Artificial intelligence personalization selects or generates parts of an experience using signals about the current user. Those signals can include a query, visited pages, dwell time, device, location, account preferences and prior interactions.
A useful system changes only what supports the visitor's goal while preserving source accuracy, brand rules and privacy. Personalization should be evaluated for relevance and unintended discrimination. Users also need clear boundaries on what data is collected and how it shapes the experience.
Acronyms and aliases
AI personalization variantAI-powered personalization variant
General terms
Specialised terms
Related terms
Frequently asked questions
How does AI personalize a website?
It can infer visitor intent from current and prior signals, then rank or generate selected content blocks, search results and recommendations for that context.
What are the risks of AI personalization?
Risks include privacy loss, inaccurate assumptions, manipulation, filter bubbles and unequal treatment. Data minimization, transparency and evaluation help manage them.
