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Four AI predictions for 2025

While the momentum behind the development of large models might fade, there will be other advances

There was nothing new in AI in 2024 that matched the sheer “wow” factor of using ChatGPT for the first time, but rapid improvements in the underlying technology still kept the field humming. For 2025, this is how I see things panning out.

Will AI development hit a wall?

In 2025, that momentum will fade. Even some of the tech industry’s biggest optimists have conceded in recent weeks that simply throwing more data and computing power into training ever-larger AI models — a reliable source of improvement in the past — is starting to yield diminishing returns. In the longer term, this robs AI of a dependable source of improvement. At least in the next 12 months, though, other advances should more than take up the slack.

The most promising developments look like coming from models that carry out a series of steps before returning an answer, allowing them to query and refine their first responses to deliver more “reasoned” results. It is debatable whether this is really comparable to human reasoning, but systems like OpenAI’s o3 still look like the most interesting advance since the emergence of AI chatbots.

Google, which regained its AI mojo late in the year after spending two years struggling to catch up with OpenAI, also showed how the new agent-like capabilities in AI could make life easier, such as tracking what you do in your browser and then offering to complete tasks for you. All these demos and prototypes still need to be turned into useful products, but they at least show that there is more than enough in the labs to keep the AI hype going.

Will AI’s ‘killer app’ emerge?

For most people, the rise of generative AI has meant constantly seeing prompts offering to complete your writing for you or edit your photos in ways you hadn’t thought of — unsought, occasionally useful tools that fall well short of transforming your life.

Next year is likely to bring the first demonstrations of apps that can intervene more directly: Absorbing all your digital information and learning from your actions so that they can act as virtual memory banks or take over entire aspects of your life. But, concerned about the unreliability of the technology, tech companies will be wary about rushing these out for mass use — and most users will be equally wary about trusting them.

Instead of true killer apps for AI, this means we’ll be left in the “AI in everything” world that technology users have already become accustomed to: Sometimes intrusive, sometimes helpful, and still not quite providing the really new experiences that would prove the AI era has truly arrived.

Will Nvidia’s GPUs still rule the tech world?

The chipmaker’s huge profits have made it the target of the most powerful tech companies, most of which are now designing their own AI chips. But Nvidia has been moving too fast for rivals, and while a quarter or two could be bumpy as it goes through a major product transition, its Blackwell product cycles should carry it through the year comfortably ahead.

That doesn’t mean others won’t make inroads. According to chipmaker Broadcom, three of the biggest tech companies are to use their in-house chip designs for supercomputing “clusters” with 1mn chips each in 2027. That is 10 times the size of Elon Musk’s Colossus system, thought to be the largest cluster of AI chips currently in use.

Even as its market share starts to erode, though, Nvidia’s software still represents a considerable moat for its business, and by the end of the year it should be on the verge of another important new product cycle.

Will the stock market’s AI boom continue? 

With Big Tech in the midst of an AI race that its leaders believe will determine the future shape of their industry, one of the main forces behind the AI capital spending boom will remain in place. Also, as some companies start to claim big — if unproven — results from applying the technology in their own businesses, many others will feel they have to keep spending, even if they haven’t worked out yet how to use AI productively.

Whether this is enough for investors to keep throwing their money at AI is another matter. That will depend on other factors, such as the stock market’s confidence in the deregulatory and tax-cutting intentions of the new Trump administration and the readiness of the Federal Reserve to continue with monetary policy easing.

It all points to a highly volatile year, with some big corrections along the way. But with enough liquidity, Wall Street could succumb to AI hype for some time yet.

richard.waters@ft.com

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