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Generative AI pilots reporting 95% failure, finds MIT study; Author explains the ‘learning gap’ – Technology News

By Advanced AI EditorAugust 19, 2025No Comments3 Mins Read
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The world is all about artificial intelligence these days, and in the coming years, the use, research and power of AI will only increase. However, despite a number of AI platforms and research methodologies, the success rate of generative AI pilots has reportedly been only 5%, Fortune.com stated, citing a recent report by MIT’s NANDA initiative titled “The GenAI Divide: State of AI in Business 2025.”

The report revealed that while generative AI has been promising for enterprises, most of the initiatives aimed at driving growth are falling flat, the report mentioned. The study found out that merely 5% of AI pilot programs achieved rapid revenue acceleration, where the vast majority delivered little to no measurable impact. 

The study was based on 150 interviews with leaders, a survey of 350 employees, and an analysis of 300 public AI deployments. It claimed an evident divide between success stories and stalled projects.

What’s causing the ‘95% failure’? Lead author of the study explains

The lead author of the project NANDA at MIT, Aditya Challapally, explained the reason behind the picture the study has painted. He said the younger startups are excelling in generative AI as they are focused.

“Some large companies’ pilots and younger startups are really excelling with generative AI,” he was quoted as saying by Fortune.com “Startups led by 19- or 20-year-olds, for example, have seen revenues jump from zero to $20 million in a year,” he added.

“It’s because they pick one pain point, execute well, and partner smartly with companies who use their tools,” Challapally further said.

He highlighted how the “learning gap” is causing the massive failure of generative AI in implementation. 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.

The lead author of the study further stressed on the allocation of funding for the resource. He said more than 50% of generative AI budgets are absorbed by sales and marketing tools, and hence, the study stated, eliminating business process outsourcing, cutting external agency costs, and streamlining operations could ease the trouble.

The role of AI deployments 

It is pertinent to note always how companies are purchasing or making AIs. Many buy it from vendors or build it through partnerships, where many have devoted time to have their own generative AI systems in 2025. However, the report said MIT’s research saw most of the companies failing while going all solo on the generative AI. .

“Almost everywhere we went, enterprises were trying to build their own tool,” Challapally said, quote Fortune.com.



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