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Dan Gallagher
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Victoria Craig
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 fier. 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 hurt 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 is pretty staggering.
Dan Gallagher
That's been a long time in 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 multiple. 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 of mid teens to low 30 range for multiple. So that gives you an idea of the gap that we're talking about here.
Victoria Craig
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.
Dan Gallagher
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.
Victoria Craig
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 Tesla's?
Dan Gallagher
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, 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.
Victoria Craig
So what would be a more reasonable valuation for Waymo?
Dan Gallagher
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, 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 a hundred billion at this point.
Victoria Craig
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 if other services do, tweaks to their software or whatever be to catch up to Waymo. Is that a risk to its overall competitiveness and then ultimately its valuation?
Dan Gallagher
Certainly there's a risk. Tesla's system is theoretically based on something that, 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 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 Robotaxi 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 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.
Victoria Craig
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.
Stephen Rosenbush
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Victoria Craig
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 WSJ Pro. 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?
Athena Kaniura
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 OpenAI 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.
Victoria Craig
So PEPC 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.
Athena Kaniura
AI PEPC 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, 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 iteration, which is the adoption of AI agents.
Victoria Craig
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.
Athena Kaniura
I spoke to Athena Kaniura. 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 and 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 layoffs, but then again, you're not seeing growth in certain kinds of jobs, at least that you would have in the past.
Victoria Craig
So these are some of the upsides of deploying AI throughout a company. What are some of the downsides?
Athena Kaniura
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.
Victoria Craig
That was Stephen Rosenbush, chief of the enterprise Technology bureau for WSJ Pro. And that's it for Tech News Briefing. Today's show is 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.
Dan Gallagher
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Podcast Summary: WSJ Tech News Briefing – "Why Corporate America Didn’t Hesitate to Go All-In on AI"
Release Date: June 30, 2025
Host: Victoria Craig
Author: The Wall Street Journal
In this episode of the WSJ Tech News Briefing, host Victoria Craig delves into two pivotal topics shaping the technology landscape: the burgeoning competition in the self-driving car industry and the rapid adoption of artificial intelligence (AI) within corporate America. Through insightful discussions with Wall Street Journal columnist Dan Gallagher and WSJ Pro’s Stephen Rosenbush, the episode unpacks the strategic maneuvers of industry giants like Tesla and Waymo, as well as the transformative impact of AI on businesses such as PepsiCo.
Tesla's Strategic Expansion into Robo Taxis
Victoria Craig opens the discussion by highlighting Tesla CEO Elon Musk's latest venture—launching robo taxis in Austin, Texas. This move not only underscores Tesla's aggressive push into autonomous transportation but also intensifies competition with industry leader Waymo.
Dan Gallagher provides an in-depth analysis of Tesla’s market positioning:
“Tesla is basically valued at a trillion dollars… their stock price is about 150 times projected earnings for the next four quarters” (02:12).
This valuation places Tesla alongside tech behemoths like Meta, Google, Amazon, and Microsoft but with a significantly higher valuation multiple. Gallagher attributes this disparity to Tesla's perception in the market as more than just a car manufacturer, emphasizing its potential in areas like self-driving technology and home robotics.
Waymo’s Valuation and Market Position
In contrast, Gael Gallagher discusses Waymo's current valuation:
“Waymo's valuation is $45 billion… some see Waymo's as should be valued a little over a hundred billion at this point” (03:22).
Despite being a leader in autonomous vehicle technology, Waymo's valuation pales in comparison to Tesla’s. Analysts suggest this is partly due to Waymo being a part of Alphabet (Google's parent company), which holds a 75% stake in the company. Gallagher explores what it would take for Waymo to bridge this valuation gap, noting the critical factors of scalability and technological advancements.
Competitive Dynamics and Future Outlook
The conversation turns to the competitive dynamics between Tesla and Waymo:
“Waymo is very far along. They're going to be very competitive” (05:17).
Gallagher emphasizes that while Tesla has made significant strides with its robo taxis, Waymo’s extensive experience across multiple cities and its established technological foundation present substantial competition. The future will hinge on how effectively both companies can scale their services and enhance their technologies to meet safety and efficiency standards.
The Motivations Behind Rapid AI Adoption
Post-break, the focus shifts to the rapid adoption of AI within corporate structures, exploring why companies are eager to integrate AI technologies. Stephen Rosenbush, Chief of the Enterprise Technology Bureau for WSJ Pro, sheds light on this phenomenon:
“Everyone seems to really get the idea of a chatbot… They don't need an engineering degree if you're an individual” (06:59).
Rosenbush explains that AI's accessibility and the tangible benefits it offers make it an attractive proposition for businesses aiming to enhance efficiency and innovation.
Case Study: PepsiCo’s AI Transformation
Athena Kaniura, Chief Strategy and Transformation Officer at PepsiCo, exemplifies successful AI integration:
“They began investing in AI something like six or seven years ago… now they're embarking on the adoption of AI agents” (07:46).
Kaniura outlines PepsiCo’s evolution from basic machine learning applications to sophisticated generative AI and AI agents. This strategic investment has enabled the company to optimize processes such as demand planning, predictive maintenance, and autonomous vehicle integration within manufacturing facilities.
Balancing Technological Advancements with Workforce Stability
A significant theme is how PepsiCo has managed to leverage AI without resorting to large-scale layoffs:
“Instead of firing people, they want their people to take on the kinds of tasks that are really more suited to the human mind” (09:01).
Kaniura emphasizes that while AI has automated certain tasks, it has also allowed employees to focus on more complex and creative endeavors, fostering a collaborative environment between technology and human talent.
Challenges and Considerations in AI Deployment
Despite the advantages, Kaniura acknowledges potential downsides:
“They are aware of the need for data privacy… there are certain kinds of limits with language models themselves” (10:25).
PepsiCo addresses these challenges by partnering with companies like Salesforce to mitigate cybersecurity risks and enhance the capabilities of their AI systems, ensuring that technological integration is both secure and effective.
The episode effectively captures the dynamic interplay between technological innovation and strategic business adoption. On one hand, Tesla and Waymo’s endeavors in autonomous vehicles illustrate the fierce competition and high-stakes valuation battles within the tech industry. On the other hand, the corporate embrace of AI, as demonstrated by PepsiCo, highlights a transformative trend where fear of falling behind propels companies to integrate advanced technologies swiftly and thoughtfully.
Through expert insights from Dan Gallagher and Athena Kaniura, the episode underscores the importance of leadership, strategic investment, and balanced integration in navigating the rapidly evolving tech landscape. As AI continues to reshape industries, the lessons from Tesla, Waymo, and PepsiCo offer valuable perspectives on leveraging technology for sustained growth and innovation.
Notable Quotes:
Dan Gallagher: “Tesla is basically valued at a trillion dollars… their stock price is about 150 times projected earnings for the next four quarters.” (02:12)
Dan Gallagher: “Waymo's valuation is $45 billion… some see Waymo's as should be valued a little over a hundred billion at this point.” (03:22)
Dan Gallagher: “Waymo is very far along. They're going to be very competitive.” (05:17)
Stephen Rosenbush: “Everyone seems to really get the idea of a chatbot… They don't need an engineering degree if you're an individual.” (06:59)
Athena Kaniura: “Instead of firing people, they want their people to take on the kinds of tasks that are really more suited to the human mind.” (09:01)
Athena Kaniura: “They are aware of the need for data privacy… there are certain kinds of limits with language models themselves.” (10:25)
Produced by Julie Chang with supervising producer Melanie Roy.
For more insights and updates, stay tuned to the Wall Street Journal’s Tech News Briefing.