Description
This talk will offer a clear, practical road map for using AI without sleepwalking into liability minefields. Drawing on real disputes, emerging case law, and live industry data, we'll explain where AI can go wrong in design, delivery, and operations, and what this means for contracts, professional duties, and insurance. Using vivid, real-world examples of AI hallucinations, flawed outputs, and disputed responsibility, we'll demystify what good practice looks like in reality. You'll learn how to cut through AI hype, how to embed internal processes and procedures, and how to structure effective internal training and implement proportionate governance, assurance, and documentation that satisfy clients, regulators, and insurers while still enabling innovation.
Key Learnings
- Learn about key legal and commercial risks when using AI in design, delivery, and operations, and how to avoid liability.
- Learn how to identify red-flag use cases for AI, and spot where additional checks, oversight, or contractual protection are needed.
- Learn how to design and embed internal AI governance, processes, and assurance in your organization.
- Learn how to structure effective internal AI training and guidance so teams use AI safely, ethically, and consistently while innovating.