Trust in AI: Earning Confidence Through Evidence

Trust in an AI system depends on whether people can judge its outputs, understand its limits, and know what happens when it fails. This panel explores how evaluation, transparency, accountability, and user experience contribute to confidence in enterprise AI. Discuss how teams can make limitations visible and respond to feedback. Attendees will gain practical ideas for supporting informed use and aligning expectations with demonstrated performance.

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