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So the upside from AI when we look at it, I think at a high level there are four really profound areas that should lead to optimism. Number one is the economic upside. In the US alone, it's estimated that the upside is about 4 trillion to GDP over the next several years. And we're already seeing with small businesses, for those small businesses that are applying AI to whether it's how they reach out to customers, how they engage with customers, how they manage supply chain, etc. They're seeing 80% of them are seeing an uplift in revenue and profitability. The second that I think is really exciting is advancing science, a place you and I spend a host of time and probably one of the best examples of that is a colleague of mine who won the Nobel Prize for something hopefully many have already heard about, AlphaFold, which is about protein folding. And it has been described as one of the greatest contributions to drug discovery in our lifetime. What they did is they said they wanted to take on a 50-year grand challenge on protein folding, which is sort of the insight to life. And when they started on that journey, somebody challenged the head of our AI lab, Demis Hassabis, and said, 'How can you take on this challenge? It takes 4 years for a PhD student just to diagram one protein, just one, and there are 200 million out there. How is it possible?' And his answer was, 'Why not?' And they went on that journey, and within 4 years, not only had they cracked the code, but won the Nobel Prize on this. And if there's one thing I think I would want to leave anybody with that I quote a lot at Google, it's with AI, that question why not is something we should each be asking ourselves about anything that to date has been intractable because it lets you break through it. The others obviously around cybersecurity, where we both spent a lot of time. And the final area is really better delivery of healthcare, education, addressing food security. We were talking about a whole host of really important social issues that we can now address as a result of AI. That aggregate portfolio to me is the reason we should be optimistic about what AI responsibly executed can deliver for society.
I do think that people should note what Ruth began with. 4 and 1/2 trillion, even if out there in a few years, let's call it GDP here is 40. A 10-point increase, which you can reinvest back in the country and in a individual company or into the citizens, it's massive. If you go look at developmental economics, that 10 points is all the difference between breakaway and kind of not breakaway. So, while there is a lot of optimism, there's also people out there that are worried about some of the downsides of AI. One of the big ones that gets talked about all the time is, 'Hey, is this causing my energy bills to go up?' Are all the data centers the fundamental cause of this? Could you help demystify that a little bit, Ruth, because I know you guys do a lot of work on this topic and you have made a lot of investments.
Well, I like how you started with the upside because if the upside's not worth fighting for, I think we all just go back into our corner. And I think the upside is worth fighting for, and we can responsibly protect against the downside. And to your question, we can't have the upside of AI without the energy to power it. I think there are a couple of pretty critical issues. You know, when I was in New York as a banker, one of the core things we all learned is if you really want to address a risk issue, you have to go at the root cause of the risk issue. And with respect to energy, it's that our country is underinvested in energy infrastructure for far too long, and it's caught up with us. That being said, data centers are in the spotlight, and appropriately, because of the growth and the expected growth. But today, just to put some numbers around it, data centers use about 4% of the grid. Expected to go to ballpark 12%. But just to scale it. Now, what I find really important also for context, and I'll get to how we mitigate against it, Lawrence Berkeley National Labs did a study a number of years ago, and they said for states that have data centers, electricity prices actually go up more slowly than for states without data centers. Why? Because data centers and large workloads help amortize the fixed costs over larger base. So, data centers through 2024 have actually helped keep electricity prices growing at a slower rate. What we have done because of this very important question and wanting to make it clear that when we show up, it's a net benefit to the community is a couple of things. One, we're committed to adding capacity, energy capacity, wherever we invest. So, you've probably hopefully seen a lot of announcements we're investing in nuclear, batteries, solar, wind, etc., so that we're bringing additional capacity online. Second, with technology, we've done something where on really hot or cold days, we can move our workloads out of the way. It's called demand response. Across the country, we've created the equivalent of 1 gigawatt of incremental capacity by saying we'll get out of the way when the community needs it. We then say not only are we paying for the energy we use, but we'll pay for any infrastructure investment needed to support that growth whether or not we use it. And on top of that, we build an energy affordability fund in the communities we go into, which works with local organizations, and they go into homes and help weatherize homes. So, all of that leakage that would otherwise show up as an energy cost on your bill drops immediately. And then, we were just talking about this, to build this energy infrastructure is actually a job creator. There are hundreds of thousands of jobs that are unfilled and will continue to be unfilled if we're not training. So, a year and a half ago we started an electrician training program. And whenever I show up in a town and we're going to start a data center, one of the really important elements is we have the IBEW or the electrician training alliance with us. We have somebody who's talking about the jobs that are created. And I was in Missouri a couple of weeks ago, and one of the many beautiful stories, talking to a woman who's going through the training program. I'll never forget her. Her name is Danielle. And her husband had recently passed away. And she has two children. And she said, you know, being a bartender, which is what she had been doing, can't cover the costs for her kids and it doesn't provide the security. This is a secure job. It's a career. And it's enabling people to stay in their communities and have careers that they're really proud of. As you were saying, when we show up and do any kind of builds or you do, the multiplier effects in the community is profound. For every job we create, third parties have said there are nine additional jobs created in the community.
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Somebody who was, I think he still is at Google, Jeff Hinton. No longer, right?
No longer, but I still like where you're going. Yes.
He made a claim that in another 10 years, this was back in the 2015 era, we're not going to need radiologists. You know, to some extent, every time a new tech is coming, people make this claim that all these jobs are going to go away and we're not going to need anything. How do you react to that, Ruth, because I think there's more radiologists
Today, there are more radiologists. So, he made that prediction 10 years ago. There are more radiologists today and there's actually a shortage and compensation is up given the acute need. He's a fantastic computer scientist, Nobel Prize winner, fantastic computer scientist. I think what we're seeing too much of are forecasts about what might happen to the future of work that actually are not anchored in history and labor economics. And I want to go beyond what Jeff had said. In the instance of radiology, what you're seeing are a host of other factors that need to be considered in answering the question, what happens to work with AI? Demographics are such that with an aging population, there's a need for more scans. Then there's obviously demand elasticity, when you can have availability of it, more people may end up using services. So, when we look at the future of work, we'll go back to what have you seen throughout history with profound technology changes? The nature of work has changed, augmentation. There are new industries that are created that typically people don't see when they're in this kind of moment, and jobs are displaced. And I think one of the most exciting areas is actually augmentation. So, what we are seeing with radiologists is you have radiologists who are also working with AI. And I think one of the very important things, going back to your first question, not everyone across the country is privileged like the people in this room to have extraordinary doctors in New York. And in many areas, you don't have radiologists who are able to actually have the cutting-edge equipment or are at the level that we're seeing. And so, what I think is really incomprehensible, and it's something that's on all of us to address, is the disparity in outcomes in healthcare should not differ based on your zip code. Not in America. I mean, not anywhere. And if you can use technology to augment and actually supplement the radiologists, we can start addressing across America outcomes. I've had cancer a couple of times. I'm fine, but I always go back to my oncologist, and he said, 'The only way to democratize the quality of healthcare in America is with AI.' So, that augmentation is important. Actually, thinking about this lunch, I was thinking so many of I look around, I see so many old friends from finance. When I started in finance in 1987, I showed up, and it was amazing to have an IBM PC. That was like the magic of the day. And young people won't remember what that is, because you've done a great job continuing to transform IBM. But it was an island. It was a little island, and you had to have your floppy disk, and you had to manually input data. And if you fast forward to 2000, and we could download whatever you needed to download, and then you could analyze it. My job went from what I thought was magic, but was still a lot of processing, to a lot more thinking. And that's what augmentation with technology does. So, there's a whole area there. Then there's jobs that are created that we don't even see today. I've talked about some. You do see them building the infrastructure required to deliver this. Areas like computational oncology or data analytics, we don't even see today what will come. But jobs will be destroyed, and I think what's absolutely critical is to make that J curve as shallow and tight as possible with job skilling efforts, and we're doing some. I know a number I see a lot of people around the room who are engaged in it. We need to get people the skills they need to get on the curve so that they actually are benefiting from what those jobs of the future are.
We'll come back to the jobs. But your point on the PC and the nature of your job changed in that 10 to 15 year period. I think that's been the nature of our call the word tools. If instead of using the word technology, use the word tools, and as the tools do more of the rote work and the mundane work, it actually frees you up to do higher order cognitive work, which then creates a lot more value for society and for wherever you happen to work. I think we've seen this movie play out again and again.
Can I jump in there? Yeah, I absolutely agree, and two points from that. All of the analysis of what is changing, tasks are changing, but not careers. Tasks are changing, and then very much Arvind to your point, we're being able to up-level and think more rather than process, which I think is one of the exciting areas. I called our chief medical officer when I saw the breakthrough that was announced a couple of weeks ago, super exciting breakthrough in pancreatic cancer. And I said, 'Why are we not hearing more about AI on things that are landing today?' And his comment was, 'People appropriately should talk about the impact to humanity, not the tool that got you there.' And so this AI is a tool, very much to your comment, that enables us to be the best we can be. It helps us crunch more data, see things more rapidly, but I still firmly believe that it is the human in bringing people together. Humanity is a critical part of then and so what do you want to do about it?
And to the point of democratizing healthcare, here is one example in the country which you talked about, but if I go out to the developing world, the country where I was born, India, there's 900 million people still in rural India. They're in villages. It is possible maybe to have a machine that cost $10,000 out there, but there's zero chance of having a doctor or a hospital. Their only hope for getting any kind of healthcare would be through AI. Otherwise, they got to think about moving someplace for a month to go get it. So, I think this question of these tools can democratize and bring much better care than what is possible. If I think about Africa, if I think about the Middle East, these are going to be essential tools. Otherwise, you're still going to get back to spiky delivery and people have got to travel across continents.
