Everyone is talking about AI, but many of the initial efforts have failed to achieve the desired results. This panel presentation will highlight three ways that vehicle validation teams are using AI effectively today: • AI driver simulation allows engineers working on driver monitoring systems to quickly test many more scenarios than is feasible with real, live humans. • AI video labelling makes it much easier to find and analyze important events in ground-monitoring video • AI chat interfaces can help engineers identify difficult-to-spot patterns and anomalies, but only if they draw from properly structured data.

• Throwing a general-purpose large language model at validation problems is unlikely to succeed unless your foundational data is well structured, and you have agents trained engineering workflows.
• AI excels at completing repetitive tasks quickly and consistently.
• When validation teams use AI in carefully targeted ways, they can improve productivity, reduce costs, and enhance the quality of their products.