AI Hits Wages, USMCA Under Pressure, Colorado River Crisis

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Download the ChatGPT desktop app or contact sales to learn more. Healthcare doesn't always work great. If you've ever waited on a refill or couldn't schedule an appointment, you get it. That's the kind of stuff optimum is changing. They're using data and technology to integrate patient care, pharmacy, and everything else, so healthcare is connected, not complicated. What's that look like? Cheaper prescriptions are easier to get and care that looks at the whole person. How you need it. Optum is helping make healthcare work as one for everyone. Learn more at business.optum.com. This is Wall Street Week. I'm David Weston bringing you stories of capitalism. U.S. Canada trade talks come to the brink. Former Canadian foreign minister, Christian Freeland tells us what is at stake. And there's been a lot of speculation about what AI will mean for jobs. Apollo's Torsten Slack brings us the first study of its kind on what's actually happened since ChatGPT came on the scene. Plus, it supports $1.4 trillion of U.S. GDP and 16 million jobs, but the Colorado River is running out of water. We look at government plans to ration what's left. But we start with the hundreds of billions of dollars being raised to invest in artificial intelligence, including $500 billion in one deal done by Nvidia. Sam Palmasano served as CEO of IBM, where he was responsible for capital investment in new technologies. And the need to make sure they made money for the company. So Sam, there is a lot of money being invested in AI, whether it's chips or whether it's data centers, including the Nvidia announced deal of $500 billion. Give us a perspective of a CEO of a big tech company. How do you decide how much to invest in a new technology? How we would have thought about it, as you know, I have one of these big tech companies. We would have thought about what is the, where do we see the future state? And you go back to Watson with the 360, because that was going to be from unit record to computation called a computer, right? My particular case was AI Watson, Jeopardy, you know, right? So how do you jump ahead of the next generation? Because the investment cycles in the R&D are going to be several, several years. So you have to start no different than quantum. There's another example of that. That's true for all tech companies. I'd say it's true for many companies that are reliant upon any form of technology. It could be energy in those sorts of things as well. So we would always look out in time. And that could be from the R&D cycle, be like a seven to 10 years in the models, three to five for short term. We'd call that operational investment, but for the longer term things. And then basically you start out with goals and milestones and objectives, because you don't have numbers. And then as you get closer, you actually build your return equations as your business model dictates. So if your IRR is 15% or 14%, that would be the hurdle rate that guys would have to come over before you launched. Seven to 10 years is a long time in any business. Yes. But right now it seems like seven to 10 months in AI. It's a long time. Product cycle time. Exactly. How do you project out returns with AI that's changing so fast? Well, the software's changing fast. And the models, right? The learning models, the frontier models. That's what's changing really fast. Data centers aren't changing fast. I mean, the estimates are three to five years before this stuff comes online. That's not unrealistic. Send me conductors to get it online probably seven, nuclear at least 10. That's the energy requirement for a lot of these things. So these things are long cycle times before you actually get the capacity in place. Now, I mean, the challenge with this and the interim, obviously, is people, the large hyperscalers, the big guys out there, will probably have enough requirement that they'll, they'll in many ways, control the market. I mean, because they'll take the, they'll make the big bets in the short term. They'll get the data centers. They'll get the energy. Other guys that are trying to compete or even to participate in this market, I think, be squeezed out. We have all these announcements. Is this point actually going to be invested? Is it going to happen? Well, right now they're memorandums of understanding. People claim that there's, there's commitments and there's teeth in these agreements. I have not read them. I have asked people who theoretically should know and they tend not to comment on the actual specifics. So I'm just going to leave it at that. I, I can't imagine if this thing adjusts, say, economically. It's supposed, for example, just adoption slows. It doesn't have to be an economic downturn. Just a simple thing. Your adoption curve will, you assume, there'll be seven to eight years. Let's make it 10 to 12. That slows, you're not going to build out. The capacity is quickly that alone, you know, could cause, I think, a change in their plans. And then if they're firm commitments, it's one thing, which I doubt, as they become more variable commitments over time, someone, again, is going to have to deal with the shortages. I mean, either the bondholders, I mean, someone committed to put a shovel in the ground to build a data center. Someone agreed to add energy capacity to support this aggressive case that we see today. At some point, if things do slow, that would have to adjust. The way things are today, we tend to look at a company based on return on an investing capital. Yes. And we compare companies, depending on their return. For example, I took a look at IBM as running about 10% of the investing capital. Microsoft, you know, Google, Alphabet, is like 25%, correct. Take the 10% number. On $500 billion, that's a lot of incremental income that you have to generate every year, every year. And put that on the base of, say, IBM, did a 60 or 70 billion. I was 100 billion when I was there, I didn't five, whatever. Put on that base of some level, our margins were a little higher than they are today. But put on the base, that you already have a stream of several billion, you've got to add an additional several billion in an annual basis. And I used to say that at IBM, for us to grow at 7 or 8% just on the top line, we'd have to be create a Fortune 50 company every 14 months. Now, an enterprise computing, that's tough for commercial. Consumer and tech is probably an easier way to do that. You get a hit, hot phone, or whatever it happens to be. But if you're selling the banks or TALCOs or governments, the odds of them taking up their expenditures at that rate say you could create a Fortune 50 company. It's pretty tough to do. If you look back at history, some of which you lived at IBM, but also going back to industrial evolution railways, and look at that, are there patterns with these sort of technological revolutions that we see? Yeah, there are actually. There's a scholar, a Cambridgeer name is Carlotta Perez, and she's done a lot of work going back to 1771 for the industrial revolution. Then the steam engine, and then the oil and gas, and then microelectronics and compute. And now she would probably want her sixth generation. But the pattern's the same over time. It starts with, she calls the installation cycle, we would call maybe the industrial, I mean, infrastructure buildout today. That's the base that gets put in place, and it takes several years to do that, obviously, to get into scale. And then normally what has happened over this history here is that it has corrected for multiple reasons. It could be an economic reason. It could be policy. I mean, governments do things. It sometimes don't always stimulate growth, so there could be multiple reasons. And every situation, it adjusted. Now, her argument is that's good for capitalism because it resets the cause base. And then what happens is she calls it the deployment cycle, then people build up, and then it goes to maturity with big societal impact. That's pattern has repeated itself since the 18th century. Will it repeat itself again today? People argue it won't. I'd argue back in the.com bubble, they said it won't. There as well. I mean, housing crisis, it wasn't ever going to go down. I mean, as you know, we've all lived these things, unfortunately, circumstances do change. It's good for capitalism to reset the cause base. It's not necessarily good for investors who invest it in that. That means somebody is taking a haircut along the way. As a CEO, how do you make sure that you don't get caught out in that? Well, basically, if I'm going to go back to my IBM's story here, how we would be more conservative on the aggressive case. These, you have to admit, I think the cases are the optimistic. All thing goes well. Girls, I mean. but we used to say alt trees don't grow to heaven. So you have to have a downside case to go, we call it a plan B, quite honestly. So you'd have your plan A, you would drive to the plan A, which is the high optimistic case, but you had a plan B that if you had to correct quickly, you could adjust. And I would say probably six out of 10 times, we were adjusting before that cycle was over. 'Cause again, it's very difficult to predict. Think about if you're dealing with just flat out demand statement. I mean, who can call the, they can't call supply J in demand for a year or two from now much less eight to 10 when you're making these assumptions? In the Paris work, she also talks about a financialization of these things. The way that the financial market's really kick in now and they're really, we're seeing that to some extent now. There are some reports about off balance sheet financing. Do we have our arms around exactly how much these companies are investing? There's no transparency, as you probably know, in the off balance sheet estimates and the companies at this point in time, given where the projects are, don't have a requirement to disclose. So you have a bunch of factors there where people are being estimated, but if you're a financial analyst in this space and you're trying to figure out the true liability or the true debt that you have relative to the company's debt capacity, it's very, very difficult. As people are projecting returns, future returns, which are speculative necessarily, it's a new technology. There's another factor that appears to be coming into play and that's China, with a different approach to their models and an less expensive one, which could constrain those returns, could it not? - Yeah, well, there's an alternative today. It's called open source. I mean, we did a program together on open source that happened to be with Linux and the operating system and then applications that were built on top of that. Well, the Chinese are arguing with deep seek and those sorts of things and the latest ones that just come out, that there's no reason why they can't have this open source capability available and it doesn't require, their models don't require the same capacity as the US models, the proprietary models, either GPU capacity so they have an alternative that's less cost and that's what they're deploying. My point of view is that if I was China, not the United States, 'cause the US, you would not like this. I was China, I would just go take the rest of the world, let the US have a sanction, say you can't come in, you can't sell in my market. Fine, but that today is probably less than 20, 25% of the market so go get the 75 and if you look at what's going on in Asia, that's where they're going and they're gonna take their model which the old industrial model, they'll build up. Massive scale, low cost, high quality which people say couldn't be high quality. High quality, take it to market and then we know what happened everywhere else and they're running the same play here. - Coming up, it's time to stop speculating, start looking at the data. Torston Slack of Apollo takes us through his study of what the actual use of AI means for the workforce. - Wall Street Week is brought to you by OTC Markets Group. Thinking about joining the exploding overnight market space but unsure where to start, designed to meet the needs of a growing international investor base. 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There are now EV chargers at about 326 of its US stores, including adding this year four high-speed charging stations in Betenville, Arkansas, even though the state has been a laggard in transitioning to electric vehicles. Walmart has hosted chargers from other companies since 2018. The big difference now? Walmart is building its own network and quickly. As of March of last year, every EV station at a Walmart is under the company brand. Now Walmart is still a blip on the US charging map. And yet, it was second only to Tesla among charging networks expanding in the second quarter. That's the Bloomberg Tech Minute brought to you by ChatGPT. Put ChatGPT to work on your most ambitious ideas and projects. Get started at chatgpt.com today by selecting Work Mode, available on plus and pro plans. - No data, no AI. It's just that simple. Until now, the data your AI depends on has been trapped behind ever-increasing cloud fees. 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[MUSIC PLAYING] This is a story of puts and takes. Until recently, most of the talk about the effective AI on employees has been based on theory. But now we are starting to get some data. Torsten Slocke is chief economist for Apollo. And recently co-author to paper, analyzing those data for hundreds of occupations. And though it is early going, the initial results indicate that those most affected feel it in the size of their paycheck, rather than whether they get to keep their job. It is now possible to look at what happened before chat TVT came along and what happened after chat TVT came along. And what we did was that we categorized the employment and weights numbers into occupations and asked what occupations were exposed a lot to AI. And what occupations are exposed less to AI. And then we looked at as a natural experiment, what happened before chat TVT came along and what happened after chat TVT came along. So when you look at the 300 different occupations that we looked at in terms of AI exposure, the conclusion is, at least when we sit right now, that those occupations that are highly exposed to AI, they are seeing weaker weights growth, but the employment effect on everyone is insignificant. What surprised you about the results that you might not have expected going in? Well, the debate around AI in the labor market for now some time has been about labor displacement. In other words, there's a lot of worries about that when AI comes along, then workers are going to get automated and therefore a lot of workers are going to lose their jobs. What we found was that that effect is not quite here yet. Instead, let's also not forget that when AI, of course, becomes more easily available as a tool, now it's also easier to open a new business. So if you look at the weekly data from the census for business formation, you are at the moment seeing business creation in the US is at the highest level ever in US history. So on this scale, you have on the one hand an automation and replacement effect that's certainly saying that the labor market should get worse. But on the other hand, so far the dominating effect has been that there is also a much more dynamic economy where people can now invent ideas, use agents, use loops, graphs to come up with ideas and as a result, create more businesses that ultimately likely will also create some more employment. In talking about the labor market getting worse, as I understand your study, it's said, it gets worse more on the wage growth than it does actually in people losing jobs, but it's not evenly distributed. Yeah, there are some occupations that are more negatively impacted. We chose, and this was somewhat randomly to categorize the buckets of occupations into those occupations that are more than half exposed to AI and those that are less than half exposed to AI. In other words, try to cut the sample into different categories of who is it? That is high exposure, who is it that has low exposure? Again, by this, actually uses data. And that does show you that those who have higher exposure generally saw lower wage growth. So in other words, you can begin to worry about that maybe AI, because it is replacing knowledge workers, is going to create some downward pressure on wage growth and so far not on employment, but it's going to create some downward pressure on wage growth. You say in your report that it's still early days that the effects may grow over time. Do you have any sense where we are in that process and how those effects may grow? We don't quite know at this point, because the market is trying to figure out the answers of that question literally every day, namely, how quick is the AI payoff going to come? At the moment, enterprises are investing a lot of money in AI. But when you look at the actual margins for the S&P 493, meaning not the magnificent seven, margins have not gone up yet. Most people, including me, expect that we should begin to see some improvements in margins over the next several quarters, but at this point, it is still very early days where businesses are trying like an S curve that you figure out will not. Now we have a new technology, now we're trying to figure out how to use that technology. And once we then have a way to use that technology, we would like to see another step higher in this. And the implication, of course, is that those industries that will be able to implement and adopt AI will, of course, be the next winners as this technology continues to develop. Based on what you've seen so far, including this study, what does it say for economic policy? What should people in Washington be focused on right now? Well, the challenge in policy making at the moment is that we just don't know which scenario we're looking at. Let's say the unemployment rate goes to like 10-15 percent because people lose their jobs. Then, of course, economic policy should be focusing on that problem. If on the other hand, that dominating effect here becomes that business creation is creating so many more jobs, and therefore, the unemployment rate, which is the consensus expectation, would actually be going down. Well, in that case, policy making does not need to worry about displacement of workers. Then they should, instead, maybe worry about the economy overheating. And another set of economic tools from policy making will be needed. So that's why the problem will be set right now here in 2026 is we just don't know whether the scenario at this point is one where the labor market is going to get a lot weaker, or it's going to get a lot hotter. And for that reason, therefore, the best thing for policy makers at this point is just literally like the market to wait and see. Are you as optimistic with AI at the end of this study as you were at the beginning? I'm very optimistic about AI because I do think that the effect of creating a more dynamic economy, many more opening up new businesses in consulting, in finance, in legal services, and those new businesses will compete with the incumbents. And that will continue to put more and more competitive pressure on the economy. And that's something that we should all be very interested in because that creates more jobs, that creates more businesses. And ultimately, as a result of that, I truly believe that AI is a miracle drug that will both create higher productivity and also create higher employment. So I'm very optimistic on what AI will bring to the U.S. and the global economy. Whether AI eventually spells riches or ruin for workers, the numbers so far tell only part of the story. Inside companies, executives are already deciding which jobs can be automated, which workers can be retrained, and how best to allocate labor costs. Diane Gerson is a senior advisor at Boston Consulting Group, and she confronted those choices when she was head of human resources at IBM. For certain jobs where there's high attrition, those are the jobs that are being automated the first with AI. Those jobs are being replaced at a lower rate. The demand for those jobs is lower, and it's your classic demand supply. So people are taking jobs at lower rates in those job categories, customer service being an example or business services. Those are the types of jobs where you need fewer of them because the work can be done by fewer people, faster. So to the extent that they are being hired, yes, they may be hired at a lower rate, but I don't see companies cutting pay. The only area that I would see this happening is in areas where you have contractors, right? So what you're seeing is there's a lot of data available. There are data brokers that can tell hospitals that are hiring traveling nurses, which of the traveling nurses have low credit scores or credit problems. And so they can offer a lower wage and know they'll get it. Or ride hailing services if there's a driver who previously took a ride at a lower rate, they'll keep being offered that lower rate. So I think those are spot wages as opposed to employees, and you're going to see that happening faster. When you talk about categories that have, for example, high attrition, things like customer service in general, and I understand this is a rough correlation, does that tend to correlate with lower income? Lower salary? Yes. Oh, absolutely. Yeah. So it's plausible that AI would affect first the lower paid employees before it gets the upper levels. You know, I mean, yes, I mean, let's take legal, so it's the paralegals that are going to go first, right? Because so much of the paralegal work can now be done by, you know, one of the AI firms is Harvey or whatever, and so to the extent that a lot of firms says, oh, but we want these paralegals to be overseeing the AI, you know, then their jobs will change somewhat. Or we'd like to train them to become, you know, some junior level of lawyer that we've never been ever existing before, because that kind of work, you know, we never really could accomplish with our junior lawyers. So there's, you know, there's a variety of different things going on, but yes, it's starting at the bottom with the more repetitive task, the analytical tasks, the known models. And you know, of course, the big question is as it moves up the stack and it's already moving up the stack, particularly in tech, you know, how are you going to train the senior people? Because if it's gobbling up the jobs below, the pipeline is lost. And so I'm seeing a lot of really thoughtful work being given to that by companies, because they want to preserve their judgment capability, they want to preserve their leadership capability, and their highest levels of expertise. And so you've got to develop them through some set of jobs. The projections right now, and you need them to justify the investments that's being made, is this AI is going to increase productivity substantially. If that in fact delivers on the promise, what does that mean for the workforce? Some companies are thinking broadly and saying, you know, productivity actually isn't going to increase our valuation that much. I mean, just doing things faster and cheaper doesn't mean you're going to, you know, have the highest valuations, but if we can create new products, if we can create new opportunities, if we can do breakthrough innovation, then, you know, then we'll have a higher valuation because we'll have growth, right? So I think those companies are saying, what can we now do with AI that's going to elevate our capability as opposed to just making it more productive and faster? A motivated workforce is essential and was part of your central responsibility at IBM. As you look at AI, assuming you had your old job back, how would you use this to motivate the workforce? Because it could cut either way. It could demoralize people, really change the culture in a negative way. Or I guess conceitably could motivate people, how would you use it? Well, I think some companies have done this really well and I'll call out Walmart, you know, they spoke with all of their employees and they said, AI is for you. You are in charge of the AI, it's to make your job better. And you're going to be involved in every stage of this implementation of AI. And so instead of it being done to them, they were made to feel like they're empowered with AI, right? And I think that's where, when people feel like they're losing their agency and they're control and they're just going to be, you know, I'm thinking about sort of, I love Lucy when they're on that chocolate line with Ethel and it's going really, really fast. But at that very end, they have to put it in boxes and of course humans can't put it in boxes as fast as the machine was going, so chocolates were all over. That's sort of the image that a lot of people have of AI, because it is machine-paced. And it's going to speed stuff up, is that what we're going to do to professional work? And that is happening in some places. But I think some companies are being much more thoughtful in saying, no, actually it's to make you a better professional, it's to augment what you do. And that's where we're going to get our productivity because you'll be able to spend time on different things. A great example is, you know, the radiologists, which everyone thought was going to go away. Actually their wages have gone up faster, 42% faster than software engineers since 2021. Even though AI can read the images, why? Because they have more time to talk to the patient, to learn more about what's happening, to interpret things that from their knowledge and experience, so, you know, so people can operate at the top of their license instead of doing the more menial parts of their jobs. That's a win. If, indeed, you can create more value. So you're seeing kind of bigger thinking going on in some companies, but some of them are just as I said, pressing the easy button and going for the, you know, going for the layoff. Up next, going to the brink with Canada over trade, our special contributor, Christchia Freeland, takes us through where we are and what's at stake for the two countries. This is the Bloomberg Tech Minute brought to you by Chachy PT, now with Chachy PT work. I'm Carol Masser. There are now EV chargers at about 326 of its U.S. stores, including adding this year four high-speed charging stations in Betenville, Arkansas, even though the state has been a laggard in transitioning to electric vehicles. The big difference now, Walmart is building its own network and quickly. Now Walmart is still a blip on the U.S. charging map, and yet it was second only to Tesla among charging networks expanding in the second quarter. That's the Bloomberg Tech Minute brought to you by Chachy PT. Put Chachy PT to work on your most ambitious ideas and projects. Get started at chachypt.com today by selecting Work Mode, available on plus and pro plans. No data, no AI, it's just that simple. Until now, the data your AI depends on has been trapped behind ever increasing cloud fees. Your data is free to move, fast to access, and ready when your AI needs it, giving your business a competitive advantage. Wasabi's flat pricing eliminates all of it, one rate, no surprises. Companies that are paying more in fees than in actual storage costs can fall behind. Don't let it happen. When your AI needs your data and you have a budget to meet, get Wasabi. Learn more. Wasabi, V.A.I. Storage Cloud, proud partner of the I Heart Podcast Network. Every sale comes down to a single second, the one between by now, and maybe later. PayPal is built to help your business win that moment, with a checkout experience that feels certain, reliable, and familiar. With a global two-sided network, and hundreds of millions of buyers, who already know us, all to keep you in control, however buying happens next. New markets, new AI-powered selling surfaces, a whole new agentic era where you decide how your business will show up and stand up. PayPal is built to help your business come out ahead. You're built for payments, built for growth, built for agentic, PayPal open, built for all business, visit PayPalOpen.com to get started. That's PayPalOpen.com. You're listening to Bloomberg Wall Street Week with David Weston from Bloomberg Radio. This is a story about couples therapy. The U.S. and Canada have been neighbors, allies, and generally friends since Canada first became a country independent of the British Empire, but President Trump has put the relationship in play, particularly when it comes to trade relations. Christchurch Freeland served as Canada's deputy prime minister, foreign minister, and finance minister. She is now a special contributor to Wall Street Week. Having gone to the brink during this week, when U.S.-Canada trade relations were told that there is a tentative agreement, what at this point do we know about that agreement? What we know so far is it seems as if the U.S. and Canada have reached an agreement that will prevent the tariffs that the U.S. announced, the brand new ones, the smootholy ones from coming into force against Canada. These tariffs were meant to be applied on the 19th of August, and on the basis of this almost concluded deal, they haven't come into force. What does it do to the tariffs that haven't existing? For example, you and I have talked before about aluminum and steel. What happens to those separate tariffs? So we don't know the full outlines of this agreement, but what people are saying both publicly and people close to the negotiations is that what Canada is agreeing to, or it is on the brink of agreeing to, is that U.S. booze will go back on the shelves of Canadian liquor stores. Some Canadian provinces had also put in express either by Canadian or don't by American provisions into procurement, that those will be lifted as well. When the two, three, two tariffs against Canada, the ones on steel, aluminum cars, when those first went into effect, Canada imposed retaliation. Most of that has already been dropped, and on the other side, the August 19th, smootholy tariffs seem likely not to go into effect, and then on the two, three, two tariffs, which are steel, aluminum, cars, and car parts, it seems as if those will remain in place, but at lower levels, and that's really a very critical element of this agreement, because up until now, Canada's position, and this has been Canada's historic position, is we have a free trade deal with the United States. Permanent tariffs outside that deal are unjustified and illegal, and we will not accept them. In this deal, Canada apparently will have lower tariffs on steel, aluminum, cars, and car parts, but tariffs will be in place and Canada will accept the legitimacy of those tariffs. That's a real rubicon that it looks like will be crossed. That feels like a pretty major give from Canada, understanding the tariffs will be lower, but considering there will be tariffs, despite a free trade agreement. I mean, you've negotiated on Canada's behalf in prior trade agreements, is that something we can ever be pulled back for Canada, or is that more or less a permanent give? David, I think that is the smartest and most important question about this entire agreement. The future obviously is unknowable, but the idea that tariffs on these sectors would be accepted by Canada, that is a really big deal. Something that I think is really important to point out here is, I think that is a bad outcome for Canada to have permanent tariffs on our steel, aluminum, cars, and car parts, really harmful for those sectors, but I think it's a bad outcome for the United States as well. It's really important for people to recognize that you can lose by winning if you've defined winning in a way which is self mutilating. I would say Brexit, the British decision to leave the EU is a great historic example of losing by winning. In this case, I think it's really important for Americans to understand that putting permanent tariffs on Canadian steel and on Canadian aluminum hurts US manufacturing. These are inputs into the US manufacturing sector and you are choosing to make your own manufacturers weaker. The tariffs that were imposed in 2018, there have been a lot of academic studies on the impact, and the net impact was harming US manufacturing. Freedom tariffs, particularly self harming, because aluminum is basically electricity in solid form, so the US is basically imposing attacks on electricity. David, you are from Michigan originally, and so you know that Canada and the United States build cars together. We've done it for a century, for more than a century, and imposing permanent tariffs on cars and car parts is really going to hurt Detroit. I think Canadians are real patriots, and Canadians want to support our Prime Minister in this really challenging time, but I think you are going to hear Canadian unions who represent workers in the car sector in steel and aluminum, quite concerned. We mentioned the auto industry, which is central, particularly in US, Canadian trade relations. As you know so well, there are auto parts that go back and forth between Windsor and Detroit all the time, several times in the making of a single vehicle. As far as we know with this tentative agreement, is the effect to just increase the price because there are some tariffs, or could it actually impede some of the flow back and forth? Another great question, David, and you are right. We really do build cars together, and the parts in a finished car can go across the border seven or eight times before that car is completed. The tariffs on cars and car parts are currently in place, and it looks as if this agreement will lower them, so it will be a better situation compared to what we have before the agreement. It will be worse though than the USMCA, where there were no tariffs. I think the concern for anyone in the car sector will be, are we moving to a situation of permanent tariffs on cars and car parts? Something to watch in the details of the agreement is whether car parts and car parts that are made in NAFTA are excluded from the tariffs in the NAFTA zone, or whether only car parts made in the U.S. are excellent. excluded from the tariffs. That's a really important distinction. When we were negotiating the USMCA, there was a moment when Bob Lighthizer wanted to include a provision that would require that a certain percentage of a car be manufactured in the US. Canada and I personally were really, really opposed to that because then you don't have a free trade deal. You have managed trade and that's an entirely different principle, ultimately it's an entirely different way of running your economy. But what Bob was worried about was protecting workers' wages, which was something I did support. So what we agreed and what is in the current USMCA is something called the labor value content provision, which requires that a certain percentage of a car be made by workers earning above $16 an hour. I thought that was a great compromise. Protects good paying jobs, but doesn't introduce that element of protectionism. It will be really important to look in the details of a final agreement between the US and Canada to see if it's specifically US-made parts that are excluded from the tariffs or whether it is NAFTA compliant parts. You mentioned the USMCA, which you know well having negotiated it. As far as we can tell, as I say, a tentative agreement, how does it fit with USMCA? Is it an amendment to it? Does it supersede it? Is it subservient to it? How does it fit? Seems like it's completely separate. Seems like this is like so many of the deals that Trump administration has been doing around the world. This is a one-off. It is about the US creating a wound, creating a problem for its partner, and then entering into a negotiation with its partner to have the problem limited. So it's not connected with the USMCA and with the negotiations that have been triggered around the USMCA. And that is a challenge because there's going to be a big question about whether some of the key issues that have been agreed in this deal automatically carry over to the USMCA negotiation. You know so well from your Canadian background that the United States Trade Policy in recent years has, shall I say, bruised some feelings north of our border. Will this tentative agreement, if it goes forward, help deal with some of those bruises? I don't think so. I think that Canadians are going to feel that we were being unfairly targeted. We were being unfairly treated. And now we're going to be subject to a little bit less abuse in exchange for not complaining about it. And each person, each worker, each business will judge whether that's a good outcome from the Canadian perspective. But I think the unanimous national view is going to be, we're being treated pretty shoddly. Coming up, saving the southwestern US from drying up, we look at the rationing plan developed by the US government to save the Colorado River, which is responsible for supporting $1.4 trillion of the US economy. [MUSIC PLAYING] This is the Bloomberg Tech Minute brought to you by ChatGPT, now with ChatGPT work. I'm Carol Maser. No data? No AI. One rate? No surprises. Don't let it happen. Learn more. Wasabi, V-A-I storage cloud. Every sale comes down to a single second. The one between by now and maybe later. PayPal is built to help your business win that moment. With a checkout experience that feels certain, reliable, and familiar. With a global two-sided network and hundreds of millions of buyers who already know us. All to keep you in control, however buying happens next. New markets, new AI-powered selling services. A whole new agentic era where you decide how your business will show up and stand up. We're built for payments, built for growth, built for agentic. PayPal open, built for all business. Visit PayPalOpen.com to get started. This is a story about triage. The American Southwest, as we know it, was built on cheap, reliable water from the Colorado River. But for decades, the river has been shrinking. And this year, the fight over what's still left has come to a head. It's forcing a showdown over who cuts, who pays, and what life in the West costs when water is no longer a given. Bloomberg's Michael McKee has the story. We know the situation on the river. It's the worst it's ever been. Without water, there's no imperial value. We are indeed getting to be in a crisis situation. This has been a very difficult year. This is the Colorado River. At over 1,400 miles long, it provides water to seven states across the Southwest. Starting in the Rocky Mountains, the river begins as snow, which melts and provides water to the upper basin, made up of Wyoming, Colorado, Utah, and New Mexico, and the lower basin, which includes California, Nevada, and Arizona. The water makes its way to kitchen sinks and front lawns, but also crops and businesses and reservoirs, which generate power for the cities in the Western US. The Lake Powell is very close to what they call the power pool. And that means that monster reservoir is below that level. It can't push the water through the turbines to create power. That's going to affect power supply. Jennifer Gimbal is a water policy scholar and former Bureau of Reclamation official. She says the river's legal framework was built in layers, beginning with a compact in 1922, but a lot has changed since then. We have no safety net now. When all those other agreements were signed, there was still a decent amount of waters in the reservoir. But no longer. This winter, the Rocky Mountain saw the lowest snowpack ever recorded, and less snow means less water downstream. Dan McAvoy is a climatologist at the Western Regional Climate Center, where he has been tracking snowpack levels across the West. Why is snowpack so important? Yeah, it's critical to pretty much all of the Western United States in terms of water supply, of course. So for many regions around the West, anywhere from 50 to more than 70 percent of the surface water that's used for public consumption, agriculture, irrigation, all the surface water supply. Most of that comes from the snowpack that accumulates in the winter season, and then historically has slowly melted through the spring and summer. But that is changing, and we saw a big shift in how that occurred. heard this year. This is a widespread event where we've seen some of the lowest snowpack on record going back 50 to 75 years or even longer. And so that's something that kind of developed throughout the course of the year. And then we had this really unusual mark sheet wave. And that triggered this really abrupt and really early snow melt leading to this really catastrophic situation in terms of snowpack as a whole across the Western US. And conditions are probably the worst in the Colorado River basin right now. That lack of snowpack is now showing up in the system's balance sheet, Lake Mead, which hit its lowest level since it was filled 90 years ago. And Lake Powell are the two biggest reservoirs in the country. Both of their water levels have been declining for decades. This year, some of the rules governing the river are expiring. And with the seven states unable to reach a long-term agreement, the federal government is stepping in to divide the waters. So now we're down to the nitty gritty who gets it and who doesn't. And you have governors, representatives, and they're concerned about their constituents, they're concerned about the economy, they're concerned about food security, but there's only so much in a river. And as they just couldn't come to an agreement. In a lower basin, the reclamation is called the water master. They control the contracts. In the upper basin, don't have a large federal reservoir. So we don't have a way to call for that water and have it delivered. It's just a natural process. So each state is in control of its natural resources. The Bureau of Reclamation recently released plan covers the next two years, suggesting a one and a half million acre-foot water usage cut annually for the lower basin, with Arizona getting hit the hardest. We think there are fundamental flaws with the final environmental impact statement, the FEIS. We believe it's not following the law. It has significant problems. With the United States just put on the table, simply isn't workable for Arizona. As the General Manager for the Central Arizona Project, Brenda Berman oversees allocation of the Colorado River Water to nearly 80 percent of the state's population. The lower basin states, so Arizona, California, Nevada, what we've done is we've put forward a plan. And we did that before that document came out. And that plan is to create two years of stability on the river. These reductions that we're talking about, 760,000 acre-feet for Arizona, is something that our communities have been preparing for. It's not something we think we can do every year, but it's something that we are prepared for in 27 and 28. You can't balance the entire smaller river on the shoulders. We there are CAPs, customers, or an Arizona, California, and Nevada. This is something that has to be shared by all seven states who share the river. How do you negotiate something like this? Everybody is in a corner because because they're just isn't enough river water. Farmers in California are probably feeling like, well, we got it better because we're what they call senior rights to Arizona. But California is still going to have to take some cuts also. Looking at the upper basin, we've been taking cuts every year during this drought. That old legal order is not abstract. The Colorado River supports $1.4 trillion of economic activity every year, and jobs for 16 million Americans. I sell this crop by the ton by the pound. One of those Americans is Andrew Lyme Gruber, whose farm in California's Imperial Valley has been run by his family for generations. We are the big target on the river because we are such a large user of water, but we're also the highest in priority. The way it works in the West, the first person to use the water beneficially, first in line, we have a system of laws in place that would have dealt with this crisis before it got to this point. Unfortunately, you know, Arizona has only been pulling water off the Colorado River since the late 1980s. The CAP was only approved by Congress with Arizona agreeing that in times of shortage they would be the first to be reduced and cut off. For the last two decades, Arizona's been taking their full entitlement even though they didn't have the need for that water. We have strong standing water rights that have gone all the way to the Supreme Court. They've been adjudicated, they've been passed in process. We have the law to stand on. If they can come in and take that away, that means there's no such thing as a property right in the United States. The impact reaches far beyond the Southwest. In the winter, much of the food that feeds American families across the country comes from desert farming regions like the Imperial Valley. Most of the population thinks that the food that they buy at the grocery store shows up in the back. They don't know that it comes from a source, that it's produced. A lot of hands in labor and blood, sweat and tears goes into producing all the bounty that we share in. Are you able to use less water? There are areas where there is efficiency that can be gained. It just costs money. Utilizing systems like drip, overhead sprinkler systems, automated flood systems, tell water return systems. All these different uses of technology but they're very expensive and costly. Unfortunately, the least expensive way to get water off of farms has been following. And following around here we call it the F-word. It's extremely detrimental to our communities. Following puts people out of work. This was not a cheap installation I would imagine. No, this half-mile system that irrigates 180 acres was a half-million dollar capital expenditure. To be sustainable we also have to be economical and profitable as a business. The benefit though is with this system I can produce more crop. If the Imperial Valley shows the cost of cutting use, San Diego shows the cost of cutting new supply. With an abundance of water at its disposal from desalinization, the county's water authority plans to help ease pressure on Arizona and Nevada for a price. How does this agreement with the other states work? First, we have to get all of the lawyers in the room and we have to get them to agree. We're looking to do things that have never been done before. As the general manager of San Diego County's water authority, Dan Denham is overseeing the effort of turning water into a financial exchange. So you'll send water to the states in exchange for them using less water from the Colorado. We're going to exchange money for water and that's the basic construct behind it. It's the construct behind what we've done with the farming community in the Imperial Valley. It's allowed the Imperial Valley to make investments on farm efficiency projects while maintaining their high priority rights to water. We receive the water that as I suggested would otherwise have been cut by 50%. So similarly, Arizona and Nevada get water and for the water authority we get inventory off of our books. Inventory off the books in the form of water means more flattening of rates out into the future. We can dampen the rate increases that have been really, really tough for us over the past three years. Does it mean that those states will not have to cut back as much? Yes. Desalination can create a new supply, but it can't put water back in the Colorado River. It shows what scarcity pricing looks like when the cheap supply is no longer enough. This water at the diesel plant, the most expensive, costs $3,500 a unit. Some of the other sources that we have are $50 a unit. Some are $800 a unit. Some are $600 a unit. Altogether, it's $1,400 a unit. And that's what makes this more affordable if it's just the only option you have. Desalination is expensive, but quite honestly, we have not paid what our water is worth to us. And so we need to make that adjustment in our minds. The next chapter of the Colorado River economy will be built around pricing scarcity, not abundance. It's clear that the basin region needs more than a temporary fix. States and the federal government need to work together to build a new operating system. It all comes down to dollars and cents in economics. Hydrology is not going to wait for us if there is a bad year next year on the river. The system will crash. We have a responsibility to our national economy. We have put massive amounts of water out there. It is time for everyone who benefits this river to step up. Next, Sam Paulisano on the Need for AI Regulation at the right time. This is the Bloomberg Tech Minute brought to you by Chachy PT. Now with Chachy PT work, I'm Carol Masser. Walmart has hosted chargers from other companies. since 2018. No data? No AI. One rate? No surprises. Don't let it happen. Learn more. Proud Partner of the iHeart Podcast Network. New markets. New AI-powered selling surfaces. We're built for payments. Built for growth. Built for agentic. PayPal Open. Built for all business. Artificial intelligence is on its way to transforming the economy. But it isn't the first time in history when a new technology from railroads to electricity to telecom has changed the way we live. And the way we do business. Sam Pomosana ran IBM during the digital revolution. And he's seen when government regulation works and when it doesn't. Well, my point of view is that fundamentally the government, if it needs to facilitate the opportunities of the new technology, not try to control the opportunities of the new technology. Within guard rails, I would argue that fundamentally what worked really, really well, go back to the internet was the private sector given encouragement by the government, but also establishing standards that you take for granted, like connectivity, data sharing, data structure, all those things that are kind of garpy. I know they haven't exactly for your consumer audience, but that's where government comes into play. They established those standards. They had parties that let the private sector invest and where it was especially important, like say DARPA, but like national security and defense, yes, there'd be more involvement. But for the commercial world, and we were in all of it, right, they would let that market mature. And you saw that happen in the internet. And it was incredibly successful. And there are a lot of debates along the way, as you know, opt-in, opt-out, all those sorts of things occurred. But fundamentally, they let innovation go. Now people argue today what went too far because of the social media guys got a huge dominant here in certain things called advertising would have you. But fundamentally, any trust that existed today does not address that concern because remember it was free. This is the flawed and the logic of the any trust cases because you're not damaging the consumer. The European models are different as you might recall, but for the US model, there's no, it's free. So there's no consumer damage. As we talk about standards or regulation for AI, and again, put aside national security, special case, what we are hearing from a good part of the private sector is don't do anything because it'll stifle innovation. You'll slow us down and we're in a race. How do you assess that if you're the government? At what point does it stifle innovation? What point? Well, that's the industry. That's not the user. You know, people forget who it is. I mean, the people in all the meetings or the guys don't want to be regulated themselves. It's not the people who are like a bank or a health care or energy or in construction. It's not the other industries of our economy, which are much bigger than the tech industry. Yes, we all know, right? But fundamentally, so that's the case that they make. I would argue that if the regulation that takes cyber security where I was on the commission with, you know, for President Obama, you might recall, I mean, our point of view when they say we're going to slow down innovation, I said, no, you only slow down innovation when you didn't design for it to be secure. If you designed upfront for it to be secure, you don't slow it down. So why don't you accept the fact that you can design for a more secure internet, which we still don't have today. And then, therefore, you're not slowing down innovation because everybody's competing for those standards. You need guard, I say guard rails. I don't know that you need heavy regulation, but you need the appropriate, their associations, their standards bodies. All these things already exist. You need their influence, I think, over how to do this properly and securely. It'll still be a huge market. This is the thing. It'll be a huge market. It's not going to all of a sudden, it maybe goes from five trillion to four point two trillion, whatever, you know, it's not going to be tremendous opportunity. But I think people should step back and have a perspective that what they should do is in the long term, let's write for their customers, let's write for their society, and then you can argue it's right for the shareholder. Do we have the expertise that we need in the government to make these judgments? I mean, going back to the railroads, we had the International Interstate Commerce Commission. Correct. It was after that. In broadcasting, you had the FCC, there were experts, you had people who knew this stuff. Do we have people within our government who have their expertise? My observation at this point, at least in this field that we're talking about, I think the government is well way behind the private sector. Not true in the past. You know, there really were smart people when I was working in government. I mean, we might not agree, but that's a whole different point of view versus they weren't really smart. And I say that you have to buy for Kate government because if you get into where I spent a lot of time like national intelligence and defense, they got some really smart people. But you get to the commercial side of government. I would not say they were honorable students when they got out of school. So if you had your way, you could decide anything. Would you create a new agency specifically on the AI subject? Now, what I would do at first, there's too much bureaucracy already and just adding more bureaucracy. And then they'll fight about who has control, who gets the money, and that's saw that in cyber. So we've lived that one recently. I think what you would really do, I would, if possible, I get some volunteers. I think they come something like subject, governmental subject experts or something like that. You know, get some volunteers. Really smart people who've been around this thing, who have industry knowledge, who know technology, who could come back with a strategy for the United States of America. And obviously there'll be debate, there'll be adoption. I got all that, right. But some very thoughtful group of people that are respected can do that. I'd make the same recommendation for some of the agencies that exist within our government that need to have a different point of view than they have today. That would be, I believe, the most beneficial way to start. Then you can decide where it resides. If I go back to cyber as my analogy, I mean, everybody wanted to be participants in that because they saw money coming, whether it was OMB or it was people not. I mean, NSA, CIA, DOD had the expertise but they didn't have any interest. Everybody else in the commercial side of government, right. I was coming after the money. They saw the money coming and I asked them this question. I said, can you show me the people you would use to stay up to projects? It's just a resume. I can read a resume. I know technology. Can you show me that? And the response was, you know, we don't have those people. And I'm, my response was, so I'm going to recommend to the president of the United States where you don't have any expertise in talent. They they fund you. They go, yeah, I should know. That's a true story, by the way, in the executive offices across the street from the White House. As we sit here today, how concerned are you about safety with AI? There are a lot of reports now about breaking out of sandboxes and AI sort of going off on its own and doing things has been told not to do. Is that a big concern for you? And if it's not addressed, yes, because it's only going to compound and get worse, right. I mean, remember, as we say that, I mean, maybe it's accidental today when the agents get out of control of those sorts of things and they're causing these issues as far as security and the concerns that we have today. But the point of it is, that it's moving so fast and the technology is so fast, if something's not done to address it, it could be out of control in like minutes, seconds, in those sorts of things. So I think it needs to be addressed. And it can be addressed. It's back to this, how you put these guardrails in place, you know, the red, the regular, the testing before you deploy. And it's all sorts of things that could be put in place. Now, of course, yes, what? It takes time and it costs money, you know, right? But the companies that are right now at least, one of them has earnings and the evaluation is off the charts, right? All the others have evaluations that are off the charts without money. So there's a lot of money out there if I would argue if they would be encouraged to deploy it in a way that's sustainable for the long term. I mean, there's debates that they have to meet with certain agencies of government where you're putting the country at risk are nonsense. Only people that would make that argument are immature in young. My generation would never have made that argument that you should put society at risk. But IBM was doing all that stuff. I mean, it would be totally responsible. We wouldn't even think about it or dream it, you know, now it's fun, you know, right? No, no, you guys don't get it. Let it rock and roll. I just think that in today's environment, the technology is such, I mean, it's only going to get faster. It's going to be light speed. Who can control? Human beings can't control light speed. And that's where it's going to go. That's where it's headed. And so therefore, at that level of speed, you're going to have to have those controls built into the systems to self-police them. That does it for us here at Wall Street Week. I'm David Weston. See you next week for more stories of capitalism. That's the kind of stuff Optum is changing. They're using data and technology to integrate patient care, pharmacy, and everything else. So healthcare is connected, not complicated. Cheaper prescriptions that are easier to get and care that looks at the whole person, how you need it. Some people use chatGPT to answer questions. Others use it to get real work done. With chatGPT work, you bring the goal plus real inputs like briefs, notes, files, feedback, data, and project plans. It can help turn them into an analysis, tracker, deck outline, prototype, or workflow you can review and keep shaping. You stay in control, giving direction and choosing the final output. Get started at chatGPT.com by selecting work mode, available on plus and pro plans. There are exciting things happening at your local CVS. Shop new extra big deals with extra care every two weeks. No coupon needed, plus get access to exclusive sale prices, personalized deals, and more as a member. Extra care is the way to save its CVS. Join for free online or in-store and start saving. Visit your local CVS store or CVS.com/extrabigdeals for this week's deals.