{"id":231222,"date":"2025-09-25T13:40:06","date_gmt":"2025-09-25T17:40:06","guid":{"rendered":"https:\/\/ibkrcampus.com\/campus\/?p=231222"},"modified":"2025-09-25T13:56:27","modified_gmt":"2025-09-25T17:56:27","slug":"is-ai-about-to-blow-a-fuse","status":"publish","type":"post","link":"https:\/\/www.interactivebrokers.com\/campus\/podcasts\/ibkr-podcasts\/is-ai-about-to-blow-a-fuse\/","title":{"rendered":"Is AI About to Blow a Fuse?"},"content":{"rendered":"\n<p class=\"wp-block-paragraph\">AI\u2019s explosive growth comes with a hidden cost: staggering capital expenditures, soaring energy demands, and concentrated data center risks. Economist Michael Normyle joins Jeff Praissman to break down whether artificial intelligence is powering progress \u2014 or overloading the system.<\/p>\n\n\n\n<iframe title=\"Is AI About to Blow a Fuse?\" allowtransparency=\"true\" height=\"150\" width=\"100%\" style=\"border: none; min-width: min(100%, 430px);height:150px;\" scrolling=\"no\" data-name=\"pb-iframe-player\" src=\"https:\/\/www.podbean.com\/player-v2\/?i=q5knb-1976216-pb&#038;from=pb6admin&#038;share=1&#038;download=1&#038;rtl=0&#038;fonts=Arial&#038;skin=1b1b1b&#038;font-color=ffffff&#038;logo_link=episode_page&#038;btn-skin=c73a3a\" loading=\"lazy\"><\/iframe>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"h-summary-ibkr-podcasts-ep-298\">Summary \u2013 IBKR Podcasts Ep. 298<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\"><em>The following is a summary of a live audio recording and may contain errors in spelling or grammar. Although IBKR has edited for clarity no material changes have been made<\/em>.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-jeff-praissman-nbsp\"><strong>Jeff Praissman<\/strong>&nbsp;<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">Hi everyone. This is Jeff Praissman with the Interactive Brokers Podcast. It&#8217;s my pleasure to welcome back, for our monthly podcast on the economy, NASDAQ\u2019s U.S. economist, Michael Normyle. Hey Michael, how are you?&nbsp;<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-michael-normyle-nbsp\"><strong>Michael Normyle<\/strong>&nbsp;<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">Doing well, thanks. Glad to be back.&nbsp;<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-jeff-praissman-nbsp-0\"><strong>Jeff Praissman<\/strong>&nbsp;<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">Oh, it&#8217;s always great to have you in the studio. And today we&#8217;re going to talk about something that&#8217;s really hot on everyone&#8217;s mind.\u00a0It&#8217;s been a big topic for quite a while, but since you\u2019re an economist, I think we\u2019ll take a slightly different angle on it than many other podcasts. Today we&#8217;re going to talk about AI \u2014 but more specifically, the capital expenditures of AI, not really its capabilities.\u00a0So again, we\u2019ll have that economic twist to it.\u00a0<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">To kick it off: the so-called \u201chyperscalers\u201d \u2014 Amazon, Meta, Microsoft, and Google, all household names \u2014 are projected to increase their annual capital expenditures from $150 billion in 2023, which already seems like a crazy number, to potentially $400 billion by next year.\u00a0What does this unprecedented level of investment tell us about their confidence in AI\u2019s future profitability, despite the current limited returns?\u00a0<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-michael-normyle-nbsp-0\"><strong>Michael Normyle<\/strong>&nbsp;<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">Yeah, I think first you could say it reflects that AI is a very capital-intensive industry, requiring chips, data centers, energy, and billion-dollar training runs for models. But more broadly, maybe it\u2019s a reflection of a \u201cwinner-takes-all, or possibly winner-takes-most\u201d mentality.\u00a0Just the way we\u2019ve seen dominant search engines, browsers, and social media platforms, I think there could be a first-mover advantage here. The first company with the best AI product could potentially dominate the market. That could be the view we\u2019re seeing \u2014 maybe being the first to AGI, artificial general intelligence, meaning AI matches human intelligence, or at least the first to the best general model. That remains to be seen.\u00a0<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">But unlike browsers and search engines, the expectation is that consumers and especially businesses will be willing to pay for AI. Of course, the risk is that they\u2019re wrong. A recent survey found that only 3% of consumers pay for AI at the moment. We\u2019ll see if that changes over time.&nbsp;<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-jeff-praissman-nbsp-1\"><strong>Jeff Praissman<\/strong>&nbsp;<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">Yeah, that leads me perfectly into my next question. MIT recently reported that 95% of companies are seeing zero return on their AI investments so far. How should investors distinguish between companies that are likely to eventually monetize AI successfully versus those that might be caught in an unproductive spending cycle?&nbsp;<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-michael-normyle-nbsp-1\"><strong>Michael Normyle<\/strong>&nbsp;<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">I\u2019ll start by saying I\u2019m not an investment advisor, so I can\u2019t give real advice here, but I\u2019ll do my best with my economist lens.\u00a0It\u2019s also important to note that the MIT study was small \u2014 just 300 AI projects. They found the biggest cause of failed deployment was actually a learning gap. Companies need to learn how to best integrate these tools, and people need to learn how to use them.\u00a0So based on that, it\u2019s hard to answer the question just yet. If I had to take a stab at it, it\u2019s probably best to focus on the narrow areas where AI is already really effective \u2014 things like coding, writing, and even figuring out protein structures.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">But as workers get more comfortable with AI, and as the technology improves, it might become more challenging to suss out which applications are likeliest to succeed as they broaden. That could be a real challenge for investors.\u00a0<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-jeff-praissman-nbsp-2\"><strong>Jeff Praissman<\/strong>&nbsp;<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">About 15 years ago, tech and AI investment accounted for about 2.5% of U.S. GDP. It now accounts for about 6%. How sustainable is this trend, and what economic vulnerabilities might emerge if AI fails to deliver on the productivity promises we all hope it does?&nbsp;<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-michael-normyle-nbsp-2\"><strong>Michael Normyle<\/strong>&nbsp;<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">I\u2019m not too concerned about sustainability at the moment. I think this reflects the changing economy in large part. And this is a pretty broad group of investments we\u2019re looking at: software, computer and communication equipment, power and communication structures \u2014 all the elements needed to power data centers and the like. So it\u2019s not strictly AI; it\u2019s \u201ctech and AI.\u201d That\u2019s what makes up the 6% number. But of course, AI has become an increasing driver in recent years.&nbsp;<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">If we drill down to information processing equipment \u2014 computers, servers, etc. \u2014 it was actually a bigger share in the 1980s and 1990s as PCs rolled out. It peaked at around 3% of GDP in the early 2000s during the internet boom. Right now, it\u2019s about 2% of GDP. So there\u2019s room for further investment relative to the size of the economy.&nbsp;<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Before worrying about sustainability, though, I think the bigger concern is productivity promises. At its core, GDP growth is labor force growth plus productivity growth. Like many countries, the U.S. has an aging population. We\u2019ve also seen less immigration lately. So labor force growth is slowing. In fact, the CBO just moved forward the timeline for U.S. deaths exceeding births to 2031, from 2033. That means faster productivity growth is needed to keep the economy growing.\u00a0Economic growth is also key to debt sustainability in the U.S. If AI doesn\u2019t deliver productivity growth, we could run into issues.\u00a0<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-jeff-praissman-nbsp-3\"><strong>Jeff Praissman<\/strong>&nbsp;<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">And just to emphasize how much AI capital expenditure matters \u2014 U.S. real GDP growth for the first half of this year would\u2019ve been just 0.2% without it. We\u2019ve talked in the past about different sectors. How concerned should we be about this dependency on a single sector for economic growth?&nbsp;<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-michael-normyle-nbsp-3\"><strong>Michael Normyle<\/strong>&nbsp;<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">Honestly, I don\u2019t see it so much as a concern as a comfort. Typically, consumer spending is the engine of the U.S. economy. But lately, we\u2019ve seen a timely structural uptrend in AI investment that helps offset weakness elsewhere.&nbsp;<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">For example, consumer spending faltered a little in the first half of the year as households were cautious, waiting to see how tariffs played out. And then you have a government purposefully reducing spending, which is still a drag on growth. In that context, I think it\u2019s good that we have this multi-year trend in AI investment to help smooth out rough patches in the economy.&nbsp;<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-jeff-praissman-nbsp-4\"><strong>Jeff Praissman<\/strong>&nbsp;<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">You talked about the internet boom earlier, but what other parallels or differences do you see between today\u2019s AI investment boom and previous investment cycles \u2014 like the dot-com era or even the smartphone revolution?&nbsp;<br>It\u2019s hard to imagine now that we didn\u2019t always have smartphones in our hands, but there was a time not too long ago when they didn\u2019t exist.&nbsp;<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-michael-normyle-nbsp-4\"><strong>Michael Normyle<\/strong>&nbsp;<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">I think the internet is the closer parallel. To me, it presents more of a business case than smartphones. Like I mentioned before, during the first internet boom we saw tech equipment investment rise to 3% of GDP, which we haven\u2019t seen since. But I think it\u2019s realistic to think AI could get us back there.\u00a0Smartphones, of course, have a business case for phone makers and app developers, but the end use is really a consumer story. Even though, like you said, everyone has a phone, it hasn\u2019t been a big productivity driver. Hopefully that\u2019s the difference with AI.\u00a0<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-jeff-praissman-nbsp-5\"><strong>Jeff Praissman<\/strong>&nbsp;<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">The Congressional Budget Office has presented two dramatically different debt scenarios based on productivity growth. How realistic is the optimistic scenario where AI helps stabilize U.S. debt at 113% of GDP, rather than letting it balloon to 156%?&nbsp;<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-michael-normyle-nbsp-5\"><strong>Michael Normyle<\/strong>&nbsp;<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">The 156% path you mentioned is their baseline. That assumes 1.1% annual productivity growth out to 2055. The optimistic case is that AI boosts productivity growth to 1.6% per year. In that scenario, debt stabilizes at 113%. Debt is about 100% now, so it would rise to 113% and plateau there.&nbsp;<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">But there\u2019s also a downside scenario: productivity growth at just 0.6% per year, which would double the debt-to-GDP ratio to 200% by 2055. For context, over the last 10 years the U.S. has averaged 1.1% total factor productivity growth. So the CBO is essentially assuming that continues.\u00a0Given that, I do think it\u2019s realistic we land somewhere between the baseline and the upside scenario. Even though there aren\u2019t signs yet of AI materially impacting productivity growth, recent research suggests a wide range of outcomes. On the low end, MIT\u2019s Daron Acemoglu suggests a 1% boost to productivity in 10 years. On the high end, a Brookings study estimates a 20% gain in 10 years.\u00a0<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Given the learning curves we talked about earlier, and still-low adoption rates \u2014 only 8\u201312% of companies are using AI according to recent surveys \u2014 it will likely take a few years before we see a noticeable productivity boost. But I think there\u2019s a reasonable case that we could get closer to that optimistic path, if not all the way there.&nbsp;<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-jeff-praissman-nbsp-6\"><strong>Jeff Praissman<\/strong>&nbsp;<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">You also mentioned consumer spending earlier, and we\u2019re seeing that slow while AI capital expenditures rise. That\u2019s a shift in economic drivers. How does it affect employment patterns, wage growth, and even wealth distribution in the coming years?&nbsp;<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-michael-normyle-nbsp-6\"><strong>Michael Normyle<\/strong>&nbsp;<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">I think the slowdown in consumer spending is temporary. We\u2019ve seen tariffs pushing through a little, which is raising inflation. Core goods inflation is showing that. But it looks like a temporary boost to inflation from tariffs. That could also cause a temporary drop in real wage growth to near zero.\u00a0But early next year, tax cuts will help offset that drag, and the tariff effect on inflation will fade. So we could start to see positive momentum for spending. Early next year, there\u2019s a scenario where both consumer spending and AI CapEx grow together.\u00a0<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Given that, I don\u2019t think AI will massively impact employment patterns or wage growth in the next couple of years. There is some research from Stanford economists showing that employment for young workers in AI-exposed industries \u2014 like software engineering and customer service representatives \u2014 has been falling. Even after accounting for other factors, like the Fed\u2019s 2022 rate hikes cooling the labor market, there\u2019s still an element that seems related to AI.\u00a0At the same time, the research also found faster job growth in industries augmented by AI. One key question is whether an industry is automated or augmented by AI. Automated industries could see less hiring and shifts in work scope, which may impact wage growth. But in augmented industries, employment growth could pick up, and we might even see wage premiums develop.\u00a0<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-jeff-praissman-nbsp-7\"><strong>Jeff Praissman<\/strong>&nbsp;<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">So basically, either AI helps you be more efficient \u2014 or it takes you out of the picture for your job.&nbsp;<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-michael-normyle-nbsp-7\"><strong>Michael Normyle<\/strong>&nbsp;<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">Yeah, possibly.&nbsp;<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-jeff-praissman-nbsp-8\"><strong>Jeff Praissman<\/strong>&nbsp;<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">I want to pivot here. With so much capital being directed to AI infrastructure, are we potentially putting too many eggs in one basket and missing out on other critical areas of the economy \u2014 or even on technological developments we can\u2019t see yet because of this tunnel vision on AI?&nbsp;<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-michael-normyle-nbsp-8\"><strong>Michael Normyle<\/strong>&nbsp;<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">The bulk of the investment is in private industry, so it\u2019s not clear that means we\u2019re underinvesting elsewhere. A lot of infrastructure investment, for example, is public. On that, you can look at the American Society of Civil Engineers\u2019 infrastructure report card for the U.S., which shows things moving in the right direction, though with room for improvement.\u00a0AI is also forcing upgrades to energy infrastructure, which has been underinvested in. Given AI\u2019s power demands, it requires a comprehensive approach to energy generation. We\u2019re seeing revivals of nuclear facilities and new investment in small modular nuclear reactors. There are also advancements in energy technology more broadly.\u00a0<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">So by necessity, AI may drive positives in modernizing energy infrastructure and energy production. The challenge will be balancing AI\u2019s energy demands with environmental concerns \u2014 and that\u2019s where green energy investments could play a big role.&nbsp;<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-jeff-praissman-nbsp-9\"><strong>Jeff Praissman<\/strong>&nbsp;<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">Yeah, I was going to say, one of the things with AI \u2014 and with a lot of other technologies that flies under the radar \u2014 is just the pure amount of energy consumption these advances require. You really just touched on my next question, about the environmental concerns, energy constraints, and potential new investments in cleaner and greener energy technologies going forward.&nbsp;<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">As AI expenditures continue to rise, we\u2019re also seeing significant regional concentration in data center development. How might this geographical clustering impact grid stability in those areas, as well as real estate markets and local economies? I know Nevada and Virginia are hotspots, probably along with some others. But that\u2019s something the average person isn\u2019t necessarily thinking about, right? They just see what AI does, not the practical aspects of making it work.&nbsp;<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-michael-normyle-nbsp-9\"><strong>Michael Normyle<\/strong>&nbsp;<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">I think if you\u2019re outside those markets, it\u2019s probably not front of mind. But there are already over 600 data centers in Virginia \u2014 double the number in Texas and California, which are in second and third place. From the research I\u2019ve done, grid stability is definitely a concern. And it\u2019s not just data centers. They\u2019re coming online at the same time EVs are becoming more popular, and there\u2019s growing demand for air conditioning. Multiple factors are colliding to impact grids. So this is something that needs to be carefully planned for when constructing data centers, especially large clusters of them.&nbsp;<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">In terms of real estate, like you mentioned, Virginia and Nevada are pretty different states in terms of density. On the coasts, where areas are more densely populated, data centers are often built on formerly rural land, which can increase property prices. In Nevada, where they tend to be more remote, the impact might be smaller.\u00a0For local economies, data centers aren\u2019t very labor-intensive to operate. You get a boost to construction jobs during the build \u2014 potentially a thousand workers or more, since they\u2019re large structures \u2014 but once completed, they typically employ only 100\u2013200 people. So, not a huge long-term driver of jobs, though there is some creation.\u00a0Recent research from Carnegie Mellon and NC State estimated that electricity bills could rise as much as 25% by 2030 in data center hotspots, compared to 8% nationwide. On the flip side, data centers are a big revenue source. One county in Virginia reported that for every $1 invested in data centers, it receives $26 in tax revenues, helping fund schools and other public interests.\u00a0<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-jeff-praissman-nbsp-10\"><strong>Jeff Praissman<\/strong>&nbsp;<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">Michael, I just want to thank you for stopping by the IBKR Podcast Studio. For our listeners, you can find more from Michael and Nasdaq on our website under education, webinars, podcasts, and articles. You can also visit nasdaq.com to see their own education materials and great articles by Michael and other economists. Thanks again, Michael \u2014 appreciate you stopping by.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-michael-normyle\"><strong>Michael Normyle<\/strong>\u00a0<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">Thanks.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>AI\u2019s explosive growth comes with a hidden cost: staggering capital expenditures, soaring energy demands, and concentrated data center risks. Economist Michael Normyle joins Jeff Praissman to break down whether artificial intelligence is powering progress \u2014 or overloading the system.<\/p>\n","protected":false},"author":914,"featured_media":231223,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":true,"footnotes":"","jetpack_post_was_ever_published":false},"categories":[10842,13857],"tags":[20575,20574,18442,20576,13014,6624,587,20577,20573],"contributors-categories":[13576,13756],"class_list":["post-231222","post","type-post","status-publish","format-standard","has-post-thumbnail","category-ibkr-podcasts","category-podcasts","tag-ai-economy","tag-ai-energy-consumption","tag-ai-infrastructure","tag-artificial-intelligence-investment","tag-capital-expenditures","tag-data-centers","tag-economic-growth","tag-technology-boom","tag-u-s-productivity-growth","contributors-categories-interactive-brokers","contributors-categories-nasdaq"],"pp_statuses_selecting_workflow":false,"pp_workflow_action":"current","pp_status_selection":"publish","acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v26.9 (Yoast SEO v28.0) - https:\/\/yoast.com\/product\/yoast-seo-premium-wordpress\/ -->\n<title>Is AI About to Blow a Fuse? | IBKR Podcasts<\/title>\n<meta name=\"description\" content=\"AI\u2019s explosive growth comes with a hidden cost: staggering capital expenditures, soaring energy demands, and concentrated data center risks. 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