{"id":634578,"date":"2026-10-02T21:06:10","date_gmt":"2026-10-02T21:06:10","guid":{"rendered":"https:\/\/www.newsbeep.com\/il\/634578\/"},"modified":"2026-10-02T21:06:10","modified_gmt":"2026-10-02T21:06:10","slug":"premium-how-has-ai-changed-the-economy","status":"publish","type":"post","link":"https:\/\/www.newsbeep.com\/il\/634578\/","title":{"rendered":"Premium: How Has AI Changed The Economy?"},"content":{"rendered":"

This week, the Wall Street Journal ran an alarming illustration of AI\u2019s potential share of GDP<\/a> that I\u2019d argue did more to muddy the waters than actually telling anyone anything, mostly because its measurement, for whatever reason, covered 2025 to 2032, meaning that six out of the eight years of the analysis were estimates of spending.<\/p>\n

\"\"<\/p>\n

To be fair, this analysis came from the Brookings Institution\u2019s Stijn van Nieuwerburgh rather than the Journal itself, but I cannot express how profoundly unhelpful it is to discuss things years in the future.\u00a0<\/p>\n

The Journal itself acknowledged this, giving us a far-more-useful number, emphasis mine:<\/p>\n

Projecting investment is tricky, and total spending might well end up substantially lower. Still, the money poured into data centers this year already represents an investment unprecedented in recent history. AI investment in the U.S. is projected to hit 1.9% of GDP in 2026, according to new estimates from Goldman Sachs. The railroad boom of the late 19th century marked the last time the build-out of one new industry accounted for a larger share of the economy.\u00a0<\/p>\n

Yet it\u2019s important to be specific that this is almost entirely a result of AI data center construction and GPU sales rather than anything to do with the companies actually renting AI compute. In other words, AI itself isn\u2019t helping boost America\u2019s economic growth, but rather the infrastructure for it to theoretically run on.<\/p>\n

This is extremely problematic, because it means that at some point data center construction will slow or stop (as discussed in this week\u2019s free newsletter<\/a>) through some combination of moratoriums and ever-pricier debt, removing any contribution to GDP and leaving AI \u2014 either through the revenue generated from selling services or productivity improvements \u2014 to cover the shortfall.<\/p>\n

The problem with calculating the exact contribution of the tech industry is that so many different pieces of these companies flow into different \u201cindustries\u201d (of which there are seventeen in total) in the BEA\u2019s<\/a> data based on the specific economic contribution.\u00a0<\/p>\n

For example, Apple\u2019s services vertical (like iCloud) would flow into the \u201cUS Information\/ICT\u201d indices of GDP calculation, but its sales of iPhones, Macs and iPads would flow into manufacturing, the same place where NVIDIA\u2019s GPU sales would go. ICT also doesn\u2019t include consultancy revenue or IT services from companies like Accenture, but that isn\u2019t really relevant to the analysis.<\/p>\n

In any case, the ICT industry\u2019s contribution to GDP is actually very, very useful for this calculation, because it specifically includes sales of AI software and rentals of AI GPUs. There\u2019re two numbers to look at here. As a share of nominal GDP \u2014 strictly how many dollars it\u2019s contributed to GDP \u2014 tech\u2019s contribution has been flat for the last two years. In other words, all those supposed GPU rentals and AI software sales in 2024 and 2025 didn\u2019t really do much on an economic basis.\u00a0<\/p>\n

\"\"<\/p>\n

I can already hear someone screaming that we need to measure \u201creal GDP\u201d \u2014 which factors in improvements to software and hardware that would theoretically boost the real GDP contribution of the ICT industry.\u00a0<\/p>\n

The problem I have with that analysis is that the BLS\u2019s Producer Price Index for Software Publishers<\/a> \u2014 a measure of how prices for packaged software have changed over time that the BEA uses to calculate real GDP \u2014 is currently sitting lower than it was in 1997, suggesting that software prices have dropped over time in a period where general prices have roughly doubled.<\/p>\n

This isn\u2019t remotely accurate based on the actual experience of people buying software. As I covered in the Hater\u2019s Guide To The SaaSpocalypse<\/a>, more than half of SaaS companies have increased their prices every single year since 2022, customers are paying more every year for the same features, and overall SaaS inflation ran over nine percentage points higher than consumer inflation every single month of 2025. This problem began in or around 2022, when Microsoft bumped up prices<\/a>, inspiring industry-wide inflation.<\/p>\n

In other words, the BLS\u2019 \u201cquality\u201d adjustments appear to be treating many of these price increases as customers getting better software for their money, rather than paying more money for the same software, with the BEA in turn counting that as businesses buying more software.\u00a0<\/p>\n

The BLS believes that software is effectively the same price as it was in 1997, largely because giving customers \u201cmore value\u201d and allowing them to \u201cdo more,\u201d which does not make sense if you\u2019ve used a Microsoft product recently.\u00a0<\/p>\n

The BLS\u2019 preferred method for these adjustments is based on the cost of the change (IE: how much more it costs to provide), meaning that any price increase connected to AI services, which require expensive tokens to provide, could be potentially considered the same or even lower-priced in the eyes of the BLS.\u00a0<\/p>\n

The BLS\u2019 data is understating how much the cost of software has actually increased in the last few years, and as a result, the BEA may be \u2014 accidentally \u2014 overstating its contribution to GDP. And AI services are only making things worse.<\/p>\n

With that in mind, I calculated the gross value (a business\u2019 sales minus its costs bought from other businesses, so no wages included) added by the ICT industry against real GDP, and found that while tech\u2019s share has grown steadily, said growth hasn\u2019t changed dramatically in the era of AI, even using the BEA\u2019s own flattering figures.<\/p>\n

Sidenote: I want to be crystal clear about the data I\u2019m discussing here. The ICT industry portion of what you\u2019re about to read is inclusive of GPU rentals, but the BLS data around software does not include them.\"\"<\/p>\n

All of this is to say that even with various statistics agencies having a fairly distorted view of the tech industry \u2014 at least when it comes to selling software and renting infrastructure \u2014 the AI era\u2019s contribution feels a little mediocre.\u00a0<\/p>\n

In preparing this newsletter, I\u2019ve realized something a little worrying: that basically every economic analysis of \u201cAI\u2019s contribution to the economy\u201d is based on either flawed data or flimsy assumptions about AI and the tech industry itself. Economists have tied themselves in knots trying to rationalize the astonishing amounts of money invested in AI, and in doing so haven\u2019t made sure that even their simplest assumptions \u2014 like how much the tech industry itself contributes \u2014 are meaningfully capturing what\u2019s going on.<\/p>\n

Today\u2019s newsletter is a frank evaluation of AI\u2019s true effect on the economy, specifically focused on actually measuring what\u2019s happening today rather than the endless analyses of hypotheticals that you\u2019ll find everywhere else.<\/p>\n

You see, everybody is obsessed with metrics that don\u2019t matter \u2014 cost-per-token, teraflops, and vague analyses of jobs data \u2014 all to avoid a much grimmer point: that when you remove the capex, AI has had a negligible effect on GDP.\u00a0<\/p>\n

And beneath the surface, I\u2019ve found evidence that software sales\u2019 contribution to GDP may have been meaningfully misstated since 2022.<\/p>\n","protected":false},"excerpt":{"rendered":"This week, the Wall Street Journal ran an alarming illustration of AI\u2019s potential share of GDP that I\u2019d…\n","protected":false},"author":2,"featured_media":634579,"comment_status":"","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[20],"tags":[345,343,344,85,46,125],"class_list":["post-634578","post","type-post","status-publish","format-standard","has-post-thumbnail","category-artificial-intelligence","tag-ai","tag-artificial-intelligence","tag-artificialintelligence","tag-il","tag-israel","tag-technology"],"_links":{"self":[{"href":"https:\/\/www.newsbeep.com\/il\/wp-json\/wp\/v2\/posts\/634578","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.newsbeep.com\/il\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.newsbeep.com\/il\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/il\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/il\/wp-json\/wp\/v2\/comments?post=634578"}],"version-history":[{"count":0,"href":"https:\/\/www.newsbeep.com\/il\/wp-json\/wp\/v2\/posts\/634578\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/il\/wp-json\/wp\/v2\/media\/634579"}],"wp:attachment":[{"href":"https:\/\/www.newsbeep.com\/il\/wp-json\/wp\/v2\/media?parent=634578"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.newsbeep.com\/il\/wp-json\/wp\/v2\/categories?post=634578"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.newsbeep.com\/il\/wp-json\/wp\/v2\/tags?post=634578"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}