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Home ›› Artificial Intelligence ›› AI in UX

AI in UX

Read these first

Explore the future of design: AI-powered interfaces that adapt, stay human-focused, and build trust.

Article by Aroon Kumar
Beyond UI/UX: Designing Adaptive Experiences in the Age of AI
  • The article discusses the shift from fixed interfaces to real-time experiences, switching the role of designers from creating screens to guiding how systems operate.
  • The piece also stresses that, as experiences become personalized, they must maintain user trust, privacy, and authentic human connection.
Share:Beyond UI/UX: Designing Adaptive Experiences in the Age of AI
5 min read

Explore how design researchers can earn the trust and buy-in that give studies impact, even as AI shifts how teams work.

Article by Sara Fortier
Earning the Right to Research: Stakeholder Buy-In and Influence in the AI x UX Era
  • The article emphasizes that synthetic data and AI tools promise speed, but not the alignment or shared purpose that makes design research effective in solving design problems.
  • It asserts that meaningful human-centred design begins with trust and the permission to conduct research properly (i.e., strategically).
  • The piece outlines how to build stakeholder buy-in for design research through practical strategies that build influence piece by piece within an organization.
  • Adapted from the book Design Research Mastery, it offers grounded ways to enable impactful user studies in today’s AI-driven landscape.
Share:Earning the Right to Research: Stakeholder Buy-In and Influence in the AI x UX Era
12 min read

AI is changing how designers work — speeding up workflows, sparking creativity, and taking care of the tedious parts. But it’s not here to replace designers — it’s here to amplify their insight, empathy, and impact.

Article by Nayyer Abbas
AI Boosts for UI/UX Designers: Fast Growth with Smart Tools
  • The article explores how AI transforms UI/UX design by automating repetitive tasks, speeding up workflows, and enhancing creativity across ideation, prototyping, and research.
  • It argues that AI empowers rather than replaces designers, freeing them to focus on insight, empathy, and strategy while maintaining ethical and user-centered design.
Share:AI Boosts for UI/UX Designers: Fast Growth with Smart Tools
5 min read

When a traveler loses her bag, a simple UX flaw turns inconvenience into chaos. What if smart design and AI could turn that moment into a story of trust instead?

Article by Krystian M. Frahn
UX Promptly Needed: a Railway Digital Transformation Story
  • The article shows how poor UX design in railway lost and found systems creates frustration and inefficiency for passengers and staff.
  • It argues that applying human-centered design and AI-powered tools, such as QR-based tracking and digital reporting, could transform the process into a seamless, trust-building experience.
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3 min read

Trusting AI isn’t the goal — relying on it is. This article explores why human trust and AI reliance are worlds apart, and what UX designers should focus on to make AI feel dependable, not human.

Article by Verena Seibert-Giller
The Psychology of Trust in AI: Why “Relying on AI” Matters More than “Trusting It”
  • The article argues that “reliance,” not “trust,” is the right way to think about users’ relationship with AI.
  • It explains that human trust and AI reliance are driven by different psychological mechanisms.
  • The piece highlights that predictability, transparency, and control make users more willing to rely on AI.
  • It concludes that users don’t need to trust AI as a partner — only rely on it as a dependable tool.
Share:The Psychology of Trust in AI: Why “Relying on AI” Matters More than “Trusting It”
4 min read

AI’s promise isn’t about more tools — it’s about orchestrating them with purpose. This article shows why random experiments fail, and how systematic design can turn chaos into ‘Organizational AGI.’

Article by Yves Binda
Random Acts of Intelligence
  • The article critiques the “hammer mentality” of using AI without a clear purpose.
  • It argues that real progress lies in orchestrating existing AI patterns, not chasing new tools.
  • The piece warns that communication complexity — the modern Tower of Babel — is AI’s biggest challenge.
  • It calls for outcome-driven, ethical design to move from random acts to “Organizational AGI.”
Share:Random Acts of Intelligence
5 min read

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