How to Invest in AI Right Now

0:01Bloomberg Audio Studios Podcast Radio News. Another week, another tidal wave of AI news. Major investments. The Disney story, a billion dollar investment from this iconic, from the House of Mouse in open AI. And some significant share drops. Oracle sank 14%. Investors are worried about whether all the money Oracle is spending on AI technology will pay off. There's an enormous amount of money flowing in and out of the AI industry right now. It's just such an all-encompassing, all-pervasive theme. Suzanne Woolley covers personal finance for Bloomberg. It's what everyone's talking about. It's what everyone's worried about.

0:50We've heard a lot of promise, but not a lot of actual revenue coming from the companies that are spending so much on building out AI. If a few of these big AI hyperscalers have a bit of a hiccup, we could see a lot of the other market taken down with them. Every few weeks, Suzanne asks experts to share their advice about where people should be investing their money. And right now, you'd be hard-pressed to find a company or a sector to invest in that isn't AI exposed. It's a little hard for me to think of a pure investment where AI wouldn't at least be embedded in the operations of a company. So Suzanne and I called up some investment experts to help assess when, whether, and how to bet on AI in the most strategic way possible.

1:38Because things are moving quickly. And alongside all the excitement about getting in on the AI race, there are also a lot of concerns about being too exposed. I'm Sarah Holder, and this is The Big Take from Bloomberg News. Today on the show, the risks and rewards of investing in AI right now. We talk to investment experts about what they think are the smartest AI plays and the ones you should avoid.

2:12Depending on who you talk to, AI is poised to revolutionize healthcare and technology or destroy jobs and natural resources. It's the most profitable investment opportunity we've ever seen or an industry bubble that's about to burst. Suzanne said the topic stirs up a lot of anxiety. We know it feels transformative and we're seeing big changes, but we can't look out 10 years from now with any sort of crystal ball and say, these are the stocks I should have invested in. And, you know, this is how it's going to reshape finance or insurance or journalism. We're seeing it in our personal lives when we read about stories of like layoffs and entry level jobs.

2:59So there is this sort of excitement over the promise, but worry over the impact on one's life and just the uncertainty about what it might lead to. I mean, does that remind you of any other sorts of investments that you've written about? I guess like the dot-com bubble, investing in tech stocks back in the early aughts. That kind of enthusiasm and the fear about hype and all the bubble talk is reminiscent of those times. But I feel like with AI, it's sort of that on steroids in a way. It's seen as a much bigger, potentially life-altering breakthrough. For the AI bulls, that's exactly the reason to put your money behind it.

3:45Getting in now and riding this wave is how you're going to make the big money going forward. We've seen incredible valuations on companies connected to AI. And that is where you get into sort of the bear case. The cons. People are worried about these valuations. There's waves, massive waves of money flowing into building out the infrastructure and the data centers to support AI. Can the industry grow into all of the money that's being spent on it? That's unclear. For a lot of investors, though, the idea of all this untapped potential makes this moment feel like the perfect time to strike. I have never seen more fear about innovation than I do now.

4:34And I'm very comfortable here. I think this is a good place. You know, you don't chase the momentum, but you buy the dip because you get these opportunities. That's Kathy Wood, the CEO of ARK Invest. She's someone whose investments are closely watched by retail investors. So when When Suzanne was looking for experts to poll, she wanted to go to Kathy first. She has such an interesting history in investing in innovative technology companies. Kathy said that as she tracks the number of users of OpenAI and Gemini, she's reminded of the early days of the dot-com boom. If you think about the internet and how it evolved, we think we are in 1995 for the consumer.

5:17The hope is that as the user base grows, so will the money that she's invested in companies leveraging AI. Like one of Cathy's longtime favorites, Tesla. It is the robo-taxi year. We believe that the autonomous taxi ecosystem globally is going to scale right now. I think if it's in the billions, I'd be surprised in terms of revenue generation. But we think it's going to scale to the$8 to$10 trillion level per year within the next 5 to 10 years. Investing in a highly valued Mag7 tech company like Tesla or NVIDIA or Microsoft isn't the only way to bet on AI's potential, though. Taosha Wang, a portfolio manager for Fidelity International based in Hong Kong, suggests looking at the infrastructure that supports the AI ambitions of MAG7 businesses.

6:14For example, semiconductor. You know, you can easily access it via ETF. And it's something that, you know, it's a structural growth story even before AI. In addition to physical technologies like semiconductors, Taosha said investors should be thinking about the underlying commodities that tech relies on, with finite supplies, but the prospect of increasing demand. We can be talking about copper, and we can be talking about things like uranium, you know, that's not traditionally on the radar of commodity investors, but nuclear is such an important way to power the AI power needs. Our third expert agreed that anything related to power is interesting.

6:56That is the bottleneck right now. Michael Smith, who runs the growth equity team at Allspring Global Investments. When you look at the commitments that have already been announced from the major players in the space and added all up between now and 2030, they need to obtain enough power to fuel basically the equivalent of 30 to 35 million homes, which to put that in perspective, there are over 130 million households in the U.S. today. But Michael also advised being more forward-looking in predicting where AI is going next. To use the surfing analogy, don't chase the wave that's already passed.

7:35Get ready for the next one. If you miss the infrastructure wave and you feel like it's too late to buy NVIDIA, don't worry. I think the next big wave will probably be the suppliers, the B2B companies that develop applications and tools that they sell to other businesses and help them use AI. And then if you miss that wave or you're not comfortable with that, I think there's a huge wave coming behind the supplier wave, which will be the consumers of all this stuff. And when AI starts to directly improve everyday experiences for all of us, there's going to be big opportunities. Another way to think about categorizing AI-related investment opportunities comes from Denny Fish, who's head of technology research and a portfolio manager at Janice Henderson.

8:22Denny Fish used the buckets of enabler, enhancer, and end user. We're going to see waves of adoption and evolution. You know, we are clearly in the enablement phase of AI and the infrastructure build out, and that's semis and that's power, data center infrastructure, all those things that you need to even be able to train a model or perform inference. In this enablement phase, companies like Microsoft or Amazon, which have major cloud computing businesses, are seeing massive growth. So are those physical infrastructure providers, companies that manufacture chips or produce liquid cooling systems for data centers.

9:03Denny Fish's next category is the enhancers. There will be companies that will embrace AI in a meaningful way to improve their competitive position in areas like software and internet. Tech companies like Intuit, which dominates in accounting and tax e-filing and is trying to use AI to improve its product. And finally, there are end users, non-tech companies that adopt AI early. A more sort of motley crew of companies that can incorporate AI to have a more competitive edge in operations, in using agentic AI, just really sort of deepening the reach of their business and becoming more relevant to their customers.

9:51You could listen to the transcript of every company in the S &P 500 last quarter, right? And I don't know, 60, 70 percent of them mention artificial intelligence in their transcript. So you can go through and pick your poison in financial services, health care, agriculture, insurance, and find, you know, unique companies that are actually benefiting from this trend that aren't, you know, quite as obvious. Take John Deere, the agricultural services company that's using AI to identify which weeds and plants to spray. Or healthcare companies like Tempest AI, which uses the technology to analyze patient data to improve disease diagnosis and treatment.

10:33Here's Kathy Wood again. That's in our top 10, which we think could become one of the most important healthcare information backbones in the United States. But what happens if all the plans to make AI profitable don't pan out exactly the way these companies have promised? How to hedge your bets after the break.

11:03The amount of money going into the AI space right now is, frankly, staggering. The current run rate spending just of the big hyperscaler companies alone equals like 10 Manhattan projects. Michael Smith at Allspring. Pretty much AI has to work. Like, we're all in. It is a massive percentage of the stock market. I think we are all sort of in awe of how much money is going in, right? That the magnitude, order of magnitude is hundreds of billions of dollars, and they are big. They are GDP moving kind of numbers. Taosha Wang at Fidelity believes it makes sense that investment at this scale would drive GDP.

11:41But after that, the boost, you know, through investment needs to come from productivity gain. And productivity is also an important driver of GDP. We are seeing anecdotal evidence of, you know, certain industries really benefiting from the adoption of AI in terms of the productivity boost. But, you know, for this to be broad economy, GDP moving, that we need to see it in many different industries that may not necessarily be traditionally at the forefront of technology. That wide-scale adoption and proven profitability are what Tausha believes will determine whether the AI run-up continues or whether it's more like a bubble that could pop.

12:22One can never time how long the bubble is going to last and what is going to make the bubble burst and make the music stop, I think it's usually related to illiquidity and cash flow. So to the extent that there's still money going around, then I think it can continue. Those bubble concerns are being driven in part by the large number of circular investment deals in this space. In other words, companies like OpenAI, NVIDIA, and Microsoft all investing in each other. The fear is that it's those deals that are propping up the industry's growth and valuations. But Tausha is among the experts who say mutual investments aren't a reason to write the whole industry off.

13:03I think it's not necessarily a brand new practice that companies invest in other companies that are in their operational sort of sphere. But she also says it is reason for investors to take care. I would generally caution against things from a cash flow perspective that do not have, you know, real revenue proof, real profitability proof, alarming amount of circular investments going on. That's certainly something that you, you know, want to be mindful of. Michael Smith has been on his team at Allspring since the dot-com boom and bust. And there's a few things he learned from that experience. There are a lot of companies that want a piece of this pie.

13:46And to me, like the big difference is who's funding their investments from the profits that their legacy businesses generate and who's dependent on the kindness of strangers, whether it would be outside equity investors, lenders, anybody who's helping to finance the growth other than the business itself. And just be very careful investing in companies that can't finance their own growth. I think that was the lesson learned in the late 90s and early 2000s. I mean, it was basically the inability to access the capital markets and continue to finance the growth that changed things that time around.

14:24As you may have noticed, the investment experts we spoke to tended to be bullish on AI. They've already bet on the industry themselves, after all. When we asked Cathie Wood if there were any AI-related investments she'd caution against, she said, basically, don't move on to the next thing too quickly. A lot of people are saying, well, you know, this AI movement or opportunity is exploited. Let's move to the next thing, which is quantum computing. They've skipped over thematically to quantum because they think, and I say they meaning thematic portfolio teams or what have you, they think AI has been exploited.

15:07We think it's barely begun. To read more about what these investment experts told Bloomberg personal finance reporter Suzanne Woolley, head to Bloomberg.com or click the link in our show notes.

15:27This is The Big Take from Bloomberg News. I'm Sarah Holder. The show is hosted by me, David Gura, and Juan Ha. The show is made by Aaron Edwards, David Fox, Eleanor Harrison Dengate, Patty Hirsch, Rachel Lewis-Kriske, Naomi Ng, Julia Press, Tracy Samuelson, Naomi Shaven, Alex Sudiura, Julia Weaver, Yang Yang, and Taka Yasuzawa. To get more from The Big Take and unlimited access to all of Bloomberg.com, subscribe today at Bloomberg.com slash podcast offer. Thanks for listening. We'll be back on Monday. Thank you.