Name: AI adoption in focus at Davos
Uploaded: 2026-01-20T17:20:16.442Z
Duration: 3 min 7 s
Description: AI adoption is a key focus at the World Economic Forum in Davos, as OpenAI reports rapid growth and rising global demand for artificial intelligence. CNBC’s Deirdre Bosa has the latest.

AI adoption is a key focus at the World Economic Forum in Davos, as OpenAI reports rapid growth and rising global demand for artificial intelligence. CNBC’s Deirdre Bosa has the latest.

Davos

At the World Economic Forum in Davos, the conversation around artificial intelligence shifted from excitement over its potential to concerns about the sustainability of its rapid growth. OpenAI released new figures showing both compute and revenue have grown tenfold since 2023, surpassing $20 billion in annual recurring revenue, but experts highlighted the increasing difficulty of maintaining such growth rates as the company scales.

Industry leaders noted that OpenAI faces significant competition from firms like Anthropic and Google's Gemini, with the latter experiencing rapid user growth. The discussions emphasized that broader adoption, both in enterprise and among consumers, is now essential for AI investments to deliver returns, as infrastructure spending outpaces proven demand.

AI adoption in focus at Davos

Open AI out with some new numbers over the weekend. Try to put some AI bubble concerns to rest. Deidre Bosa has more in today's Tech Check. Dee. Hey, good morning, David. So Open AI's blog post over the weekend, it was supposed to quiet those bubble fears, but instead it exposed the bet. CFO Sarah Fryer laid out a simple premise. Revenue scales with compute, and so far that math has worked. Compute grew roughly 10 times from 2023 to 2025. Revenue did the same, topping $20 billion in annual recurring revenue last year. But it also sets a trap for the future. Sam Altman has said he expects Open AI to grow to hundreds of billions in revenue by 2030 against $1.4 trillion in infrastructure commitments over the next eight years. Now, that would require multiple doublings from an already large base, each doubling harder than the last. Now, you could look at Amazon Web Services as precedent. AWS had a nearly decade head start in cloud computing. It built a category. It scaled faster than any enterprise business ever had. Today, AWS, it is still the market leader, but its growth rate is slower than both Microsoft and Google, the other hyperscalers. This is just the law of large numbers. The bigger the base, the harder it is to keep growing at the same rate. AWS is now a hugely profitable, successful business, but that path is less clear for Open AI. It is chasing the same outcome, only faster, more expensive, and with far less room for error. It doesn't have other businesses that it's diversified into. And this is where bubble fears come in. When infrastructure is built ahead of proven broad-based demand, the math has to keep working or it unravels fast. Those pressures now showing up in the broader conversation. Just at Davos, David, last year it was a lot of the AI hype. This year, the focus has shifted to those bubble risks with warnings that AI investment needs much broader adoption to pay off. And that's really been a buzzword of this year, adoption. Yeah, adoption. Of course, adoption in the enterprise and by consumers, the competition from Anthropic in the enterprise, Gemini certainly, I don't know if it's in the lead, Dee, but you've been focused a lot on that as well and what it means for Open AI, which, by the way, has started to introduce the idea of an ad-supported business. Exactly, this goes right back to that point that I brought up, the law of large numbers. We looked at third-party data from similar web and Gemini's growth rate in November and December, what is it? It was nearly 30%, whereas Open AI has declined 6%. Open AI is still the leader, but that kind of growth that we're seeing from Gemini makes it really hard to believe that that sort of trajectory, that ratio that Sarah Fryer laid out over the weekend is possible to continue to achieve. So you mentioned Anthropic as well. We've been playing around with Cloud Code. It's been making just huge strides in enterprise. This is all sort of making it more difficult for an Open AI to get to these kinds of growth rates, and I make that AWS comparison because it had the lead for like seven years or something, and now you see that growth slowed. Open AI doesn't have that kind of lead. No, and it's a key, of course, as you well know, Dee. Thank you.

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Breakdown