AI can assist your UX research analysis — but shouldn't lead it. Discover four responsible ways to use AI as a thought partner while keeping critical thinking and interpretation in your hands.
AI interviewers can conduct user interviews on your behalf, but they come with real limitations. Learn how they work, how well they perform, and the best use cases for adding them to your research toolkit.
Outcome-oriented design shifts how we approach UX in the AI era. Instead of designing single interfaces, designers now define adaptive frameworks that respond to individual user goals rather than optimizing for average user needs.
Although AI is (usually) good at editing, it doesn’t mean good prompting practices should be ignored. These 3 tips will help take AI edits to the next level.
As AI becomes central to service delivery, traditional service metrics must evolve — new measures will assess AI-to-AI performance, human-AI collaboration, data quality, and user trust.
When you outsource your analysis to AI, you risk more than just bad insights — you risk your credibility. Learn 4 reasons why relying on AI for qualitative analysis can backfire and why critical thinking still matters.
To build good products, start by identifying the problem, not the solution. Especially with AI, if you start with a technology, delivering real value to your users and customers will be difficult.
AI literacy is the ability to understand how AI works, use it effectively, and critically evaluate its output. But it isn’t a simple spectrum or just about how often someone uses AI—understanding, trust, and effective use vary widely.
A strong AI strategy is built by answering those three essential questions honestly. What is our core business? Are we chasing real value or just perception? And what specific problem are we actually trying to solve?
AI is reshaping service design—no longer just a tool, it’s now an active agent. Future services must compete on how well they interact with AI, not just humans.
To get better results from generative-AI chatbots, write CAREful prompts. Include context, what you’re asking the system to do, rules for how to do it, and examples of what you want.
Work with AI tools in UX the way you’d work with an intern: Treat their work as a first pass, double-check their facts, and provide specific instructions.
Product-centric design does not leverage design’s potential for creating long-term business value and profitability. Journey-centric design can activate this potential and optimize customer experiences.
Promptframes combine traditional wireframes with AI prompts to create content-rich prototypes. Ditch confusing placeholders using AI to quickly inspire feedback from your collaborators and users.
