Name: Kai-Fu Lee: The AI Device of the Future Will Always Be Listening—and Eventually Invisible
Uploaded: 2026-06-10T12:11:00Z
Duration: 19 min 20 s

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At the 2026 WSJ CEO Council Summit in London, AI entrepreneur and investor Kai-Fu Lee, CEO of 01.AI and Chairman of Sinovation Ventures, joins WSJ Leadership Institute President Alan Murray to examine the evolving AI competition between the United States and China—and explain why he believes the next generation of AI devices will be voice-driven, always on, always listening and eventually invisible.

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Kai-Fu Lee: The AI Device of the Future Will Always Be Listening—and Eventually Invisible

Occupies a pretty unique position in the world of AI, having worked at Google, Microsoft, Apple. Now spent a decade investing in China. Literally wrote the book on the competition between the US and China on AI, "AI Superpowers." Came out in 2018. So four years before we had even heard of ChatGPT. I wonder if you could give us an update. What is the state of the competition between the US and China, in your view?

Well, largely, the two countries are in parallel universes. So the companies don't really compete. If you're in the US, you don't tend to use Chinese models, and vice versa. But just to kind of compare the quality and the business models, I would say that purely large language model with Claude's new release, I think it's now around 15 months ahead of-

15 months?

That anything China can build. It's really, Fable Five is really pretty amazing. That fluctuates, right? Last March, it was three months, with DeepSeek-V3 coming out. So that's gonna, sorry, 01 coming out. R1 coming out. Too many numbers. But, so it's gonna go back and forth. Anywhere between three to 15 months, it's gonna fluctuate. So the American approach is, each one of the top three companies is like a genius who wants to win the Nobel Prize. The Chinese companies are like a bunch of smart kids who form the study group. They still compete in the class, but they sort of share a bit with each other through open source. So amazingly, China's become the open, and US has become closed. So they both deserve a place. If you want on-premise implementation, you'll want an open source model. If you want the very best, you want one of the top American models. If you don't need the very best and wanna save some money, the Chinese models can suffice. So that's the model status. In terms of enterprise adoption, and generating huge amounts of money for Anthropic in particular, that is unmatched in China. They are way ahead in that. A lot of reasons. China will eventually improve, but now, it's quite difficult to get that kind of enterprise spending, even though I work there and people listen to me.

Why?

Enterprises just haven't got used to paying annually for software, or on the per use basis. Too many CEOs think of software as a project, so they want to pay you project-based. So we're trying to change that, but we're also selling outside China because it's easier to get-

You're talking about large companies, many of them state-owned?

State-owned or private.

But how about smaller companies, startups?

But they don't have money, right? I mean, we sell to the enterprise. And the amount, Western companies, or even Middle Eastern, Central Asian companies, are willing to pay is about eight times what the Chinese company's willing to pay. Same product. So that's why we're going abroad. That's why, here-

That's fascinating. Oh yeah, yeah. We'll come back to that.

No, but let me finish on the competition.

Yeah, sure.

So very quickly, so consumer adoption, right now, it looks like both countries are doing stuff and I'm gonna bet China's gonna have a lot breakthrough new AI consumer apps, just because those gladiators are so good in what they do. And then on hardware, China is not only well ahead in robotics, embodied AI, as well as devices. Devices that will really be AI-first. The phone is not an AI-first device, it's a mobile-first device. An AI-first device, my description may scare some of you, but that's what it's gonna be. AI-first device has to be speech-driven. Guess you guys are okay with that. But then it has to be always on, always listening. Otherwise there's a huge latency. So if it's always on, always listening, then it must have an infinite memory, because it, remember why not remember everything, if it's always on, always listening? And then the technology's getting such that it will become invisible.

Yeah, so the US is 15 months ahead, Anthropic is 15 months ahead in large language models.

Yeah.

Way ahead in enterprise adoption, even though the people sitting in this room think they're way behind where they should be, so, which is very interesting.

They're both true, yeah.

But China, you're confident will be ahead in consumer products and in hardware.

Yeah.

Yeah.

Of course, there's this world model emerging. And right now I think China is not ahead at this point.

The world model being looking at the physical world and operating in the physical world.

Well it is creating a model virtually of the world, the physics and everything. That theory US is definitely ahead. But the process of taking any sort of a model, making it work in the robot, in the factory, well, China is ahead on that. So that's going to be,

And Kai-Fu, how much do you address this in the book? How much does it matter? I mean, it was Vladimir Putin who said, "Whoever wins in AI will control the world."

Yeah.

Is that what we're dealing with? Or does 15 months, Anthropic being 15 months ahead, really make a difference at the end of the day?

Personally, I think the top three American companies, and maybe the next two American companies and maybe the top five Chinese companies will more or less co-arrive at the so-called AGI. Meaning within 15 months of each other. So in that case, nobody squashes anybody, commercially. Everybody's got a potentially a different business model. And that's what's important. Do you have a business model to make money? And I think Anthropic does. The others, not so sure. So commercially, there is no winner take all, in my opinion. Now, Silicon Valley people will all disagree with me, so we'll just agree to disagree.

They wouldn't be spending so much money so quickly if they didn't think that there would-

Yeah, well now, Putin's comment. Now countries might think differently, right?

Yeah.

Because military might may be different, but I'm not an expert there.

Well, no, but talk a little bit about that. What does the world look like if you have two AI superpowers? We had some conversation yesterday about a sovereign AI, and what that means. I had a conversation with the CEO of one of the auto companies, who said they're building for their electric cars. They're building two completely different tech stacks.

Yeah.

One for China.

Yep.

One for the US. And they're not quite sure which tech stack they'll use in other countries. How does that work?

So they'll be a great customer for us, because we work, we basically build the operating system. I know we can say more later.

Yes.

But in the future, the models will be basically all the same. You got 10 companies producing slightly better here and there, who cares? So their applications is different, right? Using Claude for code, they're likely to keep that, and make lots of money with that. But their fundamental models are roughly the same. So it's like having an Intel chip and AMD chip in the old days, and so on. So what matters is the operating systems that sits on top and the applications that sit on top. So we're building that and we're being model-agnostic. So if you had that layer, then you could have the Chinese subsidiary run the Chinese models, the American subsidiary run the American models, with the layer taking care of which to use.

I promise you, I'm gonna let you talk about your company. I'm not gonna, and even if I don't, you're gonna do it. So we'll get there. But I wanna talk about the data piece of it as well, because part of the conversation yesterday was making sure they can control and have the trust that the data is under control. I mean, how does that play out?

The company? For the company?

Yes.

Yeah. A lot of companies want to have control of the data, "leave it within the company." For the first reason is they believe data is the differentiator. I actually made that statement, "Data is the new oil in 'AI Superpowers.'" I'll modify a little bit. Data plus a closed loop operation is the new competitive moat. That is, if a company collects the data and puts it away, that's useless. Collect and able to read it from our LLM, that's no good. You have to use the data to make your entire model and agents better. But, so anyway, I'm agreeing that your data is very important. That's why you don't want it out. You don't want your competitors to have it. So that's fully understandable. Now, there are a lot of technologies and companies that basically say, "Hey, trust us with our data. We'll give you virtual private network and all that." And it's largely accepted in the west. So the hyperscalers, right? Microsoft, Amazon, generally, you trust that when you send your data to the cloud, it's trustworthy. To the extent that you feel that way, you can also use any model there. Your "virtual sovereignty" is preserved. However, if you absolutely insist, "My data is so secret, it's got privacy, it's got all kinds of things, and I'm not gonna let it outside my enterprise walls." Then your only option is an on-premise deployment. Then your only option then is to use an open source model. There are a few okay American ones, but the leaders in open source is clearly Chinese models.

That's interesting. So at the end of the day, you may choose to use a Chinese model because you are hyper concerned about data privacy.

Yeah.

Anybody buy that argument? Show of hands?

No, there's no... Well let me just say there is no leakage. You took the whole model, all the waste parameters is on your server. There can't be no back door because you can run an American inference engine. So you may not like some of the way it answers, but a Chinese, American, whatever open source model implemented on your on-prem, you can unplug the Internet. There is no leak on that.

It may be a trust issue.

Well, you may not trust the answers, which is a perfectly fine reason not to use it. But there is no leakage. There can be no leakage.

All right, let's talk about what you're building. 01.AI. Explain what that is.

Okay, so we have found, I think, a very interesting solution to the problems many of you may have. I think all of you have tried the most amazing Claude, OpenAI, Gemini. You love the model, works great for your travel, for your family, for your horoscope, for whatever it is you want. It is so smart. Helps you write papers, generate ideas. It's so amazing. Then you say, "Well, CIO, put it in the company." And then you find that people are not, your company is not getting the value that you are as an individual. And the core issue there is like you just hired a number one graduate from MIT, IQ 180, to your company. And day one you say, "Well, do something for me in my company." Of course they cannot. But in six months, they can. So the key point is, how do we teach this model that's so brilliant, what is about your business, right? What's your purpose, vision, mission, goals, quarterly result, decision chain, out of the 50,000 spreadsheets, which matter. So all those things about your company, right? It might take an MIT graduate a few months to learn all that and probably learning by doing. But how does an LLM learn that? And the answer to that, you need to remember this word, is called ontology. I think many of them may have heard of it. Palantir is certainly out there selling this word. They're certainly the first to make good on that. That is the map to your enterprise. And that if you have ontology, roughly speaking, a good solid ontology takes two to three months to build. And so our company saw this is the gap between enterprise value and adoption. So we have a tool to build and maintain semi-automatically, the ontology for your company. Along with that, what we call an operating system, which includes basically able to orchestrate engines, agents, and get decision process and all that. So that is the core that we can build.

And Kai-Fu, that is not, can't just be a technology platform. That's like forward deployed service.

Yes.

It takes a lot of people to make that happen.

Yes, yeah, we can't sell it to you without our service.

So you're building that?

Yes, we have a forward deployed team.

And are you building that in the US or in China?

The team is in Singapore and China.

Yes.

And they'll fly to wherever you are.

Are your customers Chinese or American, or European, or what?

The ones who pay us real money are not Chinese.

They're not Chinese.

Yeah. They're in all continents.

And you having spent the last decade, or maybe more than a decade, focused on China.

Yeah.

Do you have a trust issue? I mean, is it hard to convince, you heard the chuckles, I guess, around here. I mean, do you find it hard to approach an American company and say, "We can solve this problem for you?"

Oh, we'll find out after I talk to some of you. Now, all the software is basically not IP. It is basically helping you to run your company. And if you have a trust issue, don't talk to me. The alternative really, at this point, is Palantir.

Is Palantir. That's your competition. That's who you're-

Well, they're not in most countries we go to, so they're not, we're not really competing. But let me also add, we have another product, maybe that will whet your appetite. This product is built on top of the AI transformation platform. And I believe AI transformation must begin with the CEO. And the CEO is the one who sets direction by using AI daily, by using it effectively. You set the tone. And also we have a product that will be called Boss AI when it's released in a month. And here's what it does. It reads everything in your company, and it also takes all your meeting notes, meeting recordings, video conferences, customer service calls, and it's all taken in, right? And everything you can imagine, this is dormant data. You currently don't use your group chats or your meeting notes or your Zoom recordings. You probably record it, but you don't use it. This is incredibly valuable. Now, without describing the product in detail, I'll tell you what I do with my Boss AI. Every morning I get up, not every morning, but every time I open it up, I would ask questions like, "Based on the meetings, 400 meetings that took place in my company in the last two days, what are three really important things I should know that I don't already know? What are the three biggest debates that took place that I don't know that I should know?" And also, I could also, I query all kinds of things. "Who made promises that are not being kept?" And we have a promised ledger that goes with the Boss AI, it tracks every manager's promises, made or kept.

Is this in the market or is this in development?

It's going to be in the market early July with forward deployed engineers. It's not going to be plugged and-

Same thing. And it's part of the broader 01.AI?

Well, the platform is what makes the ontology, and connects the model to your company.

So you can't use Boss AI without the ontology?

Actually, you can. You just have to pay more because it's more work, right? Because we have to unwire and rewire everything. And let me also add, you can ask questions like, "Who are my top 20 engineers by value, not by review." I wanna know who checked in code, who's got bugs, who has reviews from other people, whose code are copied by other people who are respected, who answered questions. So these are things will help you review employees. Then I can ask of the 20 top engineers, who are at retention risk? And that I can know, because they're less being less constructive, their tone change and so on.

Next time we do this, you'll have to be a sponsor. You realize that, don't you?

But I hope I can afford it.

But tell me this, from where you sit, what do you think everyone is getting wrong about AI?

Okay, so I think too many people delegate to CIO. Too many think of it as, which department should implement app. And many CEOs think "We don't understand, I don't understand. I'm not a user. I'm just watching you." Because I think many CEOs are used to having kind of two jobs, right? One is running the organization, execution, knowing all the information, passing all the information. All this can be delegated to AI, right? I think you can become that strategy and you need to become the AI user yourself. If it's not Boss AI, then it's some other product. Because unless you use it, right, at least you should be using a top language model to help you vet your strategy, right? To read your people's PowerPoints, and see where the junk is, where the errors are.

And one last question. You've been talking about Boss AI, but there's a lot of hand wringing these days among young people on college campuses about what all of this means for them. What's gonna happen to the entry-level employee?

Yeah.

What's your advice to young people confronting the age of AI?

Right. So my suggestion is that the good news is you no longer have to be engineer to use AI to write code. This is all wonderful news. What it really takes, who are the people who are gonna succeed in the future, are people who are willing to be accountable, who will drive a thing to its conclusion, who will manage a bunch of AI workers, so start playing. And then I think what matters for the leaders that these young people want to become are really judgment. Things like taste and conviction, courage, foresight. And if I could add one more thing is that, for those of you who don't wanna buy a Chinese software, you can buy a book written by Chinese. This book is not yet out. But I want to whet your appetite, and I have copies of the synopsis. And this describes, this is not a product sales book. This is about how to change your company, do AI transformation, and drive it as the CEO.

Do we have those out?

Yeah, we'll put it out. Yeah, or come to me and get it.

Always fascinating to talk to you, Kai-Fu. Thank you so much for taking the time to meet.

Thank you.