CNBC's "Fast Money" team discusses the tech trade, the future of AI, data center demand and more with Rick Sherlund, senior advisor at Wedbush.

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The release of Open AI's ChatGPT has accelerated the development of artificial intelligence and warnings about its impact on society.

Rise of AI

Rick Sherlin, founder of Sherlin Partners and senior advisor at Wedbush Investment Banking, anticipates a shift in the artificial intelligence (A.I.) market from broad enthusiasm to a more selective environment as enterprise adoption increases. He predicts that as A.I. becomes integrated into business processes and workflows, the demand on large language models (LLMs) for inference will surge, stressing their current capabilities.

Sherlin expects this trend to drive significant demand for data centers, with supply likely lagging due to resource constraints. He also foresees a robust IPO market for private A.I. companies, increased mergers and acquisitions as enterprises seek A.I. capabilities, and a highly competitive LLM landscape with market leaders moving up the technology stack.

LLMs will be stressed by enterprise systems

Our next guest expects the A.I. trade to shift from broad enthusiasm to a more selective environment in the New Year. Wall Street legend Rick Sherlin is founder of Sherlin Partners and recently joined Wedbush Investment Banking as a senior advisor. Rick great to have you with us. Nice to see you. Melissa thanks for having me. And I should caution you that I no longer wear the analyst hat. So I'm going to be ducking some stock questions probably. That is fine. We want to get into your head Rick in terms of how you're thinking about this A.I. trade. So when you say shift from broad enthusiasm to being more selective what do you mean. And you know what we saw today in terms of the enthusiasm behind the hardware names versus some of the others. You know does that play into your thinking. I think this year has been one of kind of a monolithic trade. People think of the Max 7. It's now about 35 percent of the S&P. But I think 2026 you're going to see that trade broaden out very substantially. You've got a whole universe of SAS companies that the streets kind of looking beyond right now. There are some issues with respect to the architectural architecture flexible enough to accommodate A.I. is the business model at risk. So they've been out of favor. I do think you're going to see some of those come back where they've made good progress on both sides of adopting A.I. and the business model changes. You'll see a very robust IPO market because there are a lot of the private A.I. companies that have gotten to scale. And some of the SAS companies that didn't get out in the peak of the market in 2021 will likely be coming coming to market where they've made good traction on A.I. and the business model shifts. M&A of course is going to be a big thing next year. All the big enterprise companies need to add A.I. into their own architecture. And an easy way to do that is through acquisitions. So I think that all the derivative beneficiaries of A.I. in the streets and you guys have been looking at pretty closely I think there's a lot more of that that we'll see next year not just within software but broadly across the economy. So it will go ahead. Yes sorry Rick. Sorry to cut you off because that's exactly where I wanted to go and to better understand your thoughts. And I'm not going to ask you to pick stocks here. But when you talk about enterprise adoption and really really the follow through from the A.I. are we talking about the industrial sector and people finally banks places that have had a great run. Industrials have rallied all year. I think on some level because they were already running their business more efficiently. Are you really talking though about the platforms a little closer to home especially whether you are talking about the hardware names. I certainly agree that software has underperformed here as people have been concerned about the hardware. And I think you'll get follow through. But please just clarify this this enterprise adoption dynamic sector wise if you can. Yeah. So a couple of thoughts you know A.I. has been a novelty for consumers with chats and a lot of knowledge workers have gotten big benefit out of it because it's very good at researching and summarizing content for knowledge workers. But after three years on the market now it's finally becoming part of the business process and workflows. How a company actually conducts business. So this involves the use of agents or gentics and how they collaborate and do complex workflows. As a result the amount of inference that's going to be required is going to explode. You know a single call to a chat bot means it's one call to the LLM to give you the answer for inference. If it's a workflow related question particularly for complex workflows it could be 10 or 50 trips back to the LLM. So LLM are going to really be stressed by enterprise systems. We've got reasoning. We're asking these models to do now. They're not built for reasoning. So they just kind of throw a lot of weight into this GPU saying give me 100 answers and I'll pick the best one. So I think for all these reasons you know the inference is going to be the heartbeat of American global business. It's how it runs. So that's going to create enormous demand for data centers. So the data center trade you know I'm not worried about it. We're going to have so much more demand than we have supply of data centers given all the constraints on data centers the capital the GPUs memory etc. So the question would be and I think this has been forefront in people's minds is well is the business model there to support the financial commitments that are being made. And I think people look to the LLM market in this. The leadership in LLM changes over more times than you know a close match basketball game. You know the score just keeps going back and forth. So the Chinese have open source models. You've got meta and video with open source models. So the LLM business can be a very competitive business. But I don't see the leaders in that market saying we're going to make all our money on LLM. What they're going to do is what Microsoft did with Windows and go up the stack. They're going to do what Oracle did on the database and move up the stack.

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LLMs will be stressed by enterprise systems

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