An AI-driven UX vision goes beyond usability — it defines how intelligent systems enhance the experience.

• Create experiences that learn, adapt, and respond to user intent.
• Use AI to anticipate needs, reduce friction, and personalise journeys.
• Align model capabilities with the long-term product vision.

AI allows goals to be tied directly to measurable improvements in behaviour and relevance.

• Increase relevance through personalised content, product ranking, and intent prediction.
• Reduce bounce and hesitation by surfacing the right information at the right moment.
• Improve conversion by using predictive models.
• Use model performance metrics (precision, recall, ranking quality, embeddings similarity) alongside UX KPIs.

Integrating AI into UX requires a structured plan connecting model maturity, data, and user flows.

• Map where AI adds value along the journey (landing, discovery, evaluation, decision).
• Define which model types support each step.
• Test AI-driven experiences through experimentation (A/B, holdouts, model comparisons).
• Plan for responsible use: bias checks, transparency, fallback behaviours when models fail.
• Align design system components with AI patterns (adaptive UI, conversational layers, contextual helpers).