Why Corporate America Didn’t Hesitate to Go All-In on AI
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Welcome to Tech News Briefing. It's Monday, June 30th. I'm Victoria Craig for The Wall Street Journal. Elon Musk's Tesla has accelerated competition in the world of self-driving cars with last weekend's robo-taxi launch in Austin, Texas. But we'll tell you why our columnist argues that's a good thing for industry leader Waymo. Then, big companies have in the past been slow to adopt new technologies. Their appetite for artificial intelligence, though, has been fierce.

But first, Tesla's robo-taxis have officially been on the streets for a week. That's a success for Elon Musk's ambitions for the company, but also for its biggest competitor and industry leader, Waymo. Dan Gallagher is a heard-on-the-street columnist for The Wall Street Journal who's been comparing the value of both companies and what's driving each forward.

Dan, we'll talk about Waymo in a moment. But first, help us understand Tesla's valuation because that number is pretty staggering. That's been a long time coming, even well before they launched Robotaxis. Tesla is basically valued at a trillion dollars. So they're up there with your big tech companies like Meta, Google, Amazon, Microsoft. But they have by far the biggest what you call valuation multiples.

So if you look at their stock price relative to projected earnings, which is a very common measure, Tesla stock price is about 150 times projected earnings for the next four quarters. All those big tech companies I mentioned are all in the kind of mid-teens to low 30 range for multiple. So that gives you an idea of...

the gap that we're talking about here. And there's also a gap if you think about car companies too. I mean, when we're talking about this valuation, it's huge. Yeah. It's because the market sees Tesla as much more than a car company. Investors really think the company has this huge future ahead in things like self-driving cars, robo-taxis, home robots, all these things. Those things actually drive the majority of that valuation for Tesla.

By comparison, though, Waymo's valuation is $45 billion, which is much lower. So let's talk about that. What's behind Waymo's valuation and how do you square it with

with Tesla's? Well, Waymo's valuation, the last hard number we have is from when they did a funding round last year. So at that last funding round, Waymo was valued $45 billion. That's actually a really big number. That's in the top 10 of venture-backed companies that are not public yet. You know, it's a lot smaller than ones like OpenAI and SpaceX, but it's really up there for a company that's actually still fairly small, not making a profit yet. But investors are still valuing Tesla's robo-taxi business

far higher than Waymo's. So what would be a more reasonable valuation for Waymo? Keep in mind that Waymo is actually majority owned by the company that owns Google. Alphabet's the parent company that owns these, has about 75% stake in Waymo. And Wall Street analysts that cover Google's parent, some of them have made a guess as to what they think Waymo should be worth now. And some of those numbers are higher than the $45 billion range.

In fact, some see Waymo's as should be valued a little over $100 billion at this point.

So what would it take to get to that kind of valuation? Because if we sort of look at the landscape of self-driving cars, obviously Waymo is the market leader. But Tesla, if it has a quick expansion of the robo taxi or other services do tweaks to their software or whatever it might be to catch up to Waymo, is that a risk to its overall competitiveness and then ultimately its valuation? Certainly there's a risk.

Tesla's system is theoretically based on something that's mostly a software download. Tesla's vision is that at some point, a lot of Tesla owners can download the self-driving software and actually turn their cars around

into taxis. So if you're sitting at home working, your car could be out there making you money. You know, the technology is still being tested. What they launched in Austin, we're talking about a dozen cars in a very ring-fenced area. We're looking at years until we see what the potential is for Tesla's robo-taxi.

service and can it scale and catch up to where Waymo is. Waymo is now in five cities and they've been offering these rides for years and there's differences in the technology and there's a lot of debate in the technology world about what is actually better and

and safer. A lot of those things still have to play out as well. So we're very, very early. How Tesla's service trends from here and how well it does and how much they can scale it and lots of other kind of unknowns will affect how the market sees Waymo. But Waymo is very far along. They're going to be very competitive. That was WSJ Heard on the Street columnist Dan Gallagher.

Coming up, sometimes fear can be a good motivator for change. For several executives in corporate America, fear has helped fuel the swift adoption of artificial intelligence. We'll tell you why after the break. Put us in a box. Go ahead. That just gives us something to break out of. Because the next generation 2025 GMC Terrain Elevation is raising the standard of what comes standard.

As far as expectations go, why meet them when you can shatter them? What we choose to challenge, we challenge completely. We are professional grade. Visit GMC.com to learn more. Big companies are apparently learning from past mistakes when it comes to technology. Some were slow to get in on the rise of the internet, social media, smartphones, and even e-commerce.

But when it comes to incorporating, even embracing, artificial intelligence, the pace has been swift. Stephen Rosenbush is chief of the Enterprise Technology Bureau for WSJPro. He writes that 88% of businesses said they're already undertaking an AI transformation, according to research by McKinsey.

Stephen, why is AI the tech bandwagon that all of these companies have chosen to hop onto? The nature of this technology boom is very different, and everyone seems to really get the idea of a chatbot. They understand what to do with open AI or anthropic or...

meta or Google's platforms. It just sort of makes sense in a way that other technologies didn't. And you don't need an engineering degree if you're an individual. You don't necessarily need massive amounts of infrastructure the way you might have in the past, although you certainly do need some. And yes, to answer your question, they did, in fact, learn from the experience of the last two or three decades.

So Pepsi is a good example of this. Walk us through some of the things that it has done early on, what's made it an early adapter of AI. Pepsi is a good example of how and why companies have become early adopters. It's a leadership decision. They're early adopters and they're leaders here because they chose to be. And ultimately, you know, as in many cases,

This stems from the CEO, it stems from the board and the rest of the senior leadership. But people tell me over and over again, the CEO carries a lot of weight in this. And they began investing in AI something like six or seven years ago. And the technology wasn't what it is today.

So they started with machine learning. Two and a half years ago, they moved to generative AI using language models to process, synthesize language, generate language, summarize massive amounts of information. And right now they're embarking on the next generation, which is the adoption of AI agents.

And it obviously saves money, but not in the way that we usually think about it, because at least in Pepsi's case, it hasn't resulted in huge layoffs. And that really is the fear of a new technology.

Walk us through how Pepsi has been able to deploy these technological advances in ways that keeps people in their jobs, but also makes their life easier. I spoke to Athena Kanayoura. She's the chief strategy and transformation officer at Pepsi. This is a company with $92 billion in revenue, by the way. And they've been doing things with AI such as

demand planning, predictive asset maintenance, and manufacturing facilities. Then they moved on to extracting insights from data in warehouses and manufacturing plants. They connected autonomous vehicles in those facilities with AI, and they tried to make that work more efficient and also safer. And her point was that

When it comes to many of these tasks, there's no reason for a human to be engaged. But instead of firing people, they want their people to take on the kinds of tasks that are really more suited to the human mind. She did say that the investment in all this technology means that they've been able to grow without taking on human labor the way they might have in the past. It doesn't mean that they're not adding jobs,

It just means that they're able to grow without investing in people the way they did in the past. So there have not been large playoffs, but then again, you're not seeing growth in certain kinds of jobs, at least, that you would have in the past. So these are some of the upsides of deploying AI throughout a company. What are some of the downsides? They certainly are aware of the need for data privacy. Everyone is always aware of cybersecurity risks.

They also understand that there's certain kinds of limits with language models. Themselves, it's not going to be able to do everything on its own. They are working with other companies such as Salesforce, which have built other technology, other infrastructure around the large language models to sort of balance out some of the limitations of where those models are right now. That was Stephen Rosenbush, chief of the Enterprise Technology Bureau for WSJ Pro.

And that's it for Tech News Briefing. Today's show was produced by Julie Chang with supervising producer Melanie Roy. I'm Victoria Craig for The Wall Street Journal. We'll be back this afternoon with TNB Tech Minute. Thanks for listening.