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
"Getting to know what people care about in the organization helps tailor workshops to support those goals and gain buy-in."
Anne MamaghaniHow Your Organization's Generative Workshops Are Probably Going Wrong and How to Get Them Right
March 28, 2023
"The real breakthrough was when the pilgrim’s mechanical bird spoke both ways, braiding their words together to reach the summit."
Kurt McCullochFaster alone, further together: Rebuilding collaboration in the age of AI research
March 10, 2026
"Good design needs better PR and the government has to be actively involved in the process."
Sofía Delsordo Kassim VeraPublic Policy for Jalisco's Designers to Make Design Matter
December 8, 2021
"I hope you’ll come out of the day feeling energized and excited about the opportunities and the possibilities."
Christian CrumlishIntroduction by our Conference Chair
December 6, 2022
"Artificial intelligence is reshaping our workflows. Our roles are shifting."
Ebru NamaldiDesigning the Designer’s Journey: Scaling Teams, Culture, and Growth Through DesignOps
September 11, 2025
"Critiques maintain focus on the quality of our outcomes and sweat every pixel we put in the hands of our users."
Joseph MeersmanSweating the Pixel: Scaling Quality through Critique
June 10, 2021
"When we showed the Iceland Ministry of Foreign Affairs their portfolio, the Foreign Minister said, we have to pivot our innovation investments to early-stage catalytic innovations."
Milan Guenther Benjamin KumpfThe $212 billion ‘so what?’: unlocking impact in development cooperation
November 20, 2025
"Sharing your skills and teaching others can boost your confidence and professional development."
Kathleen AsjesResearch Democratization: the Good, the Bad and the Ugly
March 10, 2022
"Typing prompts is not the UX of the future. Integration into the interactive context where you work is better."
Josh Clark Veronika KindredSentient Design, AI, and the Radically Adaptive Experience (1st of 3 seminars)
January 15, 2025
