The Six Five team discusses the 2024 Watch List in AI.
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Transcript:
Patrick Moorhead: Overall AI, Dan, what’s your watch list in AI for 2024?
Daniel Newman: Yeah, so kind of like I did with NVIDIA, I’m going to skip some of the obvious picks. The obvious pick for AI in my opinion is Microsoft, so I’m just going to run past that one and talk about a few other companies I think are really interesting. First of all, I think those that got the indemnification right and that focused on private data are going to be very interesting plays in 2024. I think IBM led the way on governance and we continue to say, “Well, look, companies are going to have to demarcate their private or what I call unique proprietary data from the scraping the internet for data.”
That’s what this New York Times lawsuit is going to teach us is that it does come down to who has more rich data? Then who has the platforms and who’s building technologies that enable grounded, vectorized data sets to be implemented and utilized securely? And it won’t just be about indemnification, but it’s going to be about actually building technology that doesn’t let you get into legal trouble. So by the way, that’s going to be a really important conversation in AI, that’s going to be a watch item all year long.
We didn’t talk about this company, Pat in semis much, so I’m going to talk about it in AI. But I actually think Broadcom has a really interesting year ahead of it, as we do see this pivot from AI data centers to broader data center. All the movements of data networking is going to be really, really important. So Broadcom has a very interesting play from an AI standpoint of who moves the data? And that goes into then companies in our infrastructure space, it’s HPE, it’s Dell, it’s Cisco, the network itself, it’s the data center construction, the edge. We’re going to have to move data around at a very, very high rate with very low latency, and we’re going to have to figure out ways to do this with economics. And so those economics are going to become very important, it’s going to be how do we do AI and make it affordable?
Now, one other item I’ll say is, one, people were not talking about this path, but Futurum Intelligence actually released a report, I think it went live today, on what we call it our decision-making data dashboard for AI. And companies are actually, this is going to be a topic for the year, but companies are very early in their implementation of AI. We heard Chuck Robbins at Cisco last quarter talk about the fact that their revenue, they had lowered expectations because basically customers had overbought this infrastructure that I’m talking about and now they have to put it into… you got to put it into commission to actually start using. We found that we’re seeing a 300% rise in companies that will be spending multimillion dollars in their AI strategies next year.
So what’s happening now is companies this year, it was all about the infrastructure, that was all the buying. The buying wasn’t actually companies using AI. And so who are they planning to use? Well, our data basically calls out the winners here. And I told you it was Microsoft, but do you know who the number one IaaS provider for AI?
Patrick Moorhead: Yeah, it’s AWS.
Daniel Newman: It was AWS. But there was a couple of interesting ones in there, IBM actually came in in top five partners for end-to-end AI. And a couple others I’ll mention, I think Salesforce has one of the actual productized AI offerings that they can sell and monetize. And then I think in AI, ServiceNow or any sort of workflow automation tools, iPaaS and then as well as services workflow automation tools are going to be very important because that’s going to be an early iteration of AI. It’s been ongoing and companies are going to double down because you’re hearing rumors right now, Pat, that 4 in 10 companies are planning to meaningfully cut their headcounts next year in trade for AI use cases. Which will be another big trend line is going to be productivity and efficiency in trade off of new hiring.
Patrick Moorhead: Good stuff, man.
Daniel Newman: Thanks.
Patrick Moorhead: But the great part about AI is you left Oxygen.
Daniel Newman: Oh my god, there’s a million directions you can go, dude, I bounced all over the place.
Patrick Moorhead: So I’ll take this, two things, so some technologies and companies that I think are going to do well in what I’ll call the wave two, right? We’re currently in wave one, where there has been a lot of build out, not a whole lot money being made aside from the NVIDIAs of the world. And it’s kind of a… People are driving down demand for basic enterprise stuff to put all that money into AI, yet AI servers are being stranded because they can’t get GPUs, it’s like a Catch-22. So yeah, some of the things to watch are these multimodal capabilities. We are starting to see that we’re going to see a lot more of that in 2024. And what does that mean? What that means is that a single chatbot or a single agent can do video, can do audio, can do photos, can do text all in one. And more importantly, it can find relational interrelationships between them to give you better answers.
While there was some questioning of the blue duck in the Google’s latest models that it brought out and how it did it, but that is a multimodal capability that they were showing off there. I think that we’re going to see… Training will continue, but we’re going to see a lot of action at the edge and inference at the edge. So some of the winners here are going to be PC companies, edge infrastructure companies like Dell and HPE. And you’re going to see IBM be a really interesting play here as really the enterprise solutions provider for AI for regulated industries. And you can’t be wrong, zero risk. I also think you’re going to see some of the magic move out to the non-Microsoft SaaS like Adobe and Box. I think what’s kind of on the outs could be employees that are in accounts payable and accounts receivable, right? Dan, you talked about companies wanting to dial back the amount of resource. I think legal is going to be transformed in 2024.
I’m talking to a lot of lawyers that are doing some of their first PaaS research against highly optimized models for legal. And don’t confuse those with the dumb lawyer who used ChatGPT to create cases that never even existed, right? These are highly optimized models out there. I alluded to this to a little bit with The New York Times and OpenAI lawsuit, but video and imagery outputs that break copyrights. I’m just envisioning myself or the jury pool looking at this video versus this video, right? This photo versus this photo. Being, “Yep, that was ripped off.” So I think that we need to keep an eye on the companies that are doing that. And do they go poof? I don’t know, but they could.
Daniel Newman: Yeah, we didn’t really even talk about it too with AI, Pat, but a real ’24 item to watch, the election. I don’t want to go down that rabbit hole, but how can you not mention, woo, deep fakes, misinformation, all kinds of different ways that AI is going to be used to mislead. Of course, it could be used to help people too, it doesn’t all have to be negative, but I just don’t see people putting in the work to figure it out. And I see a lot of information being amplified and algorithms taking wrong info. And gosh, it just seems like it’s a little… Doesn’t it just seem like a disaster waiting to happen in some ways?
Patrick Moorhead: Yeah, the big companies are girding to block stuff and monitor stuff, but it is going to be spy versus spy, and I just think it’s going to be a timing thing. Most of the social media platforms have turned off political advertising a month before the election, which is an interesting play. They’re leaving a bunch of money on the table, but I also think it’s trying to circumvent maybe some of the paid advertising and some of the fake videos and fake news.
Author Information
Daniel is the CEO of The Futurum Group. Living his life at the intersection of people and technology, Daniel works with the world’s largest technology brands exploring Digital Transformation and how it is influencing the enterprise.
From the leading edge of AI to global technology policy, Daniel makes the connections between business, people and tech that are required for companies to benefit most from their technology investments. Daniel is a top 5 globally ranked industry analyst and his ideas are regularly cited or shared in television appearances by CNBC, Bloomberg, Wall Street Journal and hundreds of other sites around the world.
A 7x Best-Selling Author including his most recent book “Human/Machine.” Daniel is also a Forbes and MarketWatch (Dow Jones) contributor.
An MBA and Former Graduate Adjunct Faculty, Daniel is an Austin Texas transplant after 40 years in Chicago. His speaking takes him around the world each year as he shares his vision of the role technology will play in our future.
