risk mitigation and litigation strategy
9. Future trends and legal developments to watch
   • Evolving regulatory requirements
   • Increased scrutiny of algorithmic decision-making
   • Long-term implications for insurance law and practice