To be fair, it's hard to see this not ending in a market massacre. The industry's current winner-takes-most mentality means the bets are big and bold, but the market cannot support dozens of large independent AI labs or hundreds of application layer startups. That's the definition of a bubble environment, and if it bursts, the only question is how bad it will be: a severe correction or a collapse.
Looking ahead
This was just a quick look back at some key themes in 2025, but there was so much more happening. We didn't even mention above how capable AI video synthesis models have become this year, with Google's Veo 3 adding sound generation and Wan 2.2 through 2.5 offering open-weight AI video models that could easily be mistaken for real products from a camera.
If 2023 and 2024 were defined by AI prophecy—that is, by sweeping claims about an impending superintelligence and a rupture in civilization—then 2025 was the year those claims collided with the intractable realities of technology, economics, and human behavior. The AI systems that dominated headlines this year turned out to be mere tools. These instruments were sometimes powerful, sometimes fragile, and often misunderstood by the people who used them, in part because of the prophecy surrounding them.
The collapse of the “reasoning mystique,” the legal reckoning of training data, the psychological costs of anthropomorphic chatbots, and ever-increasing infrastructure demands all point to the same conclusion: the era of institutions that present AI as an oracle is coming to an end. What replaces them is messier and less romantic, but far more consequential: a phase in which these systems are judged for what they actually do, who they harm, who benefits from them, and what it costs to maintain them.
None of this means that progress has stopped. AI research will continue and future models will improve in real and meaningful ways. But improvement is no longer synonymous with transcendence. Success increasingly looks like reliability rather than spectacle, integration rather than disruption, and responsibility rather than awe. In this sense, 2025 cannot be remembered as the year when AI changed everything, but as the year when AI stopped pretending that it already did. The prophet has been demoted. The product remains. What comes next will depend less on miracles and more on the people who choose how, where, and whether these tools are used at all.
