Based on recent reports and analysis from experts like Bill Gates and data from firms like Massachusetts Institute of Technology (MIT) and Gartner, it is highly likely that a vast majority of AI companies and projects will fail or fail to deliver significant value in the coming years.

Gates said that his opinion is not a product of pure speculation. Stating that we are in the middle of an AI bubble, he pointed to the example of “tulip mania” during the 1630s in the Netherlands. During this period, the price of tulips soared for several years only to suddenly crash.

“That’s not where we are,” Gates said. Instead, he compared the AI bubble to the dot-com era when several internet-based companies became overvalued, leading to a significant crash.

Gates’ views have a stark similarity with a Massachusetts Institute of Technology (MIT) study that claimed that 95% of organizations are getting zero return, despite $30–40 billion in enterprise investment into Gen AI. MIT published a report in September last year titled ‘The GenAI Divide: State of AI in Business 2025’, which said that only 5% of integrated AI pilots are extracting millions in value, while the vast majority remain stuck with no measurable P&L (profit & loss) impact.

The study says that more than 80 % of organizations have explored or piloted tools like OpenAI’s ChatGPT and Microsoft’s Copilot. Nearly 40% reported deployment of these tools.

However, these AI tools, as per the study, enhance individual productivity primarily with no P&L performance. “Most fail due to brittle workflows, lack of contextual learning, and misalignment with day-to-day operations,” the study highlighted.

So that more than 90% of the AI companies make common mistake in project management and technology implementation rather than investing in fundamentals like observability, validation and integration. In the majority cases the poor quality of input produced useless or poor quality out puts. Similarly, weak data quality and rigid processes can derail AI initiatives long before model performance comes into play.

So that we can conclude that majority of the AI companies will fail due to their poor data quality, lack of clear business value, high operational costs and intense competition. Most AI ventures are “solutions chasing problems,” lacking a real, sustainable business model beyond. So, please think before investing in those companies.