The Human Side of AI Adoption: Lessons From the Field
Everyone is focused on model capabilities. Nobody is talking about why 60% of AI projects fail at adoption.
Why it matters
Organizational AI adoption success depends less on model power and more on change management, workforce readiness, and human factors. This MIT research surfaces the gap between AI capability and business execution that leaders actually need to solve.
The key facts
8 to knowMIT Sloan Review study on organizational AI adoption patterns
Dichotomy identified between AI capability hype and real-world adoption success rates
Focus on human/organizational factors in AI implementation
Field research from early adopter organizations
MIT Sloan Review analysis of field adoption patterns
Dichotomy identified between AI hype and actual deployment success rates
Human/organizational factors emerging as primary adoption friction points
Research-backed insights on change management for AI implementations
Go to the source
MIT Sloan Management Reviewsloanreview.mit.edu
Publisher excerpt: Carolyn Geason-Beissel/MIT SMR Not a day goes by without another article being published about how AI could disrupt yet another aspect of our business or personal lives. In recent years, AI adoption has indeed taken off. However, if you pay close attention, you’ll notice a dichotomy. Many examples…