Search Results for « AI-assisted UX evaluation »

Artificial intelligence (AI) has made significant advances in its ability to learn from existing data and generate novel solutions, increasingly transforming the landscape of design practice across disciplines. Its integration into design processes extends beyond improving operational efficiency to reshaping established approaches to decision-making, collaboration, and design practice throughout the product and service lifecycle. While research on AI-assisted design has examined how AI can be integrated into design processes, less attention has been paid to how such integration is enacted in day-to-day practice and affects design values across disciplines, particularly product engineering, service, and UI/UX design. This study addresses this gap through a series of workshops with design practitioners, examining how AI supports real-world design tasks and its impact on design values. Distinct from prior work, our study proposes a novel cross-disciplinary AI-assisted design framework comprising of four AI assistance types and twelve design activities based on practitioners’ experiential reports of AI use in industry. Our findings show that although designers across all three disciplines engage AI across all twelve activities, differences in disciplinary priorities, the nature of design outputs, and the application of professional expertise shape how and when AI is used and how design value is perceived. We further identify how AI use enhances and impairs different design values, revealing potential trade-offs between these outcomes. This paper contributes to a more comprehensive understanding of AI-integrated design practice by developing a cross-disciplinary framework that helps researchers and practitioners deploy AI more effectively across different design stages and disciplines.

Abstract Artificial Intelligence (AI) is typically considered an efficiency tool in user experience (UX). Far less attention is paid to its potential to structure reflection. The AI-supported UX Strategy Evaluator, created by German UPA’s UX Strategy Working Group, addresses this gap by posing questions to UX strategists and UX managers, rather than attempting to provide answers or best practices. This paper describes its design principles and development, grounded in the iterative development of a UX strategy checklist to identify which skills, information, and attitudes are relevant for strategic UX work. In addition, it describes a first exploration in a workshop with 13 participants at the conference Mensch & Computer 2025. Initial findings indicate that the question-based approach encourages participants to make assumptions explicit and fosters dialogue. The article concludes with areas for improvement and outlines future work.