Artificial Intelligence Articles & Videos

  • Facilitating AI-Enhanced Workshops: From Ideation to Action

    Improve AI-enhanced workshops by narrowing ideas with clear criteria, allowing time to prompt, encouraging collaboration, and documenting results.

  • The Future-Proof Designer

    Top product experts share four strategies for remaining indispensable as AI changes UI design, accelerates feature production, and reshapes data analysis.

  • 4 Tips for Preparing AI-Enhanced Workshops

    Plan AI-enhanced workshops by preparing warmup activities involving AI, uploading context files, creating custom AIs, and providing adaptable sample prompts.

  • AI as a Creative Teammate

    AI acts as a creative teammate in group settings as it does for solo work. Thoughtful facilitation ensures teams leverage AI effectively in workshops and critiques.

  • AI Chatbots Discourage Error Checking

    AI hallucinations threaten the usefulness of LLM-generated text in professional environments, but today’s LLMs encourage users to take outputs at face value.

  • Why I’m Not Worried About My UX Job in the Era of AI

    AI is a new tool, not a replacement for UX professionals.

  • AI Design Tools Are Marginally Better: Status Update

    Despite improvements in narrow-scope AI design tools, most design-specific AI cannot replicate human designers’ output quality.

  • How AI Models Are Trained

    Training modern LLMs is a costly process that shapes the model’s outputs and involves unsupervised, supervised, and reinforcement learning.

  • Prompt Suggestions

    System-generated suggestions for AI prompts must be contextually relevant, personalized, and specific to the task and the user’s level of experience.

  • Product-Specific GenAI Needs to Write for the Web

    Generative-AI outputs need to be concise, scannable, follow the inverted pyramid, and use plain language.

  • Four AI Superpowers: Where AI Improves Products

    When using AI consider its four "superpowers": content creation, summarization, basic data analysis, and perspective taking.

  • The Return of the UX Generalist

    AI advances make UX generalists valuable, reversing the trend toward specialization. Understanding multiple disciplines is increasingly important.

  • Discoverability of AI Features: Learn from Amazon’s Mistakes

    Even AI features that offer value won’t be used if people don’t notice them. Consider existing mental models and design best practices to increase engagement.

  • UX Leads Adoption of AI Chat

    UX ranks among top fields adopting AI, mostly in writing, design, and coding tasks — though complex or human-centric UX activities remain largely AI-free

  • AI Adoption in the Workplace Still Low, 2 Years Later

    Designers may think AI features are now familiar to our users, but recent research suggests that adoption is still lower than we might think.

  • Scope in Generative AI Features

    When designing AI product features, scope shapes key decisions. Research shows that focused AI features lead to better user understanding and adoption.

  • Common-Sense AI Integration: Lessons from the Cofounder of Condens

    Experience in the context of a UX-research platform shows that AI can be integrated well in focused tasks but isn’t capable of independent complex analysis.

  • How Service Design Will Evolve with AI Agents

    AI will force the transformation of service design by introducing new actors, shifting user dynamics, and redefining success metrics.

  • AI Hallucinations: What Designers Need to Know

    Plausible but incorrect AI responses create design challenges and user distrust. Discover evidence-based UI patterns to help users identify fabrications.

  • The UX Reckoning: Prepare for 2025 and Beyond

    In 2025, reevaluate tactics; use AI to deliver user value; and develop deep UX skills, instead of relying on toolkits.