MIT Report: 95% of Generative AI Pilots at Companies Are Failing

The GenAI Divide: State of AI in Business 2025, a new report published by MIT's NANDA initiative, reveals that while generative AI holds promise for enterprises, most initiatives to drive rapid revenue growth are falling flat. Fortune: Despite the rush to integrate powerful new models, about 5% of AI pilot programs achieve rapid revenue acceleration; the vast majority stall, delivering little to no measurable impact on P&L. The research -- based on 150 interviews with leaders, a survey of 350 employees, and an analysis of 300 public AI deployments -- paints a clear divide between success stories and stalled projects.

To unpack these findings, I spoke with Aditya Challapally, the lead author of the report, and a research contributor to project NANDA at MIT. 'Some large companies' pilots and younger startups are really excelling with generative AI,' Challapally said. Startups led by 19- or 20-year-olds, for example, 'have seen revenues jump from zero to $20 million in a year,' he said. 'It's because they pick one pain point, execute well, and partner smartly with companies who use their tools,' he added.

But for 95% of companies in the dataset, generative AI implementation is falling short. The core issue? Not the quality of the AI models, but the 'learning gap' for both tools and organizations. While executives often blame regulation or model performance, MIT's research points to flawed enterprise integration. Generic tools like ChatGPT excel for individuals because of their flexibility, but they stall in enterprise use since they don't learn from or adapt to workflows, Challapally explained.

Read more of this story at Slashdot.