WSJ What’s News - Could Bringing AI Into the Physical World Make It Profitable?

Episode Date: June 15, 2025

As businesses are adopting artificial intelligence and beginning to figure out how it will make them money, developers are already working on ways to embody AI in the physical world. From home robots to manufacturing and beyond, tech reporter Belle Lin digs into the industry’s plans and tells us whether physical AI might bring both makers and users the big returns on investment they’ve been anticipating. Alex Ossola hosts. Further Reading:  These Developers Can’t Get Excited About Apple’s AI Efforts  AI Is Here for Plumbers and Electricians. Will It Transform Home Services?  Companies Are Struggling to Drive a Return on AI. It Doesn’t Have to Be That Way.  Nvidia and Perplexity Team Up in European AI Push  Apple Executives Defend Apple Intelligence, Siri and AI Strategy  Meta in Talks to Invest $14 Billion in Scale AI, Hire CEO Alexandr Wang  Apple Fails to Clear a Low Bar on AI  Learn more about your ad choices. Visit megaphone.fm/adchoices

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Hey, What's News listeners. It's Sunday, June 15th. I'm Alex Osala for the Wall Street Journal. This is What's News Sunday, the show where we tackle the big questions about the biggest stories in the news by reaching out to our colleagues across the newsroom to help explain what's happening in our world.

On today's show, as businesses are finally starting to find ways to integrate artificial intelligence into their operations, developers are already working on future iterations of AI, including ways to embody the technology in the physical world. But the question remains, can the developers or companies make money from AI? One of the biggest stories in tech over the past six months is the huge investments tech companies are making in data centers needed to power artificial intelligence.

In January, Metta said it was allocating up to $65 billion this year. In the same month, Microsoft committed $80 billion. And in May, a data center startup that works with OpenAI secured almost $12 billion. These developers have big plans. They see one of the next steps in artificial intelligence as bringing it out of the cloud and into the physical world, like consumer devices and humanoid robots

for manufacturing spaces. But will this future phase of AI finally earn a return on investment for these users and developers? To dig more into the AI industry's future plans and whether they'll make AI profitable, I'm joined by Belle Lin, who covers AI and enterprise technology for The Journal. Belle, what do developers say is the next phase of AI? What's coming? It's an interesting question because it feels like we're still in some of the earliest phases of AI, where AI is still chatbots and you have to interact with chat GPT in order to get something back. You have to type in something.

But the wave after chatbots is supposed to be AI agents. And those are technologies or software that can basically do things for you, like order a cab when you're arriving home from the airport or to make a restaurant reservation. And then after that is physical AI. And some tech watchers and certainly Jensen Huang, the CEO of Nvidia, has talked about this phase as being where AI enters our physical world. And that has a lot of meanings, but in the corporate sense, it can mean that you're bringing automation to warehouses and bringing automation to factories. And then maybe in our daily lives, that's something like bringing humanoid robots to our homes.

So broadly, it's the idea that AI is entering our devices, whether in our homes and wearable devices that we wear, or in the idea that AI is entering our devices, whether in our homes and wearable devices that we wear or in the factories and the warehouses where our products and goods are made. I'm curious how that actually would work because right now I think about AI as a chatbot, essentially. How does that then become something that is embodied in the physical world, whatever that may mean. There are some examples of wearable devices and these AI pins and devices that already came to fruition in this sort of first few phases of AI. There are things like AR and

VR goggles that we've all heard of, the Apple Vision Pro, there's the MetaQuest, smart glasses like from Meta and Snap. And so these are examples of AI that is embedded within these devices that we interact with usually by voice or with gestures. Sometimes there's a more physical button that we might press or something that we might toggle. But the idea is really that AI gets embedded within the hardware itself rather than the human, the user, us, being tied to some screen or some interface that we're used to seeing as a laptop or a phone. Who is leading this trajectory? Who's leading the pack?

What we've seen from OpenAI and Johnny Ive's company is this collaboration called I.O. in which Johnny Ive and his team will serve as the creative brain behind this new device that OpenAI will release, the sort of family of devices. And they've been pretty tight-lipped about what the device will look like and what it will do, but they've said a few things like it'll be ambient, it'll be this third core device that you put on your desk after your MacBook and your iPhone. And so you could say that they're leading the pack because they're promising a lot of what has yet to come. But they have this really great heritage in the whole Apple ecosystem and the design aesthetics that Johnny Ive has put out. And also, they have the models, they have the

fantastic models that OpenAI has pioneered so far that are still state of the art. So when you combine these two technology powerhouses, right now, you get a bunch of promises, but they seem pretty promising. You know, it sounds like there are a bunch of different kinds of applications, consumer facing, more heavy industry, kind of something in between in the form of self-driving cars. Do we have a sense of which of these might sort of come first and how the developers of AI are thinking about monetizing those phases? Monetization questions are always front and center because so many of these startups are

funded by venture capital firms who need to see a return and there's so much cash that's being injected into AI right now. Some of the ways in which they're monetizing are in the software side on the models themselves. So you could sell on a word or bit basis the ability to use open AI's models in other services and other technologies. In the wearable side, the selling of the hardware itself plus the software upgrades. But at this point, it's still really about adoption and figuring out which areas in the consumer world really stick. And then if we're talking about the heavy industry side, that's where ROI becomes a lot more important because you can shave a lot of costs by automating human labor away.

And so that's where a lot of the warehouse and logistics companies are hoping to have an impact on their bottom lines. Coming up, AI developers may already be making the next generation of artificial intelligence. But if they build it, will the customers come? Stay with us. No Frills delivers. Get groceries delivered to your door from No Frills with PC Express. Shop online and get $15 in PC optimum points on your first five orders. Shop now at nofrills.ca. ["Dreams of a New World"]

Bell, we've been talking a lot about the developer side, how AI gets made and what form it'll be in. But now I want to talk about the people who are going to be buying it and using it. Lots of companies have started using AI. According to a survey by McKinsey, 78% of companies say they use at least one AI function. So it seems like companies need to show they're integrating AI into their operations. Would you say this is an existential need for companies right now?

Oh, absolutely. There are really existential questions for categories of companies like law firms that have questioned what is the value of the billable hour because so much of what AI is really good at automating away right now is reading and summarizing through texts and being able to provide synthesis of answers. And that's kind of early stage paralegal work. So if companies don't embrace AI, there's the question of will we still exist in 10 years time frame. Never mind questions of will we be using AI pins and devices.

We need to embrace AI now or else we won't be around. So that kind of brings me back to this other existential question about physical AI. Who actually wants this? Well, there is, if you look at examples of where physical AI exists now, I know we've talked about warehouses and factories, but there are also great examples of wearable headsets like the Apple Vision Pro and the MediQuest and many others that have been around for a while have huge applications in the military, for instance, for training the armed forces and in training for surgeries in home services where you have skilled

trades like plumbers and air conditioning technicians learning how to build the physical engines that keep homes running, as well as jet engines, technicians learning and figuring out how to troubleshoot them. So there's great examples of where physical AI and augmented reality, which is a really early version of bringing AI into the real world, already have a lot of value. And so you might see more acceleration in areas where AI in the real world are already having an impact, but once it becomes much more useful, you could see things like basic knowledge work becoming a lot more augmented because the ability to stream someone's virtual presence into a meeting room makes it that much better

and there's no longer a need to have an in-person meeting. One of the things that is in the news cycle about AI right now is just how unbelievably expensive it's been. Companies are shelling out billions of dollars to build these data centers because they are doubling down on AI being the future. Is there enough demand in all of these different applications for physical AI that we've talked about that will bring

down those costs of the data centers, or will they just keep skyrocketing? A lot of this goes back to the AI models and the software layer because as they become more efficient, then the promise is that they require a lot less GPU compute and power going into the data centers. And so when the models become more efficient themselves, even though they are quite large and unwieldy, they can be trained much more efficiently. From that point of view, costs will certainly start to come down in terms of the infrastructure. But at the same time, other costs will need to come down as well. The cost of hardware in a really general sense is

still quite high. The chips required to basically power Apple Vision Pro or to power a humanoid robot or to power self-driving cars. Those are not quite commoditized. They're still quite expensive. So as developers make these devices and software and as companies figure out how to use them, whose responsibility is it going to be to figure out how to actually make money off of this? Yeah, a lot of the AI developers and the AI startups will be hard-pressed to come up with an answer on how to Actually monetize what they're building right now A lot of them are funded by VC dollars are backed by research or other types of grants and funding And so there will be this sort of inflection point where either their technologies, their devices, their robots,

their cars catch on consumers or they don't. Because as we look at some of the other waves of technology that were funded by VC dollars, like the Ubers and the lifts of the world, there's this limited time frame in which they can be funded by venture capital dollars until they have to show their metal. And how about for the companies using the products? For the companies, that's already a really pressing question. ROI has been challenging since the dawn of the chat GPT AI era that we're

in now about three years ago. Companies have been investing heavily in AI models and AI technologies, but there's really not a clear way to determine whether or not they're paying off. So you could say that productivity of workers has gone up, but it's hard to measure. You could say that sales have gone up, but that's also hard to measure. So measuring AI's value has been a question for tech executives for the past several years and continues to be. But there's a lot of economic incentives that are aligned in trying to make sure that the AI companies are profitable and that companies are saving on the bottom line and generating top line revenue that the market forces kind of end up working out in some way.

That was WSJ reporter Belle Lin. Thank you so much, Belle. Thanks for having me. And that's it for What's New Sunday for June 15th. Today's show was produced by Charlotte Gartenberg with supervising producer Michael Kosmides and deputy editor Chris Sinsley. I'm Alex Osola and we'll be back tomorrow morning with a brand new show. Until then, thanks for listening.