The deep AI shifts that will reshape our lives

0:00Hey, folks, Jeff Berman here, co-host of Masters of Scale. I am thrilled to share some of the new names who will be joining us at this year's Masters of Scale Summit. They are the leaders driving the most pressing conversations in AI. Replit founder and CEO Amjad Massad, Cloudflare's Matthew Prince, Signal president Meredith Whitaker, and many, many more who will take the stage this October 20th through 22nd in San Francisco. We want you there with us too. Join us at mastersofscale.com slash pioneers. That's mastersofscale.com slash pioneers. AI is everywhere and so is the noise around it. Hype, fear, jargon.

0:47I'm Jess Love, host of the new podcast Life Automated. Thoughtful conversations about AI that go deep without getting too technical because you shouldn't need to be an AI person to make sense of the future we're building. Life Automated is produced by Kellogg's Ryan Institute on Complexity and distributed by KQED. Find it where you get your podcasts.

1:13I would characterize AI as a general purpose technology, which has the ability to influence an economy and a society over time such that it becomes a platform for other invention and innovation. So nobody in the Western world is like, oh my God, electricity. That's so cool. You know, it just is. And thankfully, right, we're in a privileged place where we can even say that. We're going to hit a point where the things that we talk about when we talk about AI will just kind of be like electricity, just part of what powers other things. But it is not evolving in isolation, and it also doesn't work in isolation.

1:59So it's a pretty significant force that impacts everything else that's happening. Amy Webb is a futurist, an author, and CEO of Future Today Strategy Group. She says we've entered a convergence era, an era defined by the collision of technologies, capital flows, geopolitics, climate pressures, and behavioral shifts at scale. In this conversation, Amy and I unpack her 2026 convergence outlook and dig into AI-driven forces that are reshaping businesses and daily life. But most importantly, we discuss how leaders can take these insights and apply them to their organizations. I'm Rana El-Khalyubi, and this is Pioneers of AI, a podcast taking you behind the scenes of the AI revolution.

3:00Amy, so good to see you again. Thank you so much for being here. I know. I feel like we only see each other virtually these days. We've got to figure out how to connect in real life. But maybe the kids aren't doing that anymore. They're just extremely online and extremely AI. So, you know. My daughter's actually really into in real life experiences. So I think, but I think we have a game plan. I'm coming to New York. Visit your office and then get a curly hair haircut. Yes, I will tell you who it is, but not publicly because I don't want this person to become overrun and I can no longer book her.

3:34So we'll talk about it. I'll text you it later. I love it. That's awesome. Okay, so let's dig in. I am ready. So you've been publishing a Tech Trends report since 2008, and it's been read by millions of readers. I think the latest version of it had a thousand pages. It did. And then this year at South by Southwest, you killed the report. And you actually, I wasn't there in person, but I watched it. You actually did a whole funeral thing, and it was very cute and funny. So yeah, instead of the Trends report, you released the Convergence Outlook. So I was kind of thinking in my mind, like, is a convergence like Outlook just a rebrand of a trends report?

4:16Yeah, that's a great question. Yeah, how is it different, right, fundamentally? Yeah. So it's a very good question. A trend report is really just this is our definition of a trend and we track longitudinal trends. And a trend has to meet certain criteria. It's the combination of signals that sort of come together over time. There's a whole data model behind it. So these are just individual. Here is a thing that we have noticed in the trajectory that we see it headed in. And at the moment, you know, we've got a thousand plus persistent trends that are evolving as they're emerging that we're tracking because we have to track that as building blocks for other inputs to our work.

4:54A convergence is the intersection of multiple forces and trends and uncertainties that intersect and create the sort of net new. The combined impact is greater than any one of those things alone. And there's system level changes. A convergence would happen over multiple domains versus a singular domain. And convergences are always present. The key difference right now is that we appear to be in a convergence cycle. So rather than one or two convergences popping up, instead, there are a whole bunch of them kind of happening at the same time. Convergences tend to redistribute power and value. So a trend might cause something to accelerate or decelerate.

5:45But a convergence influences who will win, where power will concentrate, you know, what things might change. And then, crucially, they are hard to reverse. So once a convergence is really in motion, there's really no way because it's a systems level change. So all of the different systems reinforce each other. That's the core difference. And then what's in the outlook is pure analysis. So we spend a little bit of time explaining what it is and the rest of the pages explaining what does that actually mean and how does that shape things going forward. Yeah, I definitely want to get to how do we action all of these convergences in our conversation.

6:26But let's unpack some of the convergences first. So you have this map in your report. Topological map. Yes, that we are going to pull up. So, Amy, what are we looking at here? It looks like a topological mountain range-ish map. Yeah, help us read this. What we are looking at is something my team was like, nobody's going to understand what you're trying to say here. So I spend a lot of time outdoors, and I spend a lot of time hiking and on my bike and looking at maps like these. And a topological map is important not just to figure out how to get where you're going, but also so that you can have a better sense of terrain and how that terrain may be shifting and moving around.

7:19So to me, that was a fitting metaphor for the convergence landscape. And what we're trying to show are the forces that are in play and the convergences and how they are pushing or impacting those different convergences that we've identified. So that would include, where is the ground stable? Where do we think there are some pressure zones? Where do we think there are fault lines? And the point is to help organizations identify individual actions that they can take so that they're not sitting on their hands, you know, and unprepared when a seismic shift, if you will, happens. So let's pick AI that is right at the center there.

8:06And actually, it is like a key force in a lot of these convergences. Is that the right way to think about this? Yeah. Here's the thing that I think people are missing. So artificial intelligence itself is not a single technology, as you know, and as I'm sure listeners of the show know pretty well. You know, it's an umbrella term for a constellation of various different technologies, some of which are now self-improving in different ways. So I would characterize AI as a general purpose technology, which has the ability to influence an economy and a society over time such that it becomes a platform for other invention and innovation.

8:52So nobody in the Western world is like, oh, my God, electricity. That's so cool. Right, right, right, right. It just is. We're going to hit a point where the things that we talk about when we talk about AI will just be like electricity, just part of what powers other things. But it is not evolving in isolation, and it also doesn't work in isolation. So AI is a driving force behind the frontiers of agriculture, where there's really interesting things happening now. And obviously, like longevity science, which I think people are probably somewhat aware of, but also continual monitoring and recording, making the physical world parsable, and even going as far as to regulate, like regulating our emotions or interacting with us in some way.

9:45it's a pretty significant force that impacts everything else that's happening. Given that AI is so central to a lot of these convergences, let's unpack some of them. And I just picked a few that I thought were particularly interesting. So the first one is compute shock. And I love that you use the word shock. Your point of view is that there's huge demand to use AI, but the physical infrastructure to support it, so its data centers and all of that, is really lagging, right? Right. So I would love for you to explain what is that gap and how is the U.S. specifically addressing it? Sure. There are some components that make up this convergence.

10:29And some of this stuff, like, we already know. Exponential AI workload growth. And in some cases, if not the growth itself, then at least the hype. So people are talking so much about the potential for the growth that it kind of becomes its own thing. Specialization of compute hardware. And this one is kind of big. So we've got specialized chipsets and CPUs and TPUs and GPUs and all of the potential opportunities and constraints in the supply chain and the geopolitical arena that come along with that. Memory constraints. Power is another. We know this. It's a binding constraint. It's so interesting to me.

11:09people talk so much about data centers and not at all about the power lines leading up to the data centers, which is kind of interesting. Thermal management, water management. Like cooling. Cooling. And this is a politically sensitive area. From my point of view, the breathless, apocalyptic discussions about water scarcity are somewhat overblown. Really? Not immaterial from my point of view. I'm one person. Wait, can you say more? Yeah. Look, to some degree, it depends. So we have a server rack in our house because my husband and I, we don't have hobbies. We just build more computer stuff, I guess, and so does our daughter.

11:59She's 16. So she's actually extremely offline, except for she wants to be a designer of things and structures off planet. That's all she's at lunar architecture. Cool. Yeah. Is that a thing now? Wow. That's amazing. It is becoming a thing. I didn't know it was a thing. And this has been her only thing now for like six years. She's got a whole plan. So we tend to tinker and build and print and whatever stuff. Our basement is full of computers and it gets warm down there. Okay, right. Even though it's a basement. So like the point that I'm making is like, even our rinky dink kludge together system, you know, needs to be cooled.

12:46And that's just like the system we've got running the various things in our house. there's a proposal to build a Manhattan-sized data center in Utah. You know, you have to keep things cool. But there are other ways to do it besides just water. It's not as simple like data center means the lake next door is going to dry up, which is where the conversation devolved to. Yeah. Oh, my God. Like investment opportunity, right? Like who is innovating on these cooling technologies? Yeah. Like I want to talk to these people. 100 percent. I mean, the interesting irony of Compute Shock is we we could wind up with a whole bunch of climate solutions or at least attempts at climate solutions to resolve.

13:38As a side effect. Yeah. As a as a net positive side effect, I think. Yeah. Yeah. So Forbes recently reported that France's president, Emmanuel Macron, said that unless Europe competes at a much higher level in AI, it will end up as a colony of either the U.S. or China. And in this global race to build a sustainable AI infrastructure, yeah, that is a concern. So can you talk about how other countries are handling this compute shock and where does the U.S. stand? Yeah, well, I would love to add one little layer on to what Macron said, he's not wrong. And as it relates to artificial intelligence, the United States has had this sort of totally laissez-faire, meaning like an economic terms approach, right?

14:26So just let everybody throw spaghetti at the wall and we'll see what sticks. and then the capital follows without a plan. And that's fine because it does mean much more potential for innovation. But anybody who believes that a thousand new AI companies will bloom and survive is kidding themselves. We will always, because of our economic structures, wind up with just a few people and companies who are at the nexus of all the power. And we won't have any plan anyways. So a lot of times when we've seen this type of technology super cycle in the past, what results are lawsuits on the other end, which is exactly what's happening.

15:12In China, that's not the story. So China has these five-year plans that come out every couple years. And the current five-year plan is all about infrastructure. So China's going to let the United States pay to do all of the R &D. They're going to fast follow us. Right. And then they'll just implement it. Yeah. So but by the time they're ready to adopt, you know what will be the difference between Europe, the U.S. and China? China is going to make it so that every single person can be online. Everybody's going to have access to broadband in an affordable way. The entire country is orienting itself toward a future in which everybody can use technology.

15:54And the crazy thing is, if you talk to people in China, which I do, and you talk to people in the U.S. and Europe, which I do, the Americans are like, AI is going to come and take our jobs and then murder us in our sleep. Or it's the opposite, right? It's going to usher in this magical unicorn era. The Europeans are more skeptical. I spend time in the Middle East. I know you do, too. So there's, I think, some amount of we're here too. Don't forget about us. Right. And a lot of investments, obviously, in AI infrastructure. And yeah. That's right. But China, people are more concerned that they're not learning fast enough and therefore they can't keep up with their colleagues.

16:34It's a totally different attitude. More of my conversation with Amy after this short break.

16:59Every day, it's getting harder to tell what's real and what's not. Alex reassured me that he was a fully licensed and certified psychologist. But in fact, Alex is not a person, but it is an unfeeling chatbot. I'm Dexter Thomas, and every week on my podcast, Killswitch, we look at the right now of living in the future. To help you take back control of your life, listen to Killswitch in the iHeartRadio app, Apple Podcasts, or wherever you get your podcasts.

17:33The business world is moving faster than ever. And when change hits, we need to learn in real time. On Rapid Response, you'll hear candid conversations with CEOs and leaders making tough calls about AI, human talent, responsibility, and the bottom line, how they navigate uncertainty, pressure, and high-stakes moments. I'm Bob Safian, former editor-in-chief of Fast Company, and I'll be your host as each episode breaks down what you need to know right now. You can find Rapid Response wherever you get your podcasts.

18:39We'll see you next time. It's anything but business as usual. Find Masters of Scale on Apple Podcasts, Spotify, YouTube, or wherever else you get podcasts.

18:58There's also a lot of discussion about whether or not the cost of compute is less expensive than the cost of human labor. And actually, one of my investment theses is that AI is eating into the labor market. So I'm curious, how do you think about the cost of compute versus cost of labor? I will say that as a maxim, history is not necessarily a good predictor of what the future is going to look like because, you know, you have to update your priors. Things change. with a lot of technologies that fall within the realm of things that are automated. With some time, the cost of running something automated versus the cost of human labor always inverts.

19:45So the cost always starts high and ends at zero, right, or negative relative to what it would cost for a human. That was true with the printing press. That was true with certain factories at the beginning. I think that's going to continue to be true. At least it seems to be going forward. Now, the big shift we're seeing is not just with human coders, so people writing code. It's also because physical AI is a thing now, right? We're starting to see interesting human jobs become less important. So let me talk about sports for a moment, because that's like, that's the thing that like nobody would think of.

20:24So in a lot of endurance sports, you would have a coach and the coach would look at your body and look at your data and think about how you're eating and all of these different things. And, you know, with a calculator and a pencil, try to work it all out. Customize a plan for you. That's right. In more recent times, we have access to different types of computers. So runners have a heart rate monitor they can wear. I talk like I know what I'm talking. I don't know what I'm talking about with running. Cycling, I know. I've got a computer on my bike. I have a watch. I've got all these sensors. I've got sensors in my pedal.

21:05And after a ride, I can see when and where my pedal stroke was lagging. I can see what my breath was like when I was climbing. I can see all these data. And I have a tool that I kludged together that will analyze a lot of those data. There are similar apps now that are being deployed for football scouts. So previously, scouts for teams might have traveled constantly and gone at all these high schools and watched kids playing soccer. There are apps now where the kids will record themselves on the field, playing, kicking. They get scored based on whatever system is. And then those scores are sent to, instead of a fleet of scouts, like one scout, right, who's using those data to make decisions.

22:02Absolutely. Okay. So you were already alluding to this, the living intelligence convergence. I would love to hear your definition of living intelligence and some of your favorite examples. Sure. If you've not heard of living intelligence, it's a term I made up a couple years ago, so don't worry. So living intelligence is the convergence of artificial intelligence, advanced sensors, and bioengineering. And they create this flywheel and a sort of omnidirectional system of data flowing. So the data's flow into the systems and back out of them, And that creates a adaptive system that can learn and can act.

22:44So Walmart had this, they never deployed it, but they built a grocery cart that when you put your hands on it, it started collecting your biometric information. So there were sensors all over the place. Yep. Sensors and cameras in the store. and the concept was as you're roaming around Walmart, you get to aisle six and your kids are screaming because they want cheesy poofs and you're having a bad day, it's hot. You know, like everybody's upset. All you really want to do is like find not cheesy poofs, but you know, whatever the third thing was on your list that you just want to get out of there because the store's too, whatever.

23:22The grocery cart would sense that you are super stressed and it would ping a command center and a store associate would come and find you on aisle eight, recognize you and be like, how can I help? Let's do this together. What is it that you're looking for? That's pretty cool. So it depends on your perspective. That is either really cool or really invasive. But that is some of the reality of a world in which the technology systems become alive and use our data in real time. Yeah. I'm very passionate about the applications of this in health and wellness and what are the different sorts of sensors that could be on my body, in my body, around my home, etc., that can help paint a more comprehensive picture of my health and wellness.

24:19And then be actionable, right? The key here is how can it be actionable? Yes. Yes. So I don't know where you sit on the spectrum. I wear a whoop quite religiously, and I will sometimes make decisions on what to do or not to do because I don't want to mess my green streak of recovery scores and whatnot. So what do you think of all of that? I look my family had weird health issues growing up my mom got sick very young so I lost her at a very young age to cancer it was a neuroendocrine cancer my father had all kinds of issues and Parkinson's so it's it's tough to see loved ones go through an illness and that really prompted me to do everything I can.

25:11You know, we got one chance and, you know, I'm a robot, right? And like, I got to take care of the machine. So I have always been interested in, you know, having access to data. But the data alone aren't useful. You need physicians in your life who are willing to work with those data and who know what to do. We've got, you know, systems learn a lot about us and people are incentives, incentivized to get more clicks, therefore to say more crazy things. So all the data that you can scrape, you know, physical data you can scrape, totally into it. But I think you need a good guide to make sense of it.

25:56Yeah. Love it. I'll be right back. But first, a quick break.

26:25So the last conversions I want to dig into is one that's actually very close to a lot of the work I've done, which is - I figured you would want to talk about this. Can you guess? Emotional outsourcing. Yeah. So as you know, I've spent my entire career building emotional intelligence into machines, not to replace humans, but to augment our abilities to understand and connect with one another in a very digital technology-driven world. I'm going to quote you here. We're outsourcing empathy. AI systems now provide validation, reassurance, and companionship at scale, replacing relationships with people to platforms designed for sticky engagement.

27:04Can you unpack all of that? Sure. Does not sound good. It doesn't feel good either. So, look, we've been tracking a lot in this space. And the reality is, for a variety of reasons, we are short of healthcare providers. People can't afford healthcare. There are many valid reasons why mental health crises are on the rise. People are more isolated. So we know all of these things. Technology has removed the friction of resolving those issues. Depending on whose study you look at, in this country, somewhere between, I think it's 30 and 50 percent of Americans have used chat GPT for mental health. which means that an LLM now is the largest provider of mental health care services in this country.

28:00Oh, wow. That's such a crazy way to think about it. But it's true. I know. It's true. And like the issue is that that is not what that system was designed to do. I don't think anybody was intentionally being malicious, but there are some invasive ways that these systems that everybody has access to are starting to impact how we feel. Just as an example, I was thinking about getting different glasses. And my husband's an eye doctor, so I got a guy. I can get glasses when I want. I took a photo of myself and I sent it in. I think it was to Claude. I don't remember. That's like having an affair, Amy.

28:42Like, what? I know. I know. But I was like, what should I get? You know, style me. and pretty quickly it devolved from this shape because your face is very oval. You know, this is the shape and here is why that you should look at. Instead, it was like these heavy glasses are making you come off as overly academic. It was like making a judgment. The point is, look, it's taken a long time, but I'm now very self-assured and confident. And in a moment, that confidence eroded. Wow. Erodded. I suddenly felt self-conscious about the glasses that I was wearing. And then like, finally, I snapped out of it and I was like, what the, you know, this is ridiculous.