Thanks to advances in deep learning, the capabilities of AI in UX design have evolved from basic task automation and data analysis to analyzing large volumes of user data. Today, AI enables companies to uncover and leverage intricate user patterns and trends, resulting in highly personalized services and predictive experiences. Three key benefits of using AI in digital product interactions include personalization, enhanced user assistance, and proactive recommendations.
Increasing personalization—a key aspect of successful user interfaces—is one of the most powerful ways AI enhances UX. By leveraging AI algorithms, designers can tailor content and functionality to meet individual users’ needs. Digital-first health service provider eMed UK, for example, uses advanced AI algorithms to analyze user health data, provide personalized health recommendations, and deliver real-time medical insights. The company uses natural language processing (NLP) to analyze spoken and written language from users to understand their health concerns and provide targeted responses during AI-run virtual consultations. eMed UK also uses machine learning (ML) techniques to identify patterns or anomalies in data from patients’ wearable devices and electronic health records to alert users to potential health risks to discuss with a medical professional.
I recently used AI technology to create a personalized experience for target users of a vehicle telematics platform. The platform would offer users insights into their driving habits (such as speed, fuel consumption, and braking patterns) and encourage safer and more eco-friendly driving practices. Insurers could use the platform’s data to enable usage-based insurance models, allowing for personalized premium plans based on individual driving behaviors rather than demographic generalizations.
