Future predictions for the year

Hello and welcome to this episode of The Times Tech podcast where each week we unpack how technology is reshaping business , culture and everyday life. I'm Katie Prescott sitting here in the city, the city of London, and a very, very happy new year to you. I hope you had a fantastic Christmas break if you were lucky enough to have one and you got all the gadgets that you wanted in your stocking. So on the random end of presents, I dodged giving my kids any tech this year and my daughters got stick in sets, instead, real ones, which have been keeping us all entertained as we try and work out what they like to eat. I hope other kids got luckier with their parents. But speaking of unwrapping presents, twenty twenty six is shaping up to offer lots more gifts in tech. And I was thinking the other day reflecting on the year just gone and believe it or not, it is only just over three years since the launch of Chat GPT, which propelled us really into this new era of advanced AI and that has just upended everything . I joined the Times just before this all started and I do feel very lucky to be on the tech beat following the twists and turns of it and meeting some of the larger than life characters that the sector seems to attract. So we thought on today 's episode as a good way to start the new year, we'd gaze into our crystal ball and ask what the year ahead really holds. And what better way to do that than to speak to Stalwarts of the venture capital industry , the people who place bets on which tech and which tech companies are going to be the stars of the future. So by now you may have picked up that you're not hearing the dulcet tones of my co host Danny Fortson. He is still enjoying a well earned winter break, but we will be hearing from a recent chat that he had with an investor John Callahan of True Ventures based in Silicon Valley that has funded companies such as Bluesky. And I am joined in the studio today by Hannah Seal from Index Ventures, the Transatlantic Fund whose remarkable hit list includes Dropbox, Epsy, Figma, and Revolution. Welcome to the podcast, Hannah, happy . Thank year you. Happy New Year to you. Delighted to be here. Kids didn't get stick insects for Christmas. Well, they got sea monkeys actually, if you remember sea monkeys , which they're very excited about. They're growing very nicely. So guess our kids got similarly unlucky with their parents . You give me inspiration for next year. That's a good one. I wanted to start on the big picture and perhaps picking up on a lot of the chatter at the end of last year, which is, of course, are we currently in a bubble with all of the money that's pouring into AI ? And I just wondered what your reflections were on that. And I know it's a massive topic, so perhaps we separate out what's going on in the public markets and the private markets. But what's your view as we head into twenty twenty six ? I'm pretty optimistic actually. And I think it's easy to think it's a bubble because the numbers are just so big. And it is really like nothing we've ever seen before in terms of these sort of huge volumes of the funding rounds and the valuations that are abounding. But my view is that AI is such a transformational technology that's touching not just software but also you know real world applications, physical world applications , robotics, healthcare, pretty much every industry globally will be touched in some way by AI and these like huge subsets of GDP, like healthcare and services that in many areas these huge valuations are actually justified because the impact that the technology is going to have is just so widespread and so transformational . So I do think some of these valuations are justified and are sort of based on the impact that AI is having . Having said that, there will be winners and losers in AI and I think this year we'll also see some consolidation and some players continuing to succeed in others where perhaps the quality of revenue was lower or the value they were adding was not what was thought of or the technology or product is becoming commoditised. I think some of those businesses will struggle but at the other end there will be continued to be these big winners with huge valuations. I guess the question is when is the other end, right? Because I keep hearing from people that yes, it is going to be transformational and have an enormous impact on everything . But presumably between now and that point and those returns being delivered and the impact of the technology there's going to be quite a bit of destruction or potential for destruction. Yeah, and I think what we'll see this year is last year was a lot of large enterprises sort of dabbling with AI. And the boards were saying, Oh, what are you doing with AI? You've got to do something with AI that's this important technology. How are we transforming the business, making it more efficient, increasing profits with A . So every large enterprise was doing something, trying to build something themselves, messing around with open AI, doing lots of different things. And there were kind of budgets flowing because everyone sort of was experimenting. And I think this year there'll be a lot more scrutiny on AI budgets. Okay, where are we actually seeing ROI? And I think that's where we'll see some of the sort of winners and losers actually starting to appear, which is the few companies that are really showing like meaningful ROI for these businesses , they will continue to get the budgets and maybe increase budgets and the others will start to sort of see a lot of churn from their customers and actually it's going to be a difficult year for some of these other companies. So I think this year we will start to see the beginnings of that sort of bifurcation of winners and losers in the AI application space. And how about the circular deals that we were seeing which link what's been going on in the public markets with the enormous valuations of say the magnificent seven and then the private companies such as OpenAI and Anthropic also with their massive valuations. I mean, I think that's something that is also an enormous concern. Yeah, and it's it's an unusual situation, obviously. So we will we will see how that plays out. I mean it's baffling to me as it is to you right on top of one another. Investment is made with the promise of buying from the company that's made the investment, for example. Exactly. But I think the hope and the expectation amongst many investors is that these companies like OpenAI and Anthropic and many other private companies, they will continue to build this groundbreaking technology, which is then used I mean on the other side of it is the revenues are growing astronomically, right on both the consumer side and the enterprise for these sort of businesses and more and more use cases are coming every day. So there is a lot of substance underpinning these valuations and the investment that's flowing into these companies, but obviously there is a lot of questions to still be asked. How about in your world? When you see companies crossing your desk at the moment, do you think ooh, they're looking really expensive because there are so many investors who are wanting and looking for the top AI companies at the moment or do you feel they're about right? What's the market looking like? The reality is every really good company always feels expensive. In AI or not in AI, at the beginning of some of the best businesses we've invested, they've always been expensive because the demand is always there for the top one percent of companies. So I'm not sure this is necessarily an AI phenomenon. There is always a huge amount of capital and demand chasing that top one percent of companies and that hasn't changed. It's obviously got more intense, I would say , but that's also a reflection of the fact that outcomes are larger. It used to be that a couple of billion was an amazing outcome in venture ten, fifteen years ago . Now we're getting outcomes fifty one hundred billion. I mean, look at revolution , for example, still a private company. The latest valuation is seventy five billion dollars, which is would have been almost unthinkable a decade ago. So in many ways, the high valuations are being justified by the sort of longer term opportunities for these companies to become hundred billion dollar businesses. And what are you particularly excited about in the year ahead? What are you going to be looking for? I think in venture, it's interesting that a lot of what we invest in, it's not like we're sort of going out necessarily and looking for a particular company in that solving that problem or in that theme. Many of the companies that we end up investing in, we haven't even conceived of the idea. You know, it's these like brilliant entrepreneurs that come up with this outlandish concept that sounds crazy in many ways. So we have to stay open minded and opportunistic. And especially in this era, so many areas that a few years ago you wouldn't have thought were investable by venture capitalists like more services heavy industries or robotics or manufacturing industrials, healthcare are now suddenly being opened up because of AI to being investable for us. So there's now a lot of new sectors that we're starting to look at. I mean, it's a sort of slightly separate topic, but a lot of sort of the negative chatter about AI is oh it's going to take away jobs and we'll come to that. Sort of disasters, but interestingly, in the past few months, a lot of the businesses that we've been seeing have been solving labour shortages . So actually in industries where it's not about taking jobs, it's about actually like resolving the demand that is in these industries where there's actually no labor to do the job. So we saw one company a few months ago that was building robots to make brick walls because there's this huge shortage actually almost globally of construction workers to actually build houses in other buildings. And there was like a robotic arm that was putting the bricks and the cement together which, sounds simple actually pretty complicated building sites or pretty complicated places, but that's not one that's taking away jobs. That's one that's actually like enabling the economies to build faster because they're solving this labor shortage. And I mean, healthcare is another area, you know, we all know the shortage. And I think AI probably the past couple of years, the biggest use has been more of like the back office admin for doctors like transcribing and doing the sort of the manual routine work, but we are going to move into a phase where it starts to take over some of the more high value work that doctors do, the diagnosis, screening, that sort of thing, which is a great thing for the economy and there's a shortage of doctors and other healthcare professionals. So a lot of what we see is actually in areas where there's this real immediate burning sort of shortage and AI is coming in and technology more generally is coming in to resolve that. So I expect to see more of those sort of businesses this year, which is exciting. And has there been a shift in the past few years on the sorts of things that you're seeing, the volume, perhaps? Yes, I think with any technology cycle where people get very excited, you always get a lot of volume and a lot of opportunists actually coming in and getting AI into their pitch deck. Yeah, and it's like a way to make a quick buck, you know, build an AI startup and hope that you're sort of somehow acquired quickly or whatever. So there's definitely a lot of noise and a lot of companies. I think we see a couple of different arch etypes of founders that are coming through . One like the technologists, you know, PhDs who are real academics but now see that this is their moment to build a company, which is interesting . But on the other side, we also see the type of founder which is in my view pretty necessary for this market, which is like very adaptable , very malleable, very able to move for the time. So I think what is tricky in this market is if you are sort of too stuck in a way of working or in using a certain type of technology to solve your problem because I've never seen a technology cycle that moves so quickly. Every day, there's a new model that comes out, there's new technology. There's competitors coming from every different angle, every different market globally. There's always something new. So you have to be adaptable. You have to be flexible and you have to be able to move quickly. So those are the type of founders that we're seeing actually succeed really well in this sort of new AI market are the ones that are very able to adapt to sort of changing circumstances and not too sort of stuck in the old ways of working. Hannah, as you were saying, one of the areas that we talk about a lot as having massive potential when it comes to AI is of course health care and drug discovery and that sort of thing. And the question this year is whether we're finally starting to see it happen some sort of significant scale. And that's something that Danny put to John Callahan from True Ventures. I think one of the things that I'm starting to think about, and I'm wondering what you're seeing is science because like from the moment we had the chat GPT moment everybody's like, well, we're going to have automated scientists. We're going to be able to live forever, we're going to cure all cancers, we're going to solve climate change. All of these things , genuinely I've been trying to find like companies who are like, actually, we're going to use leverage this infrastructure, these tools to actually do hard science and solve some of these like intractable problems. Is that a thing that is happening when you think about like twenty twenty six moving forward A few different things to look for , perhaps in the power of AI, first of which would be in biology and health, your point in uncovering new treatments, basically treatment pathways for intractable diseases for us. And the other is there's a bunch of innovation and around material science as well. And I think that is likely one of the big stories of twenty six and seven, which is that there are a number of companies funded back in our case in twenty twenty and twenty twenty one, a company you're starting to hear a lot about called InVada, founded by Bishwa Kolaru, InVada and Boulder using the power of AI basically for new types of drug discovery across a number of very important disease categories and having remarkable success, remarkable speed, remarkable sort of proof in the data. And so what are they doing? Like could you be a little bit more specific around drug discovery? Like what are they enabling that wasn't happening before? Yeah, so just the sheer scale of capability to process elements of biology and understand what elements of biology could potentially be applicable to some of these disease states. And the staggering number of biological compounds that we understand, it's, you know, it's something like three or four percent that we do understand and ninety seven percent that we don't. So insanely large data sets, incredibly complicated causal relationships and compound relationships that AI is perfect for. And AVA has in a very, very short period of time, has many, many incredibly promising candidates for conditions that would have taken traditional pharma decades decades decades . The thing to look for is or I should say, are these breakthroughs? Are these moments when companies sort of come out of nowhere with incredibly promising treatments or devices or compounds? We've got another company that shows the power of this, actually it's in London Basecamp research. They've built one of the world's largest databases of biological data from all around the world. So they go survey incredibly remote places, find the only place on the planet where one species of plants grow. They sample all of that. They have built a large data model and a foundation model of their own and a data set of their own that understands these relationships. So there is there is a reality behind the hype is what you're saying. Yeah. When you start hearing about these companies, the questions to ask her exactly is like how long would industry have taken to do this? In some cases, you know, in the basement of research case, their data set, I think, is the largest, certainly larger than any other private organization, but I think they're larger than any single public organization as well. But how does AI enable that because don't you actually have to go out and get the goods like, go out in the physical world and find the plant basically. Yeah. Okay, so stepping back, trillions of dollars being spent on infrastructure, right? Both obviously in the GPUs, obviously in the training runs, obviously in the inference capabilities, power data, all that . In any prior innovation wave, the value that's been built on top of infrastructure has been somewhere on the order of a low of two or three to a high of five to ten ,X the number of infrastructure investment. So that's like one way to look at it, but the other way to look at it is just, again, the power of these tools because of all that infrastructure investment, it's so capital efficient to build these things right now. And so you can attack insanely large problems like biology or material science or pharmaceutical or large disease conditions in health with tools that you've never had before and you can do it with really small teams. And AI's designed exactly for that to handle insanely large data sets at scale. Quite a lot to get into there. On the healthcare point, is that something that Index looks at at all? Yes, we do look at healthcare and we've made quite a few invest ments in the space in various areas, whether that's more on the sort of the back office and the admin side and then we've also done things all the way to drug discovery. I mean, it's healthcare is obviously such a huge space . And especially here in the UK. Yeah, exactly. And it's interesting. People have often said healthcare is an not interesting space to invest in the UK because there's the NHS and it's very difficult to serve the NHS, but actually, in many ways, it's an advantage for us here in the UK because we've got sort of one place where the data is stored and if you can get into the NHS and if the NHS is willing to work with you, it can actually be a huge advantage because there's less fragmentation than there are in other markets. But I think maybe one of the reasons why it might feel to the average person that AI hasn't impacted healthcare so much is because despite the fact that there are all of these sort of new discoveries in the drug space happening, you know, there's still regulation. It's still a highly regulated industry so you still have to then do the clinical trials and pass all the regulations. So these things aren't immediate. They will take time, but I'm really optimistic that there will be diseases that will be cured in our lifetimes that we may have never thought possible because of AI. I mean , I remember ten years ago when I came to this industry, people were talking about self driving cars and I felt right in five years time there's going to be self driving cars everywhere and my kids are never going to learn to drive and I'm never going to buy a car again. And we're only just starting to see self driving cars on the streets of the UK, hopefully coming this year, but it's taken time. Behavior change takes a long time, regulation takes a long time. So I think even sometimes even when the technology is there, as we see when you go to San Francisco, you see Womos everywhere. So the technology's there, but sometimes these things just take a lot longer to proliferate than you might anticipate or hope for. So I think a lot of these sort of technological advancements that are around will actually take longer unfortunately than we might hope to become mainstream. It was interesting they were talking about infrastructure as well because at the start we were talking about this idea of a bubble, whether there's a bubble or not and a lot of that is coming from the huge expenditure on AI infrastructure. In terms of the UK's AI infrastructure, do you have a view on that at all? I mean, I hear a lot of people saying actually we're quite far behind the US , China, Jensen Huang even said I think London Tech Week last year that were the biggest AI market without any AI infrastructure. Yeah, definitely I mean we're definitely behind if you look what's happening in the US and as you say in China, it's not been an area where the UK has invested heavily . You know, we focus more on other areas. And I think UK can be, you know, outside of data centers. I think we can be an AI powerhouse. We have some of the best universities in the world. We have Deep Mind that's based here. So there's a lot of reasons why the UK can really be this epicenter for AI, especially in Europe, but we've got a lot of work to do on investment and bringing talent here and really making it a focus. So I think investors and the broader sort of tech ecosystem are trying to do as much as possible, but yeah, it's going to it's going to take work. Does that data center point? So it's been traditionally very difficult to build data centers here . You need space, you need power . Power is very expensive in the UK. We don't have that much space. It's quite complicated. The government's trying to make changes to adjust to it, but obviously this takes a lot of time. As an investor , is that a hindrance to you? Is it something you hear companies talking about? Not really, because the founders that we tend to back are ones that are dead set on solving a particular problem or have a mission and they will figure out how to do it whether there's data centers in the UK or not, right? Like they will they'll solve that problem. Interestingly, we have a company coming in up a photo called Ethflux that's building data centers in space . So one of those one of those exactly thing . So there's always new innovation on every front that crops up. So the best founders will figure out a way to break through whether that's how to build new data centers and outside of Earth. So yeah, get around planning for mission exactly as way possible . I want to pick up on the jobs point because it's something I think listeners are really concerned about and intrigued about and just watching how AI is shaping the workplace and changing everything . You gave that lovely example of the robot building a wall and doing work that perhaps we can't find people to do . But clearly it is also changing the workforce. And if you look at, for example, what's happening to coding and the amount of big Silicon Valley companies that have said actually, we areinking shr our workforces, or we're just not hiring more people, which is what Klan has said, for example. Where do you see that going and what are the companies that you work with seeing? Yeah, I think there's two different s path actually in the question. So the companies that we work with, interestingly, and we spend a lot of time asking our portfolio companies about this, they are cutting jobs or slowing down hiring. What they see is that they can just move faster. So they're actually almost hiring more and more quickly because they're doing so much more, so much more quickly. So with, for example, coding tools, you can just build software faster, which means you can bring forward your product roadmap and do more . So they end up hiring more salespeople and more people in other areas to actually sort of satisfy the demand for these new products. So we're not seeing in the data of our portfolio companies that they're cutting jobs at all. In fact, it's the opposite. They're growing faster because of AI and they're hiring more. However, I think it would be naive to think that outside of tech, the broader economy isn't going to see some shift. I'm an optimist, so I think that humanity will figure out a way eventually to find new roles for a lot of people. But I think there will be some discomfort in the short term and people that will need to rescale because jobs will become obsolete. But as I said, you know, I think these things take a lot of time to filter through and things don't tend to happen as quickly as we expect them to happen. So I think it will be a slower burn than we might expect. There are probably a lot of jobs already today that could be made obsolete but because of challenges in changing behaviour or regulation , the jobs will persist . So I think it will happen but slower than we might expect. And I think on the flip side, there will be new jobs that will be created because of AI so that overall sort of employment will maintain. I'm not, you know, one of those people that thinks that we're all just going to have nothing to do and we're going to have, you know, leisure time and we're going to have to lovely thought beach. Yeah, in every industrial cycle, there's always, you know, a period of discomfort before new jobs are created. And I think this won't be any different, but I think it is inevitable. On that discomfort point, I wonder if it plays into what you were saying earlier about this just taking a very long time to integrate into companies, particularly large ones. And it feels like AI's been used as productivity tools for individuals who might have maybe co pilot, if they're a Microsoft user or whatever , but it just takes time to embed something like this an organization? Yeah, and I think there's been a few obvious use cases for AI that organizations are quite rapidly adopted. So obviously like software engineers, they're early adopts of technology. They've adopted these coding tools that's fairly low friction . If you ask most of these engineers, would you like to go back to a world without these tools? They'd be absolutely no way. I can't live without them anymore. They make me ten, fifteen, thirty, forty percent more productive. Customer support is another area where we've seen a lot of activity because it's a very obvious use case for AI and very clear ROIs. But beyond that, what we're seeing is a lot of large enterprises, they know that AI is a transformational technology, but they don't really know how to unlock other use cases. So on that issue of jobs, the question about what AI does to jobs is clearly absolutely massive. And this is something that Danny asked John about as well. The sort of promise of productivity when it comes to work versus the fear of job losses . How do you think about this whole jobs question? Because it's big and it feels like dangerous territory because you can see the seeds of a backlash if people are just like , why is AI good for me? Yeah. Now it's hard to get a job. There's a lot to worry about with AI. Just say that. Like there's a lot of we don't know what I wanted to hear, John. You know, we don't look we've built things like social media. We built things like self driving like these have large impacts on society, the things that we're building as an industry . In terms of jobs, though, the five year number, I don't see that. Five years is not, it's too fast. But beyond that, ten, yeah, I don't know if I would say jobs are gone though,. Jobs are different and I am a firm believer just because I'm a student of innovation throughout history. And every time we've had a large technological advance, there has been disruption, but there's been incredible social productivity gains that have led to growth. And we've had these worries with every single the internet. This one is much more scary because AI has the promise, if you will, doing everything in our lives. Therefore, it's much more about me for every one. It's much more scary for everyone. Yeah. So I think there's a lot to be afraid of and a lot of people are afraid. But I don't I don't see in the data in my sort of primary day job. So actually there's a before I get to that there',s an article on Wall Street Journal a bunch of COS were surveyed. Do they expect white collar jobs to increase and then coding and whatever? And I think the majority was that they expected increases not decreases. And maybe that's you can automate a lot of things, but that allows you to if you have better customer service that's AI base, maybe you sell more stuff or more devices or more goods or more services in the non AI economy. And that enables growth. That would be the thinking that we have observed in every other technology way. What I do see every day is not that AI is going in enterprises and they're therefore firing lots of people. I'm not seeing that at all. These are very large IT projects. They usually have hiring associated with them and or redeployment of people. The startup companies are hiring themselves lots of engineers to put on site for deployed engineers, FDEs is the big new trend. So this job change in displacement possibly, but it is not the case again at a unit level with portfolio companies that we're talking to an enterprise that they're going in and saying, we're going to let you remove half of your X or Y Z team. That's not part of the sales pitch. It just feels like the industry's done a really bad job at selling the positive case . And maybe it's because it's too hard to envision, because if you're like, well, if we can have these new agents that are gonna approximate what you or I can do or anybody can do in any kind of knowledge work . It's maybe it's almost too hard to imagine, okay, well what's the next generation, what's the new generation of jobs that are going to be enabled by these tools? And what do those new companies look like, right? So I'm sure you do. I use the tools for literally every aspect of my business and life. It's allowing us to do way better work, way faster with a lot more depth. I mean, it's very capital efficient. The industry now is very capital efficient, meaning it's easy to start companies, but I mean, look at just the size of the startup industry is swell. I mean, it's absolutely booming. So I think you're going to see dislocation, but I think you're going to see some very, very large companies built because of these tools, not just in the industry, but because of and many, many more of them. I like the way that John at the start said there's a lot to worry about with AI. And it feels to me that those worries which were so prevalent when Chatti launched and just that year afterwards, when do you remember the government held that AI safety summit in Bletchley Park and pulled everyone together to talk about risks and safety? It's rather fallen off the agend a a bit. Does it feel like that to you? Yes, it almost feels like the cat's out the bag. AAAI is here and it's here to stay. And there seems to have been just a bit of sort of inertia and like, we don't know how to regulate it , so we've just feared at the beginning . And actually it seems to be generally a force for good rather than anything to be hugely worried about. But I'm an optimist. And there is definitely people, especially in Silicon Valley that are huge pessimists and are terrified of AGI and what that can mean for humanity. These technology's falling into the wrong hands, but I sort of trust humanity to figure that out. And you know , very optimistic. And I think we will, and we may have challenges along the way, but I think we generally will, and I also think AI is very, very far away. So artificial general intelligence is the most advanced form of AI when it can sort of approximate how humans behave . Yeah, is more advanced than humans, but I think we're quite far from that, even though there's a lot of companies working on that. You know, I think if you go to Silicon Valley and spend a lot of time there, it feels more intense. It's everywhere . And everyone it's all that everyone talks about constantly. It's very different to us sitting looking at the city of London, big financial centre, exactly lawyers, money, but tech, but you know, a bit of everything. Exactly. And I think that's healthy in a way because it gives you a bit of perspective. You know, I speak most of my friends aren't in technology. They're doctors or lawyers or journalists. And when you talk to them, actually, their lives haven't changed a huge amount. Maybe they've got a little bit better in many ways. You know, for my accountant friends, they use some of these AI tools and their jobs are way better . And for the lawyers, they use these document review tools and that sort of thing that well , it takes all the grunt work out of being a lawyer. And I'm sure there's many things that journalists can now do with AI that actually makes the job more enjoyable. So you get a bit of perspective at one it's not yet all consuming and actually there's a lot of positive to take from it and there are a lot of other industries outside of technolog y that are, you know, substantive and contributing to the world. So I think being in London gives you quite a healthy perspective and sort of less of the doom and gloom of perhaps AI that you might get in Silicon Valley. That's true, you're not in the cauldron of it all. Yeah. So before we wrap up, I just want to touch on this issue of risk and AI again because for all of the excitement around it and all of the things that we've just been talking about, there is still a huge amount of concern about the possibility that we lose control of the technology in some way. Hannah, we'll get your thoughts on this in a second, but for one final time, here's Danny and John Callahan . And based on everything you're seeing, what keeps you up at night? How does this go wrong? There's a lot of scariness here and like I'm thinking personally I just wrote a big piece about Australia 's social media band for under sixteen's. Personally, I was like, that feels like a pretty reasonable place to have got to seeing what's happened over the past twenty years. Absolutely. I'm dying to see your piece because I was just talking to my kids and families about that that and experiment and their experiences. And I think we as an industry well, I don't think any of us have understood kind of the unintended consequences of the technologies that are being created that have been created. And I would of course believe it's been incredibly good for the world and et cetera, et cetera. But there are a lot of unintended consequences. And I think that is certainly a very big risk of what we're creating with AI. Yeah, because also millions of people are using these things as friends and girlfriends and therapists and you're starting to see more of those really disturbing cases of when things go really wrong and it's our next societal experiment which we're running in real time . Running in real time and I think running in real time because there is a large societal need for someone. I mean same with social media. It's solving a human need or desire. But yeah, I think with incredibly unknown long term consequences . We were both saying it'd be good if they brought in that social media ban here both having young kids. Do you feel the same about AI? I mean, do you see parallels there? I think it's a little bit too early to tell what the unintended consequences of AI are going to be, or which there obviously will be many . It's technology in general. We just can't lose our humanity and our human connection, but I think what we're already starting to see is, you know, in many ways a desire for more in person activity. You know, travel is increasing. People want to meet in real life. People want these in person connections. So I think we will see the backlash to all of this technology use and the new opportunities being created out of that. I do think about it a lot. I don't know what the unintended consequences are, but I think we will see a reaction to that . And I definitely agree that social media should be regulated. I think it's almost like sort of tobacco was many years ago. It's just been a free for all and I think now we're only starting to see the negative societal consequences and I think it has to be regulated, especially for young children. Let's end on a more upbeat note. What are your tech predictions for twenty twenty six? What do you see coming down the track over the next twelve months? Yeah, I'm very optimistic about twenty twenty six . I think there's going to be a lot of great stuff coming. I think it will be the year where AI budgets in big companies are scrutinized, but you start to see a lot more money flowing to the big winners, the big companies that are really adding real value and solving real problems for companies and we're going to see even more impact in terms of efficiencies in these companies. I think on the consumer side , what we'll see is a move from using AI sort of passively to answer questions, you know, where should I go on holiday or trying to sort of self diagnose with some symptoms to actually using it as more like an agent. And not just where should I go on holiday, but okay, can you book me that hotel? Can you book me that flight? Can you recommend me restaurants and book them and now send semi itinerary to my friends? So a lot more on the personal productivity side that AI will enable consumers to do this year, which I think is an exciting development. And then I think we'll see a lot more interesting companies being created across a wide range of industries, so not just in enterprise software, which is where a lot of the activity we've been seeing so far is, but I think we'll see a lot more in healthcare, a lot more in robotics , manufacturing, industrials and lots of other segments of the economy, law accounting, finance that have so far not been sort of massively affected by AI, but I think will be this year, but hopefully positive developments. And no bubble . No bursting bubble? I don't think the bubble will burst. I think we will see winners and losers and I think there will be some consolidation and I think we will see who are the companies that are really def ensible, really adding value, and really building something meaningful and others that were sort of more hot air. But I think overall the AI economy will continue to grow and there will only be sort of more use cases and more advancements across a wide range of areas. So no , I'm bullish that this AI momentum will continue. The governor of the Bank of England can sleep easy in his bed because he is why he's got some V. He's got other things where I'm about but yeah, it's one of them. Thank you so much, Hannah, for joining us. Thank you . That is it for this week's episode of the Times Tech podcast. If you're enjoying our show, please follow, like, and subscribe or leave us a rating. It does help other people to find us. And if listening to more podcasts is part of your new year's resolution, check out some of the other ones that we make here at the Times, as well as tech, we've got politics, geopolitics and business covered. And one of my favourite listens this year so far is the general and the journalist who've been looking at the US attack on Venezuela. So if you want to understand what really went on there, do give it a listen. Next week, Danny and I are back together and we'll be talking to Nigel Vaz, who's the boss of Publicis Sapient, that company which connects brands and marketing with the tech that delivers it, a company which sits under the massive publicist marketing group. See you next time