Log in or create a free Rosenverse account to watch this video.
Log in Create free account100s of community videos are available to free members. Conference talks are generally available to Gold members.
Why AI projects fail (and what we can do about it)
Summary
Most AI projects fail. Somewhere between 50-90% of them, which is double the rate of more traditional tech projects. This Rosenverse Session will draw on years of Carnegie Mellon HCII research to dive into the five traps that AI projects can fall into, and then talk about what designers and project managers can do to avoid those traps. Including one startling finding: user-centered design alone isn’t enough.
Key Insights
-
•
Most AI projects fail due to choosing the wrong problems rather than poor execution.
-
•
The AI innovation gap occurs because data scientists focus on technically hard but low-value problems.
-
•
User-centered design alone often identifies problems unsuitable for AI solutions.
-
•
AI works best for low-risk, moderate accuracy (~90%), narrow tasks like spam filtering or smart text suggestions.
-
•
Executives push AI fast to avoid falling behind, risking deployments without clear user or business value.
-
•
Consequences scanning is a vital method to detect and mitigate ethical risks before AI product launch.
-
•
Matchmaking AI capabilities with real user needs and organizational goals increases project success.
-
•
Agents add new AI capabilities to sense, think, and act, requiring adapted design processes.
-
•
AI lacks context, aesthetic taste, and common sense—designers must provide these to create effective AI products.
-
•
There is currently little corporate or legal accountability for AI ethics; responsibility largely falls to product teams.
Notable Quotes
"Welcome to the AI party, we've got 10 years of research to share."
"Executives said it's better to go fast and fail than to go slow and succeed."
"AI can be magical, but it's also just not that smart."
"Don Norman was named the top accomplished woman in UX by AI, even though Don is a man."
"Companies hunt for AI innovation in technically challenging areas instead of simpler, more valuable places."
"Most AI fails because projects require near perfect accuracy, which AI can't reliably deliver."
"The traditional user-centered design process doesn't work well for AI problems."
"Matchmaking connects AI capabilities to user needs so you find the low hanging fruit projects."
"AI struggles with context, taste, and common sense, and designers bring that to the table."
"Consequences scanning helps detect unintended harms and risks before launching AI features."
Or choose a question:
More Videos
"Everyone wants to have an impact on the decisions being made no matter what the role is called."
Jess GrecoClaiming your power: Practical tools for amplifying your unique voice
March 13, 2025
"This isn’t about Skynet; it’s about simple signals of awareness that adapt to immediate context."
Josh Clark Veronika KindredSentient Scenes and Radically Adaptive Experiences
June 11, 2025
"Advanced logic, matrix questioning, AI survey design creation — these are baseline capabilities you should expect from any modern survey tool."
Aleksandra Korczynska Caroline Jarrett Justyna ParmeeSurvey Tools
March 12, 2026
"Involving partners means tell me and I forget, show me and I may remember, involve me and I will understand."
Anat Fintzi Rachel MinnicksDelivering at Scale: Making Traction with Resistant Partners
June 9, 2022
"Every few years consultants come in and tidy up our mess, but as soon as they leave, we mess it all up again."
Peter MorvilleThe Architecture of Understanding
May 13, 2015
"Design portfolios are filled with slop when people lean too much on AI; you lose the human effort that makes design meaningful."
Paul FordNew work, new words: A glossary for AI
June 9, 2026
"We still have so much more work to do and things to learn."
Ariel KennanTheme Two Intro
November 17, 2022
"Rivian told Volkswagen, You tell us how to make a software-based vehicle; we’ll build the frame around the computer system and sensors."
James RamptonThe Basics of Automotive UX & Why Phones Are a Part of That Future
July 25, 2024
"Concept testing is about testing ideas before development to confirm there is a real need for the product."
Michaela MoraAdvanced Concept Testing Approaches To Guide Product Development and Business Decisions
March 11, 2022
