The 6G Era: Qualcomm's CEO on one of the "biggest transitions in wireless" | Titans and Disruptors

0:01 Every car, every bus, every bicycle, every pedestrian, everything is moving.

0:04 You're going to create a digital twin of the entire world.

0:08 Welcome to the edge of possible.

0:10 You may not have heard of Qualcomm, but you have definitely used their products.

0:14 Many major smart device manufacturers use Qualcomm's technology,

0:17 ranging from physical chips in our phones

0:20 to the G and soon 6g networks that connect them.

0:25 But in the lightning fast tech industry,

0:27 what's cutting edge today can become obsolete tomorrow.

0:30 Qualcomm, CEO Cristiano Amon, is prepared to bet the farm to stay ahead.

0:35 If you look about companies in the mobile

0:37 industry to every generation of wireless,

0:39 there was a big cemetery of companies, and we're still here.

0:43 Cristiano credits the 40 year old company's

0:45 success in part to its culture of reinvention.

0:48 In cristiano's Five years as CEO,

0:50 the company has evolved from one that's highly smartphone dependent

0:53 to one that's working in automotive robotics and wearable AI,

0:58 jewelry, pins, pendants, things that you wear,

1:01 and it can connect you to an agent I met

1:05 with Cristiano at Qualcomm's high tech headquarters in San Diego.

1:08 Robot incoming is giving us a big warning to discuss how

1:11 Cristiano and Qualcomm are building what could be our next primary device,

1:15 after the smartphone.

1:16 I'm Alyson Shontell, and this is fortune 500 Titans and disruptors of industry.

1:20 We'll be back with Cristiano after a message from our sponsor,

1:32 Fortune spoke with Deloitte us CEO Jason garzadas on understanding

1:36 quantum computing and how he sees it transforming industries.

1:39 Quantum Computing has been a topic for some time in research circles,

1:46 certainly closely watched by business,

1:49 but it's fundamentally a different computing paradigm that uses the principles

1:55 of physics instead of mathematics to drive the computing outcomes.

1:59 And I think the real uses will

2:02 be ultimately around very complex optimization scenarios,

2:08 further enhancements to scaling machine

2:10 learning and also very complicated simulations

2:13 that could be relevant to a whole host of different business applications.

2:18 What steps should leaders take

2:21 to prepare their organizations for quantum computing?

2:23 It's really about readiness planning right now

2:26 and preparing an organization to understand the implications,

2:31 understanding what skill sets would be required,

2:33 what type of cyber security protocols would need to be

2:38 in place to make it viable in an enterprise context,

2:41 and begin to think about the types of use

2:45 cases that would be very germane around optimization and simulation.

2:50 Cristiano, thank you so much for sitting with us

2:53 for the fortune 500 Titans and disruptors podcast.

2:55 You are sitting in the center of the universe of AI,

2:59 I'm not sure that people realize quite how much

3:01 Qualcomm is embedded in pretty much everything that they use.

3:04 From a device standpoint, can you maybe just give us some size and scale to it?

3:08 Your 117 on the fortune 500 about

3:11 5 billion devices are powered by Qualcomm chips, and counting and counting,

3:15 so kind of give us some scale to what you're doing here.

3:18 Yeah, by the way, thank you for taking the time.

3:20 Very happy to be here talking to you.

3:22 Look, Qualcomm's very unique company.

3:23 We used to say, before people got to hear about Snapdragon,

3:27 we used to say Qualcomm is probably the biggest company.

3:29 Nobody knows about it.

3:31 I think when we started,

3:32 it was about creating the fundamental technology that everybody uses now.

3:35 I think for wireless, we have been into every generation of wireless.

3:39 But as as you look at what happened with the wireless revolution,

3:43 and I think you look of our smartphone right now as most inseparable device,

3:47 our technology, basically propelled by the scale of the mobile industry,

3:52 starts to go in many different places.

3:54 And I think in today, I think Qualcomm not only is in the smartphones,

3:58 I think we enter into the PC space.

4:00 We are into the wearable space, those future personal AI devices.

4:04 We're going very large scale business on automotive.

4:07 It's in people's cars, and it's going to industry and industrial and all the way

4:13 to what they're going to be the future robotics and data center.

4:16 And I think we're very happy.

4:18 We're, you know, we we have a very large scale semiconductor business.

4:22 I think most of us grew up in the company within mobile,

4:26 but we started to see their technology

4:28 became relevant to so many other industries,

4:30 and I think that's what we're doing right now.

4:32 Yeah, I think of you all as sort of like

4:34 the brains of the tech that we use every day, and increasingly so,

4:38 whether it's the cars we drive or the phones that we use,

4:41 the computers we're on, you all are there embedded in the devices.

4:44 We just had a new issue of Fortune come out,

4:47 and our cover is the AI tipping point.

4:50 It feels like we're very much in a new wave

4:53 of AI where maybe it hasn't really hit peak consumer yet,

4:56 and people are still kind of wondering on the whole

4:58 What is this and how do I use it, and what.

5:00 To mean, but certainly from the standpoint of the capabilities of AI,

5:04 it feels like we're at this just straight vertical lineup.

5:06 Would you agree with that?

5:08 And what's happened?

5:08 Maybe you could give us, like,

5:10 some big picture of what has happened the last few months that has

5:12 made it so 100% I think we have been preparing for this point,

5:15 and we look at this a little bit different than some of the other companies.

5:19 You know.

5:19 We build a lot of devices that people, you know,

5:22 use every day, and devices how people are going to interact with AI,

5:26 and there are aspects of AI that are going to change,

5:29 you know, how we actually think about computing in general.

5:32 I think the way we look into this is,

5:34 everything we do, it's going to be processing some form of AI,

5:38 or connecting to the cloud, to, you know, to do a lot of AI.

5:43 This is how we're going to go to this transition

5:45 of computing that we don't worry about OSS, we don't worry about applications.

5:49 And I think what is causing this tipping point,

5:53 it's that in this year 2026 we've been saying

5:56 that that's going to be the year of agents.

5:59 It's now you have agents that can, you know,

6:02 make AI useful to do many, many different things.

6:05 And I'm going to break this down into different aspects.

6:08 When you think about the evolution of AI,

6:10 I think we all started heard about chat TPT.

6:12 There's a chat box.

6:13 You go and ask a question,

6:15 but then you also have this incredible development about how AI just

6:19 become the next higher level language that you can use to write code.

6:23 But then there are other aspects.

6:26 One aspect is, and we've been saying that, I think, since the very beginning,

6:30 which is now because of large language models, because of large visual models,

6:35 they understand the word the way we understand the world, communicate with us,

6:39 the way we communicate with natural language and and that creates

6:44 a new user interface between the humans and the computers.

6:48 And now, once you have all of those things put together in an agent,

6:52 that you can tell the agent what you want,

6:54 that's going to fundamentally change how we interact with those devices

6:59 and and with that, I think I started to get a lot of scale.

7:02 I think people are just starting to understand their agents for everything.

7:06 Now, their agents are going to go into the computer, do things for you,

7:09 is going to go to the cloud and do things for you.

7:11 And I think that is how we're going to start

7:13 to see massive amount of scale into every day,

7:17 things that we do on the consumer space, on the enterprise space,

7:21 and we're excited about that because it's going

7:23 to create a big cycle of new devices.

7:26 They're going to be intelligent,

7:27 they're going to be smart and be connecting us with those agents.

7:32 AI powered devices often demand lightning, fast networks to operate fully,

7:36 something that Qualcomm and Amman have spent decades building.

7:39 Qualcomm technology powered the launch of the 3g 4g and 5g cellular networks.

7:45 Amman, who first joined Qualcomm as an engineer

7:48 in 1995 directed Qualcomm's global 5g rollout.

7:52 Today, Amman is eyeing 6g which he believes will

7:56 deliver the efficiency and performance required by applications like holograms,

8:00 collaborative robots and driverless cars.

8:02 I was really struck by your MWC, your world mobile Congress,

8:07 conversation about how we've gotten from 2g to now 6g an ecosystem of you.

8:12 I was wondering if you could kind of walk us through that.

8:15 You've been at Qualcomm a long time, 30 years.

8:17 You're actually a boomerang CEO.

8:18 You were here, you left, you came back.

8:20 You've risen through the ranks.

8:21 Walk me through that transition in tech,

8:24 and what 6g means for people like you and me.

8:27 Every even number generation of wireless is huge.

8:30 So 2g was huge.

8:32 4g was huge.

8:33 Then 6g just being an even number is going to be huge.

8:36 But I think beyond that, I think 6g is one

8:40 of the probably biggest transitions we're going to see in wireless,

8:44 and it's going to be way beyond, I think, how we think about wireless,

8:48 just connectivity, but it's going to be also how

8:52 AI is going to be part of the networks,

8:55 and it's going to feel a little bit different for the entire sector.

8:58 I you know, one of the things I said in MWC,

9:02 and I wanted to be provocative on purpose.

9:05 You know, if you remember how telecom started, right,

9:09 you have a dial tone, and you call somebody, right, and, and all of a sudden,

9:13 you look at telecom today, it's very, very different.

9:15 You have, you know, a very high capacity,

9:19 you know, data network, where you stream television,

9:23 you do data, you do competition on demand,

9:26 you do a bunch of different services, way beyond calling somebody.

9:29 I think that type of transition is going to be also what's going

9:34 to happen when you go to 6g so we talk about agents a lot.

9:37 One of the things that we are seeing now with those agents and this new

9:42 kind of classes of AI devices is we're going to see, you know, devices.

9:48 We call them personal AI devices, glasses, for example.

9:53 It's very natural, because if the AI understand what we say,

9:58 what we hear, what we see.

10:00 Glasses is very close to our senses, like close to your eyes,

10:03 your ears, your mouth, you turn your head,

10:05 you see things and all of this information,

10:07 it's going to be very important context for agents to do things for you.

10:12 So one of the features of 6g of course,

10:15 is I need to have a network that everything that I see can

10:20 get streamed to the cloud at a very high performance and high speed.

10:24 So all of us are going to be walking cameras, right?

10:27 And this concept of See, what I see, is what 6g is going to do.

10:32 So one of the features of 6g that consumers

10:35 relate to, what is this radio going to do?

10:37 For me, it's going to be a very fast uplink,

10:40 if you think about what happened to G,

10:42 enable streaming on high definition video to your phone, to your to your laptop.

10:47 Now you're going to stream information up to the cloud,

10:50 which is going to be very important context for agents and for models.

10:54 That's the connectivity side.

10:56 But the big picture of 6g is because RF signals can be looked at as physical,

11:04 AI and what's an RF signal?

11:07 It's like a radio signal, radio frequency that go from the tower,

11:11 the base station, to your phone.

11:13 So that's how you transmit data, you know, over the air.

11:16 All of those signals, which are electric, magnetic waves,

11:19 we're going to look at those things as physical AI.

11:22 It's just sensor data,

11:24 and you can apply AI to the network to make sense of all of this things.

11:29 So if I give you an example, when I look at my automotive business,

11:33 and we have assisted driving and autonomous systems,

11:37 and we have input from a bunch of sensors,

11:39 there's cameras on the carbus also has radars,

11:42 like a radar, you know, send a signal.

11:44 I'll get a reflection back, and then he maps everything around you.

11:47 Sometimes, when you look at some demonstration or some advanced driving system,

11:51 you see the screen all of the different cars that the radar can detect.

11:56 So think about every single one of us connecting to the 16 network,

12:01 the radio that we transmit and we receive when the AI process all this data,

12:06 this is like a radar at scale.

12:08 So another thing that 6g is going to do,

12:12 not only at at your neighborhood, not only at the city,

12:15 at the state, but at the entire country level,

12:18 will map the digital twin, I think, of the world.

12:22 And that also become very interesting.

12:24 Of course, in today's I think environment,

12:27 if I say that, everybody will understand it like you can do drone detection.

12:31 You know, everything that is moving is going to be tracked.

12:34 You have a radar at scale.

12:36 You can manage the entire future aerial economy.

12:40 The things that we also look at maps and you see is there congestion.

12:44 Here is a green, is a yellow, is red with 6g you'll be able to map every car,

12:51 every bus, every bicycle, every pedestrian, every everything is moving.

12:54 What are the roads?

12:56 Everything around you?

12:56 You'll be able to use AI to refine and detect different objects.

13:00 You're going to create a digital twin of the entire world,

13:04 and that's going to be very, very important data for agents as we

13:08 continue to evolve how we think about computing.

13:10 So 60 is a big transformation,

13:12 are you probably so I'm very excited about it, I think.

13:14 And it's also for a company like Qualcomm.

13:16 It's perfect for everything we have been doing.

13:18 How we diversify, we can come up with an end to end story,

13:22 from the device to the network and to the data center.

13:25 There is so much to unpack there,

13:26 and I want to get to a lot of it so for like, just the average Joe out there,

13:32 it's more data, more personalized data than ever before will be collected

13:35 and will be usable to create a personal relationship with our devices.

13:40 But you know, there's so many applications for that that we

13:43 can get to a really granular level of understanding everything out there.

13:47 But I wanted to talk about that relationship

13:49 that we're going to have to our devices,

13:51 and then also what the future format could

13:52 look like for what our devices will be.

13:54 It sounds like we're moving from a relationship

13:56 with our tech that it's responsive to what we want,

13:59 to anticipating what we want and sensing

14:02 in the world because of all this extra data.

14:05 Is that correct?

14:05 Yeah, that's a good way to put it.

14:07 And I think one of the things you said, as you summarize it,

14:10 there's an important point when you think about

14:12 what our relationship with devices as an example like.

14:15 So for example, I think the first personal device we

14:19 we all got to experience in computing was the PC, like the first device,

14:24 and we started doing a lot of things on the PC,

14:27 but then the phone arrived, and what happened is people didn't abandon the PC.

14:32 You still have it.

14:33 You still use it.

14:34 It's incredibly useful.

14:35 But certain workloads did shift from the PC to your phone, given because,

14:39 you know, now you have the computer with you all the time.

14:43 As an example, when e commerce started,

14:46 people started to do a lot of all of e Commerce on your PC.

14:50 Most of the world right now will do e Commerce on a mobile phone.

14:54 So but now fast forward to what we're starting to see right now.

14:57 You see all those different companies building what we call.

15:00 Personal AI devices.

15:00 You saw a lot of the AI companies.

15:02 There are some secret form factors that I cannot tell you about it,

15:06 but I think we're we, we're working with pretty much all of them.

15:10 I think an AI meta, all of them, and you have different things that people wear.

15:15 Glasses is the easiest one to understand,

15:18 but they're going to be more they're going to be jewelry,

15:20 pins, pendants, things that you wear,

15:23 and it can connect you to an agent and now have this conversation.

15:29 If the AI understands what we write,

15:32 can read everything we read, see everything we see,

15:36 the type of use cases are going to be a lot more personal.

15:40 Needs to have a lot more context and needs to happen a little different.

15:45 Because, if it not, you just pull up your phone and you do it today.

15:49 So how do I describe that?

15:50 I think for you, like, for example,

15:52 you'll be walking around and you have a glass,

15:55 and you're gonna see, I really like this.

15:57 I like to buy this.

15:58 How much is on Amazon, and it's gonna say, Oh,

16:00 it is how this is, this is how much it is Amazon.

16:02 And they say, Can you, can you render how I'm going to look with this?

16:06 And and it's going to get rendered.

16:08 And so it's going to be a different kind of low friction experience.

16:11 And workloads are going to start to shift

16:13 in the same way that shifts from your precede to phone,

16:16 certain things you're going to do with an agent.

16:19 We even have this example that we often say,

16:23 which is, shows the importance of context.

16:25 You're going to be walking around, and the agent's going to say,

16:28 I just noticed you have 10 minutes right now.

16:30 Can you talk to me?

16:31 I have a conflict on your calendar.

16:33 I would like to ask you for options.

16:35 Like, it's very interesting,

16:36 how also those things going to interact across devices,

16:39 which is, you know, a meeting pop up,

16:41 and the in the agent said, you have a conflict with a doctor appointment,

16:46 you want me to call the doctor for you and reschedule.

16:49 And then, you know, actually call,

16:51 and it said, I'm calling behalf of this person.

16:54 You know, I would like to change the appointment.

16:56 What's your what's your availability next week?

16:58 So those are going to be different type of use cases,

17:03 and as they started to get developed with low friction,

17:06 we're going to see they'll start interacting

17:09 with them with other types of devices.

17:11 And the way to think about this, this is the way

17:14 we've been talking about the ecosystem of you as an example,

17:17 there's a big shift in the industry we

17:20 are coming from, and we're very proud of it,

17:23 because we had a big piece of that in a world that is a smartphone centric,

17:28 the smartphone is the center of your digital world.

17:31 And then what happens is,

17:32 everything is around that smartphone that's like, you pick your smartphone.

17:35 Are you going to do everything with it if you have a wearable device?

17:38 The job of the wearable device is

17:40 just to extend the functionality of your phone,

17:43 like people sometimes buy the wearable from the same brand at the phone,

17:47 because it's kind of right, like Apple has the Washingtons.

17:50 You send sensor data.

17:52 That's best now the center when you use UI in an agent,

17:58 the center of your digital life is no longer the phone is the agent,

18:03 and the agent will manifest itself on your phone

18:06 and your PC and across different devices.

18:08 You see a lot of discussions about experience across devices,

18:11 and when you have this shift,

18:13 the agent needs to understand context, to be proactive.

18:17 You have models to being trained today on all

18:20 of this data that we created and put it on the internet.

18:23 So you go in, you look at the books and social posts, and you train models.

18:28 Think about tomorrow,

18:29 if all of us walking around over cameras to see what we see,

18:34 that amount of data is massive,

18:36 will dwarf the data that has been training models today.

18:40 And that's how AI is going to evolve,

18:42 and it's going to be very personalized to you.

18:44 Qualcomm technology has been embedded in smartphones since the earliest models.

18:48 The company locked down early deals with industry

18:51 leaders like Apple and LG in the early

18:53 2000s and smartphones today are still about

18:56 75% of Qualcomm's high margin chip sales, but rapid advancements in AI are now

19:01 expanding the mobile technology landscape beyond the smartphone.

19:04 Rather than moving away from the phone,

19:07 Aman is leaning in developing new tools and systems

19:10 that connect and enhance the devices people already use.

19:13 You sit in a position where you see what Microsoft is building,

19:16 what OpenAI is building, what meta is building.

19:19 We talked some about the glasses,

19:20 but what future form do you think really will be the one that wins?

19:24 Look?

19:24 You're going to have many, right?

19:26 And the interesting thing about, you know,

19:29 those agents is they have to be with you all the time.

19:32 So that's why we saw the whole concept

19:34 of wearable is turning into a personal AI device,

19:37 and it's going to be things that you are comfortable wearing.

19:40 You have the mix now of fashion and technology,

19:43 and you have AI that people wear and for me to buy in stores,

19:50 like 2027 2028 I think so.

19:52 I You're going to start to see some of those towards the end of this year.

19:55 Amazing.

19:56 Yes, awesome.

19:56 So smartphones have been the primary device.

19:59 Do?

20:00 How much longer do you think smartphones will be the primary

20:02 device for I think it's already in the process of a change.

20:06 I think what is going to happen if I have to make a prediction,

20:10 and it's super hard to make those predictions first, I will say,

20:13 I'll give a 50% chance that I'll be correct,

20:16 but I'll say this year will be the year of agents,

20:19 and you started to see more and more form factors or things that people wear.

20:23 When you start to get to 2728 you're going to start to see workload shift.

20:28 The smartphone is not going to go anywhere.

20:30 But here's how I describe this.

20:31 If you pull up your phone, you have to pull up your phone,

20:34 open your phone and lock your phone, and you're going to do phone things right?

20:38 However, the phone is not natural for you to be pointing

20:41 at things or picking up your phone and you talk to your phone.

20:46 So as you have those other devices,

20:48 certain things, not everything, but certain things,

20:51 is going to be more intuitive to you to just do it like for example.

20:54 Let's say you wear a smart glass that has a camera,

20:57 and you get a restaurant bill,

20:59 and you look at the bill and has a QR code and say,

21:03 Pay this and just notify me What's completed.

21:05 And that's it.

21:06 It's done.

21:06 So I think what we're going to see within 2728 I think there's

21:10 going to be a lot of workloads going to shift to those devices,

21:13 and will those devices be on market by then?

21:15 You think we see the smart glasses already prices are starting to get on market.

21:18 I think 2728 they get scale like one of the things we we talk

21:22 about it is those devices right now are now in the 10s of millions,

21:26 I think in in within the next five years,

21:30 it's very possible they're going to go to hundreds of millions,

21:33 and going to get to billion.

21:35 And it's all about the maturity of agents,

21:37 and maturity of agents doing things for you.

21:39 And then it's going to become very, very natural.

21:42 And I believe that's how we're going to see

21:45 all of us going to have different devices.

21:47 And it creates another interesting dynamic.

21:49 Do you think there'll be a primary device for agents like,

21:51 will there be, like, the pendant or the glasses?

21:54 It sounds like you're pretty bullish on bullish on glasses.

21:56 Yeah, I'm very bullish on glasses.

21:57 And the reason because, look, I wear glasses,

22:00 but I think humans are very comfortable with glasses,

22:05 and glasses is very natural.

22:06 You turn your head, that's where the camera is going to see what

22:10 your what your eyes are going to be seeing is very close to your ear,

22:15 is very close to your mouth.

22:17 You're going to read something.

22:18 The camera can read it.

22:19 So glasses, I think is the primary form factor.

22:21 But let me tell something important about this.

22:24 When you buy a PC, consumer electronic device,

22:26 you buy a phone's consumer electronic device,

22:29 you have consumer electronic brands.

22:30 But when you think about things that you wear, because it's close to you,

22:34 close to your senses and agents, tends to be like very low friction, intuitive.

22:38 That's our fashion devices.

22:40 So now you have the mix of fashion and technology.

22:43 It's very interesting.

22:44 For example, if you look at some of the glasses company,

22:47 they can become a technology company.

22:49 Their multiple is going to expand,

22:51 but you're still going to be buying a fashion device.

22:55 Would you believe that a consumer electronic

22:58 company will do one glass in six colors,

23:02 and everybody's going to wear that, or people

23:04 going to pick the brand that they want.

23:06 And I think what's going to happen is you're

23:08 going to see more things that we wear becoming smart,

23:13 and it's going to be a new set of players.

23:16 One thing I can tell you with precision, every new generation of wireless.

23:20 Just think about mobile as an example.

23:23 The players change, the industry change.

23:25 So I think we're going to see that again.

23:27 So you'll think there'll be like an Apple or Google of the future AI.

23:32 I think in personal AI device is more horizontal,

23:35 and you're going to it's it's going to be less concentration.

23:39 Is going to be a lot more fragmentation,

23:42 because not everybody wear the same clothes,

23:44 not everybody wear the same glasses.

23:45 So I think you're going to have a number of different companies,

23:48 and the key thing is going to be the control point.

23:52 They used to be the OSS and the App Store, become the agents that you use.

23:56 And it's not going to be like one agent that rule it.

23:59 Oh, it's going to be different agents.

24:00 They're going to be different agents that you're going to choose to use.

24:03 And I think the interesting thing is,

24:05 you started to see things like with open claw,

24:08 and a bunch of things getting installed for open claw,

24:11 for anyone who doesn't know, is, like,

24:13 it was a big agentic AI moment that really took over the internet.

24:17 It was released, and it could do just incredible things,

24:20 although there's a lot of cyber security issues that came with it,

24:23 like people select digital wallets were coming online and things.

24:26 The reason I brought this example is because it's

24:29 just not unique to just those personal AI devices,

24:32 even your phone's gonna change.

24:33 As an example.

24:34 In the last earnings call, we talk about this, nobody paid attention

24:38 to but we we said that by dance in China,

24:42 you know, launch a smartphone, and the smartphone has had an agent like,

24:48 like, open claw, and basically is the same thing.

24:51 You talk to the phone, or you text your phone and you say, do this for me.

24:55 And you go to your phones and go

24:57 to your apps and started to start one app, close another.

25:00 Their app and start doing things for you.

25:01 So I think we're going to see the control point of the industry is changing.

25:05 It's not about the OS and the App Store.

25:08 It's going to be, what are the agents or the claw that you're going to select?

25:12 It's going to be multiple of it is going

25:14 to do things for you on your existing devices,

25:17 and then they're going to be new classes of devices that you're going to use

25:21 with your agent of choice to just going to be doing things for you as you go.

25:24 You know about your day, and I think that's how this thing is going

25:28 to pan out and how AI is going to get scale.

25:31 Maybe that's why I go back to how we started.

25:33 That's the tipping point as AI becomes ubiquitous.

25:36 Amman is repositioning Qualcomm to meet the moment.

25:39 The company has invested in the quickly growing automotive AI market,

25:42 which is projected to grow by more than 65% over the next five years.

25:48 Qualcomm's automotive sector generated a record $1.1 billion

25:51 in revenue in the first quarter of 2026 marking

25:55 its second consecutive quarter surpassing $1 billion in 2025

26:00 Qualcomm acquired semiconductor and wireless connectivity company alpha wave,

26:03 a key step into the data center business.

26:06 The company has also invested in smart home devices,

26:10 robotics and edge computing.

26:11 I mean, I could future talk with you all day long,

26:14 but I do also want to understand how you're navigating Qualcomm,

26:16 because in the last five years, you've been the CEO.

26:19 You've been with a company mostly for the last 30 years,

26:23 you've gone to lengths to diversify the business where smartphones

26:26 and your Snapdragon chip within smartphones is still the top business for you,

26:31 but it's not the only business line you have.

26:33 I'm curious how you have under your leadership really

26:36 put an emphasis on diversifying revenue lines for Qualcomm,

26:39 and how you've oriented your team to execute on it,

26:43 because now automotives is a big space for you,

26:46 meaningful revenue coming in every quarter, Internet of Things,

26:50 PCs, and those things were not to the scale of what they were five years ago.

26:54 So how have you oriented the team around this diversification mission?

26:56 It's a big, important topic for us.

26:59 I think it has been our priority.

27:01 I think my number one priority when I became CEO Qualcomm,

27:04 technology is relevant to so many industries.

27:07 We have ability to build a leadership position.

27:09 How do we do this?

27:10 And we do all of it at the same time,

27:12 which is not easy, because a lot of companies,

27:15 historically, they're not all very successful when

27:17 they try to go to do new things, develop new core competences.

27:20 I think the good thing is I could

27:22 always rely on a very unique asset, the company.

27:25 I think obviously very partial.

27:27 I think I also started Qualcomm as an engineer.

27:29 I think we have an incredible technical talent,

27:32 and I think that was the, probably the foundation to what we did.

27:35 We realized that we had a probably unique technology portfolio.

27:40 I think most people think of Qualcomm like they think about mobile,

27:44 but we have every single technology and wireless communication.

27:47 You know, not only seller,

27:48 we're number one Wi Fi and Bluetooth and position location,

27:52 but also we have every form of compute.

27:54 We do our own CPUs or GPUs

27:56 or neural processing units or image signal processors.

27:59 So I organized the company in the way that we could leverage and scale

28:04 our technology roadmap to serve the needs

28:07 and the requirements for all different industries,

28:09 like, of course, for example, if you think about our GPU from rendering screens.

28:14 When you go to a car, you have to rent 12 different simultaneous screens.

28:19 You have to scale that capability.

28:21 We have to build safety across everything that we do.

28:25 So we build that engineering machine

28:27 to scale our technology to other industries.

28:30 We build different business units.

28:31 They will be really focused

28:33 on building leading platforms that industry requirements.

28:36 We have to build a lot of different software teams.

28:39 And what is interesting about this is we actually

28:42 did this with the same level of operating expenses.

28:45 We went from being in the mobile business to now

28:49 being in the mobile the personal AI business, the PC business,

28:54 into the robotics, in industrial, in automotive,

28:57 all the way to the data center, and doing all of this in parallel.

29:01 It was not easy.

29:02 I think we put a good face on the outside, inside, like a pressure cooker.

29:06 But I think the culture of the company,

29:09 I think the company has a history of always reinventing itself.

29:12 If you look about companies in the mobile

29:15 industry to every generation of wireless, there was a big cemetery of companies.

29:20 And we're still here.

29:21 We survive all of it.

29:22 And I think this culture of the company to reinvent itself,

29:25 to be able to be the curiosity, you know,

29:30 the of learn new things, innovate, do new things,

29:34 enable us to build the structure and execute it in parallel.

29:38 I think we're probably misunderstood as a company.

29:40 I think people are always chasing the shiny object.

29:44 People want instant gratification.

29:46 I think when I look at investors, we have been on a journey.

29:51 It takes time of diversifying the business, growing the non mobile business.

29:55 I think as we get to the end of the.

30:00 First half the year, we're going to in our investor day.

30:02 Now, the date been set up.

30:03 We're going to say what we're doing in data center,

30:05 which we're very excited about it.

30:07 But I'm a big believer in Qualcomm.

30:09 I think what's unique about Qualcomm is we're probably

30:11 one of the few semiconductor companies that can do

30:14 a sub two milli watts chip in a 2000

30:17 watts chip for a data center within that range, all of it in parallel,

30:22 and that's kind of the motivation I have to keep

30:26 executing on this strategy and diversifying growing the company.

30:29 Your ability to, like almost bet the farm on ideas as a CEO

30:34 and kind of get the team oriented in that direction is great,

30:37 and it also takes time.

30:38 You have 75% of your business being a smartphone

30:41 business five years ago to what is it today?

30:44 Look I think our goal is to get to about 5050,

30:48 in 2029 I think we now been executing to about $22 billion of completely

30:54 non mobile business by 29 and that doesn't include some of the new bets,

30:58 such as the data center as an example,

31:00 especially, I think you mentioned something about betting on idea,

31:04 not only betting an idea, also dealing with a lot of skepticism,

31:07 like when we said we're gonna go to automotive and said,

31:09 you guys don't know anything about automotive.

31:11 You were going to buy an XP,

31:13 then go through there's no way you're going to succeed.

31:16 And look at today, we're probably the largest

31:18 provider of Advanced Silicon for the automotive industry.

31:21 Same thing.

31:22 We entered the PC.

31:23 Everybody said, nobody can go into PC if you don't have x86 and we said,

31:27 well, I don't think so.

31:28 We're just gonna keep executing this.

31:29 Market's gonna change.

31:31 There's now people understand convergence between mobile and PC.

31:34 It's just Apple just launched the Neo that is based on silicon for mobile.

31:38 We always believe that.

31:39 So I think that's now it's going to be our industrial and robotics business.

31:43 So that's the conviction, I think that's the confidence in our technology

31:48 and ability to build a leading platform,

31:50 and the fact that, you know, we can compete and win in the marketplace.

31:53 I want to talk about two of the new lines of business,

31:56 and some are brand new, but data centers, I think are you really made a big

32:01 announcement last fall that you're going into the space,

32:04 and I'm sure more to come later this year.

32:06 A lot of the capex spending from tech

32:08 companies has been going into data centers.

32:11 We know it can fuel the future of AI,

32:13 but it also comes with issues the energy situation here that prevents the scale.

32:18 There's a report in Bloomberg recently that half of data center plans are

32:21 kind of stalled or being canceled because

32:23 of material issues and things like that.

32:25 And then there's just a bigger consensus of, like, are we over building here?

32:28 Could this, like, run companies into problems who are pouring lots of money in?

32:32 Can you give me a big picture of, like, where we are in this AI data center,

32:35 boom, and unpack that for me, because that's there's a lot here,

32:38 everything we've been talking about, what's going to happen with AI,

32:41 it's going to change every compute you know,

32:42 it's going to process a lot of data.

32:44 Is going to have more and more data.

32:46 I think the demand for AI computing, and especially inferencing, because, see,

32:50 you train a model, but then you wanted to put into production,

32:54 that's inferencing, that will continue to increase,

32:57 and it's going to I think the demand of compute is is going to be high.

33:01 And the way I would describe this, whether people talk about,

33:05 is there a bubble, another bubble, here's the simple way to describe it,

33:09 and maybe a bad example, because I don't think is exactly like

33:12 that, but, but it's the only example I can provide.

33:14 Let's go back to the year 2000 when there was the.com bubble, okay,

33:19 when people were saying what the internet is going to be at that time,

33:24 I will tell you right now, 26 years later,

33:27 the internet is way bigger than people thought.

33:30 Whatever they thought it was small versus whether what exactly happened,

33:33 it didn't happen all in one year, but it did happen.

33:37 I think in the long run, AI is probably still underestimated.

33:44 The amount of computes and the amount of data is going to continue to increase,

33:49 and it's going to increase, not only on the cloud, is going to increase,

33:53 all the devices going to be processing AI, just trying to imagine this future,

33:57 we're talking about all the different devices and agents and all of that, I

34:01 think that is going to continue to go we can have an argument about,

34:05 is the slope of the curve going to change?

34:09 Is everybody now playing to win right now, I like to go back to this internet

34:15 example in the year 2000 in the very beginning,

34:18 probably people said Mapquest is going to be the map, right?

34:22 And maybe it isn't, or or could,

34:25 and in my space, are going to be the social networks.

34:29 Maybe it is.

34:30 Maybe it isn't.

34:30 I think we saw what happened.

34:31 There's a first mover disadvantage there in a new market.

34:34 So I think what's going to happen is, it's too early.

34:36 Everybody's playing to win, and there's going to be,

34:39 maybe there's going to be a handful of winners.

34:43 Maybe there's more.

34:44 We don't know.

34:44 You could argue, you know there will be.

34:46 As we go the next few years,

34:48 you're going to have different changes in the slope of the growth,

34:51 but the growth is going to be very high,

34:53 and will continue to be very high on the short term, you have other issues.

34:56 This is the growth of compute.

34:58 This is the energy availability.

35:00 That is the reality.

35:01 I think Silicon moves very fast.

35:04 Energy infrastructure projects don't, especially here in the US,

35:08 and I actually think it in many cases, is going to be like a global phenomenon.

35:12 All of this creates an opportunity, and let me give you an example.

35:16 Phone has nothing to do with data center,

35:19 but I'm going to give you a phone example,

35:22 because that's kind of informs how we're thinking about

35:25 what we're going to be doing in the data center.

35:28 The phone is a very, very challenging engineering problem,

35:31 because if you look of your phone today,

35:34 and you look at your phone, go back all the way to the feature phone, right?

35:39 Your phone has an incredible amount of computing power.

35:42 There's a lot more things you do with your phone, but still fits in your pocket.

35:47 It cannot get hot.

35:48 You're going to touch your face, and the battery didn't change much.

35:52 The battery, the energy that you have,

35:54 is the energy that you have, and it has to last all day.

35:56 If it didn't last all day, it's not useful.

35:58 I have to pack a lot of compute density in a very small space.

36:02 I cannot have liquid cooling, and I don't have unlimited power.

36:06 I cannot plug in thing to the wall.

36:08 So therefore, I had to go do something called the disaggregated computing.

36:12 I have to design this specialized computing for every task.

36:17 The way I'll give you an example is,

36:19 I think you'll probably remember when all of us had

36:22 iTunes and iPods and in the PC when mp three started.

36:27 A lot of the mp three decode will be done by the CPU, not in the phone.

36:33 CPU burns too much power.

36:35 We have to have a dedicated accelerator just to do mp three decode.

36:38 When you take a photo, we have a dedicated accelerator.

36:41 Just do JPEG encode as an example.

36:44 So when I look what's happened at the data center, I like to do this parallel.

36:48 This is the demand to compute.

36:49 This is the energy.

36:50 So it's like, okay, you have to design

36:52 a different architecture that it's going to map, what's the energy availability.

36:56 So I think there's going to be, now this new trend of of different architectures

37:02 for the data center is going to be energy efficient,

37:05 and that's why we believe we have a role to play.

37:07 For example, when we start talking about post GPU architecture,

37:12 people you know said, you guys don't know anything about this.

37:15 You don't know what you're talking about.

37:17 The GPU is the do all is the is the is the solution for data center,

37:22 then Nvidia with grok,

37:24 people say, Well, maybe there are different architectures for different things,

37:27 and that's exactly what we're doing.

37:29 We're basically building a solution that is going

37:32 to be from a CPU perspective and inference perspective,

37:35 is going to be more energy efficient,

37:37 and it's going to be designed for when AI gets

37:40 scale and and companies are going to have to compete,

37:43 total cost of ownership matter, and it's going to have,

37:47 like, a different architecture about Compute and memory.

37:49 And I'm optimistic about it.

37:50 I think we're going to tell the world what

37:53 that is towards kind of the end of June,

37:55 and that's going to be the next mission.

37:57 I'm spending, personally, a lot of time with this, and excited.

38:00 I think that that's where maybe Qualcomm has a role to play.

38:03 One more on where you're heading.

38:04 I want to get your perspective on robotics.

38:06 There's all been a lot of predictions about bipolar robots are going to be like,

38:09 there's gonna be a billion of them on the streets doing all sorts of things.

38:12 It was just starting to really hit in industrial robotics.

38:15 Seems like that'll be the first place we'll really see them.

38:17 But the Judy Jetsons robot in your house feels farther off.

38:20 Can you just give me some perspective on robotics?

38:23 As you probably noticed from this conversation,

38:25 I like drawing parallels and looking at things that we

38:28 can learn from the past and apply in the future.

38:30 I will do a parallel between robotics and automotive for us,

38:34 the reason we became successful in automotive is because you

38:38 cannot put a server in the trunk of a car.

38:40 So we needed to do a lot of computing.

38:42 You needed to have very energy efficient and I think that's

38:45 why it was very natural for us to go to robotics.

38:48 Robotics is an edge, AI problem, like a car is an edge, AI problem.

38:52 And then my parallel comes when we think about RoboTaxi and assisted driving,

38:57 when we go to automotive, in addition to providing silicon for the digital

39:01 cockpit and processor for, you know, Adas and autonomy.

39:05 We also started to build a stack for assisted driving.

39:09 And what you realize is, there was everybody thinking about a RoboTaxi,

39:13 and we're going to get there,

39:15 but a RoboTaxi takes a long time for you to train, you know,

39:19 you can get you train a stack from zero to 95% but if we for you to go

39:23 from 95 to 99.999 so it's safe to the point

39:28 that you remove the steering wheel of the car, you just sit and wait.

39:32 That requires time, require mileage, require a lot of training,

39:37 but the opportunity for assisted driving when you there to pick

39:41 up the steering wheel if you need it, that's massive.

39:44 You can do that in every car.

39:46 That's how I think about robotics.

39:48 It's going to start with industrial it's going

39:51 to start with tasks that a robot can do.

39:53 You can perfect a robot to do one particular task.

39:58 You can train the robot on video.

40:00 You, you can train by doing that.

40:02 We call tele operations, that the robot will imitate.

40:04 It will be very good at that task.

40:05 And then you download another task.

40:07 We'll do another task.

40:08 The robot is going to walk with you, do everything for you in our house.

40:11 And that's going to take time, you know,

40:14 because every house is going to be different,

40:16 how you navigate and all of those things.

40:18 So I drew that parallel.

40:19 I think there's a massive opportunity

40:21 for robots in a lot of industrial settings,

40:25 like something simple as restocking a shelf

40:28 at night in into a grocery store, a supermarket.

40:31 So we've a lot of activities from our customers

40:34 interest in our chips, many of it, it's kind of the same recipe we use

40:39 in automotive that's going to be a big opportunity.

40:42 And then eventually the level of training

40:44 and maturity will be like the RoboTaxi example,

40:47 that we're going to have general purpose robots like the Jetsons.

40:51 I think they the opportunity is big.

40:53 I think, you know, physical AI, enable those things.

40:56 We like that as Qualcomm, because, like a car that's an edge.

41:01 Ai, the AI needs to be in the robot.

41:03 And versus cloud, there's going to be things in the cloud,

41:06 but the the robot needs to do everything in real time.

41:11 And that's really the robot is the perfect case of an edge.

41:14 AI.

41:15 And the robot has different levels, I think, of intelligence.

41:18 We call them like system zero, system one, system two.

41:21 System zero is like, you know,

41:24 you get the robot and supposed to grab something and escape,

41:27 and he go and grab it again.

41:29 He has to be super fast, very low latency.

41:32 System one, you tell the robot, pick up this in this table,

41:36 then the camera will see, recognize, that's what it is to pick it up.

41:40 System to reasoning and do things in the robot plus the cloud.

41:44 It's a great opportunity, and I think we believe it's going to be significant,

41:50 especially when you think about dedicated industrial use cases.

41:53 And it could be robots in all sizes and form factors as well.

41:56 Amman is a techno optimist.

41:58 Since taking the reins in 2021 Amman has

42:01 helped turn the tech of science fiction into reality.

42:05 Qualcomm is pioneering hands free driving humanoid robots and AI

42:09 tools designed to proactively finish tasks before they're even asked.

42:14 The company's San Diego headquarters is

42:15 a living lab of these projects in action,

42:18 but skepticism around AI remains high in the US.

42:22 A 2025 Pew Research Center survey found that half of the American

42:26 public are more concerned than excited about AI entering their daily lives.

42:31 Amman and Qualcomm want to bridge that gap,

42:34 turning extraordinary tech into everyday tools.

42:36 In a world where we already are feeling some tech lash, there's like,

42:40 small movements where people are saying, oh, throw out my phone, my smartphone.

42:43 I just want to be on a flip phone again.

42:45 Or kids are resisting Facebook, and they're like, you know, doing other things.

42:48 Are we just too close to it?

42:50 Like you and I love technology, and you wear glasses,

42:52 and, you know, you want lots of data.

42:54 But do you think actually the public and the consumer will

42:57 want to be sharing everything about their lives and data like that.

43:00 It's very difficult to answer this question,

43:02 but I think I will answer this with two different data points.

43:06 One data point is, if it's useful, if it's useful,

43:10 if it's helpful, users are going to embrace it.

43:13 I think we have seen, we've been talking about this issue of a privacy but if

43:18 you just look at what happened over the past few decades,

43:21 I think more and more, I think users, especially on the consumer side,

43:25 signing up for different platforms if it's useful,

43:28 if it it's it, it's removes friction.

43:31 It's a better way for them to do things.

43:34 I also think agents will remove a lot

43:36 of the clutter that exists with technology right now.

43:39 The other part of the answer, it's actually more important.

43:42 This is going to further separate who are should be the custodians of the data,

43:48 who are the trusted companies, who are not the trusted companies.

43:50 Because this, when you think about all of us,

43:53 for example, being walking cameras,

43:55 this is now a significant level of capability above and beyond,

44:01 I think, what we have today,

44:03 and that's why we see a lot of interest, for example,

44:06 in 6g it gets often associated with conversation

44:09 about sovereign AI and a bunch of other things,

44:12 because it becomes like a critical infrastructure,

44:15 not only because of the ability to detect everything that is moving is flying,

44:19 but also because of the amount of data that is from all of us,

44:25 which are going to be walking around and doing

44:27 things in the world and sending data to the agents.

44:29 So it's going to be a different world,

44:32 but it's kind of what we have seen over the past decade.

44:34 Is just going to be an evolution.

44:37 More and more data is going to be on the cloud,

44:40 and the consumers are more mature about it,

44:42 and there's going to be a lot of regulation about,

44:45 you know, what to do with this data.

44:46 So that's an interesting way of kind of thinking

44:48 about who the winners of this could be.

44:50 I think, like, it's so much of the AI world,

44:52 it comes down to, like, who can you trust, and what do you trust?

44:55 And if anyone can create these devices

44:57 eventually using these powerful llms IN THE.

45:00 Agents, then it probably will come down to like,

45:02 would you rather have apple with your data,

45:03 or would you rather have meta with your data?

45:05 Those are probably the trade offs consumers will have to make.

45:08 The consumer is always a more complicated discussion,

45:10 but let's just talk about enterprise as an example.

45:12 That's exactly what you started to see right now.

45:15 You have a lot of AI use for coding for enterprise.

45:18 You have open source, you have different companies provide the service.

45:21 Just look about how companies dealt with their email,

45:25 for example, their email, all of their internal data.

45:28 Who are the cloud companies that those companies

45:30 have trusted to provide the service to them?

45:33 So I believe you're going to see a lot

45:36 of those things and create actually business opportunities

45:39 for a lot of the enterprise companies go back

45:41 to the comment you just said open claw when it started.

45:44 People said, Is this thing safe?

45:46 But you're going to see that there are going to be open

45:49 claw version of some of the major companies in the world for enterprise.

45:53 And then you're going to say, Okay, I will trust this company with my data.

45:58 So I think that's how this is going to evolve.

46:00 We see now, claw for phones, claw for PCs.

46:03 It's going to be in your car.

46:05 It's going to be everywhere.

46:06 So I could feel the techno optimism just like oozing off of you.

46:10 You're so excited about what you're building and as you should be,

46:12 and you're really powering this AI future that we're all going to live in.

46:16 I want to get your perspective on there's a disconnect between, like,

46:19 our level of excitement for this, and the average

46:22 person's excitement for this, people

46:24 are seeing things like open eye just came out with the 13 point proposal,

46:28 equating the moment to the New Deal era, progressive era of history,

46:33 where we need a new societal structure, a new tax structure, new everything.

46:36 Jobs might not be the same or even exist to some extent.

46:40 How do you level with that, like,

46:43 how do we get your optimism to be contagious in a world where

46:46 it seems like there's a lot for consumers to fear with this feature?

46:49 First of all, we really, really thinking about, how can we build, you know,

46:55 efficient computing that enable this technology

46:57 in the way that can empower people?

46:59 And I think we have, at least we have a track record,

47:03 which is the smartphone you know,

47:06 like everything you know, like every new technology you you can misuse,

47:10 you can you know, you're going to have some drawbacks.

47:14 But you look in aggregate,

47:15 I think what the smartphone enable is connected everyone,

47:19 empower people with information in many countries,

47:21 we see that all the time how people actually became

47:24 digitally capable and actually experienced the internet for the first time,

47:28 it was with a smartphone.

47:29 And I think AI has this capability to empower people.

47:33 I am not one of those that think AI is going to be better than humans.

47:38 I don't think so.

47:40 And maybe because some of the chips that we

47:42 do are the chips that the humans use.

47:44 But I will give you my personal reaction to this.

47:48 I don't know if it's right.

47:50 It's it's just my personal reaction.

47:53 I graduated in engineering school in the early 90s.

47:57 It was 92 you still have on the early 90s.

48:00 You go to the office and there's a fax machine,

48:02 and you get a bunch of fax and I remember,

48:04 look at the facts, and you have to type another message and send it.

48:07 And then email started to happen.

48:09 And then the internet happened, and and you think about it,

48:13 how big of a debt transition was when we didn't have the internet,

48:17 we didn't have things like email, and then we had the internet.

48:21 It changed how we do work.

48:23 Those are bunch of different tools,

48:25 fundamentally very different I also look the same

48:27 way when you think about a software programmer.

48:29 We start computers will program in assembly

48:32 language like Steve is the actual machine language.

48:35 All of a sudden you have a higher level language like C that you

48:39 can write in a higher and now you have the AI that writes for you.

48:42 So I look at those things as very powerful tools, and it can be misused,

48:47 but it's going to be probably as big of a change as when the internet arrive,

48:53 and we survived that.

48:55 So I'm more of an optimist than a pessimist on this Well, I hope you're right.

49:00 That sounds like a great future.

49:01 And thank you so much for sharing your insights.

49:03 No problem.

49:03 Very happy to have this conversation with you.