Contracting in the Age of AI and Emerging Technologies: Legal Frameworks, Risk Allocation, and Practical Drafting Strategies

Artificial intelligence is no longer a futuristic concept - it is embedded in enterprise software, vendor relationships, and client deliverables at an increasing rate. Yet most standard commercial contracts were never designed to address the unique risks that AI systems and emerging technologies introduce: opaque decision-making, hallucinated outputs, shifting model behavior, and unresolved questions around intellectual property ownership and data privacy.

This webinar equips attorneys, in-house counsel, and business professionals with the practical tools needed to identify AI and technology-related risks and negotiate contracts that actually address them. Drawing on recent developments in AI regulation, emerging case law, and real-world deal experience, this session bridges the gap between rapidly evolving technology and the contracts that govern it.

Whether you are reviewing a SaaS agreement with embedded AI features, negotiating an AI development or licensing deal, or advising clients who are deploying AI internally, this webinar will give you a concrete framework for spotting issues and drafting smarter.

Learning Objectives: 

1. Identify the key categories of AI and technology risk that must be addressed in commercial contracts, including accuracy, bias, explainability, and model drift
2. Recognize how standard contract provisions fail when applied to AI systems, and understand why boilerplate representations, warranties, and limitation-of-liability clauses require AI-specific tailoring
3. Negotiate and draft AI-specific representations and warranties, including output accuracy standards, training data provenance, and model performance benchmarks
4. Allocate liability appropriately in technology AI contracts by distinguishing between vendor-side and customer-side risk, and understanding when indemnification carve-outs for AI outputs are enforceable
5. Apply data privacy and security obligations relevant to technology and AI systems under frameworks such as GDPR, CCPA, and emerging U.S. state AI laws, and translate those obligations into enforceable contract language