The Impact of AI on UX Design
summary
Booking.com builds an AI trip planner during a hackathon that uses OpenAI GPT via API but wraps it with company data so it never hallucinates — recommendations tie to live prices and availability from 30 million listings and 250 million guest reviews across a platform with 700 million monthly visitors. The system exposes booking flows inside chat, includes prompt-engineered personality and guardrails (blocks on exploitative requests), session resets, delete-conversation options, user feedback buttons, and explicitly keeps chat data out of model training.
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chapters (14)
- 0:00Introduction to AI in UX
- 2:56Booking.com company culture
- 4:08Understanding AI terminology
- 5:57Changing user expectations
- 7:01Booking.com's AI applications
- 7:52The AI Trip Planner case study
- 10:48Building an AI-powered product
- 12:35Enabling hyperpersonalization
- 13:57Designing nonlinear interactions
- 16:10Prompt engineering for AI
- 17:28Setting guardrails and limits
- 18:58Focusing on AI output quality
- 21:25Testing and feedback loops
- 22:55Future of design and AI
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