Daily analysis of why 85% of AI projects fail to reach production, featuring insights from MIT, Reuters, Wall Street Journal, Harvard Business Review, and more. Learn from others' mistakes before they become yours.
A groundbreaking MIT study reveals that 95% of attempts to incorporate generative AI into business are failing. Despite $200B invested in AI in 2025, AI tools complete only 30% of real-world office tasks. Only 5% of businesses succeed at "rapid revenue acceleration."
The Bank of England warned that AI stock valuations echo the dotcom bubble peak, with 30% of the S&P 500 concentrated in just 5 AI companies—the highest in 50 years. "The risk of a sharp market correction has increased," the BoE's Financial Policy Committee stated.
Research shows that even the best AI products successfully complete just 30% of real-world office tasks assigned to them, with most doing significantly worse. Yet companies invested $200B in AI in 2025 alone, expecting AI to revolutionize productivity.
Mark Zuckerberg admitted he would rather "misspend a couple of hundred billion dollars" than risk being late to the AI expansion. This statement reveals the FOMO-driven spending that's pushing AI valuations to unsustainable levels.
Share valuations based on past earnings are the most stretched since the dotcom bubble 25 years ago. Fund managers call AI stocks the "most crowded trade" in 50 years. History suggests a correction is inevitable.
70-80% of AI projects in IT organizations fail, not because of the technology itself but due to strategic and implementation challenges. The most common issue? Poor data quality and lack of clear business objectives.
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