Machine Learning Times
EXCLUSIVE HIGHLIGHTS
AI Business Value Is Not an Oxymoron: How Predictive AI Delivers Real ROI for Enterprises
  Originally published in AI Realized Now “Shouldn’t a great...
How To Un-Botch Predictive AI: Business Metrics
  Originally published in Forbes Predictive AI offers tremendous potential...
2 More Ways To Hybridize Predictive AI And Generative AI
  Originally published in Forbes Predictive AI and generative AI...
How To Overcome Predictive AI’s Everyday Failure
  Originally published in Forbes Executives know the importance of predictive...
SHARE THIS:

2 days ago
The great AI hype correction of 2025

 

Originally published on MIT Technology Review, December 15, 2025.

Four ways to think about this year’s reckoning

Some disillusionment was inevitable. When OpenAI released a free web app called ChatGPT in late 2022, it changed the course of an entire industry—and several world economies. Millions of people started talking to their computers, and their computers started talking back. We were enchanted, and we expected more.

We got it. Technology companies scrambled to stay ahead, putting out rival products that outdid one another with each new release: voice, images, video. With nonstop one-upmanship, AI companies have presented each new product drop as a major breakthrough, reinforcing a widespread faith that this technology would just keep getting better. Boosters told us that progress was exponential. They posted charts plotting how far we’d come since last year’s models: Look how the line goes up! Generative AI could do anything, it seemed.

Well, 2025 has been a year of reckoning.

This story is part of MIT Technology Review’s Hype Correction package, a series that resets expectations about what AI is, what it makes possible, and where we go next.

For a start, the heads of the top AI companies made promises they couldn’t keep. They told us that generative AI would replace the white-collar workforce, bring about an age of abundance, make scientific discoveries, and help find new cures for disease. FOMO across the world’s economies, at least in the Global North, made CEOs tear up their playbooks and try to get in on the action.

That’s when the shine started to come off. Though the technology may have been billed as a universal multitool that could revamp outdated business processes and cut costs, a number of studies published this year suggest that firms are failing to make the AI pixie dust work its magic. Surveys and trackers from a range of sources, including the US Census Bureau and Stanford University, have found that business uptake of AI tools is stalling. And when the tools do get tried out, many projects stay stuck in the pilot stage. Without broad buy-in across the economy it is not clear how the big AI companies will ever recoup the incredible amounts they’ve already spent in this race.

To continue reading this article, click here.

Comments are closed.