Technology vs. asset class<\/h2>\n\n\n\n
As a technology, AI is the product that people use<\/strong>. Putting aside the question of its profitability, it creates value by writing code, analyzing data, or automating tasks, among other functions. When talking about the technology, the question is what it can do<\/strong>. <\/p>\n\n\n\n As an<\/strong> asset class<\/strong><\/a>, AI is the investment vehicle<\/strong>. It creates value through return on investment, stock price appreciation, and market speculation. When talking about the asset class, the question is how much profit it can generate<\/strong>.<\/p>\n\n\n\n When you buy the asset class, you\u2019re not necessarily investing into the technology itself. You\u2019re not funding the next big frontier model training. In most cases, you\u2019re investing into things that stand to profit from people using the technology. Kind of like how the person who buys land next to a highway stands to benefit from people using cars \u2014 they could open a restaurant to feed the drivers. <\/p>\n\n\n\n This distinction is important because bubbles happen in asset classes, not in technologies<\/strong>. According to Sequoia partner David Cahn, AI would need to generate almost $3 trillion in revenue to justify all the infrastructure spending<\/a>. If it doesn\u2019t manage to do so, the AI bubble will burst \u2014 the asset class will go kaput, but the technology will remain.\u00a0<\/p>\n\n\n Bubbles tend to form around revolutionary technologies precisely because they\u2019re revolutionary. Investors see that this<\/em> is the future, and they want to get in on the action early to maximize the return on investment. The problem is, they tend to overestimate the short-term ROI.<\/p>\n\n\n\n When these same people realize that the short-term ROI they were hoping for isn’t real, and that they\u2019re investing into a money sink, they hurry to sell and recoup what investment they can. This triggers a frantic selling frenzy and, with no one willing to buy, the asset class plummets in value, bursting the bubble.<\/p>\n\n\n\n This happened with the dot-com bubble around the start of the new century. Investors saw that the Internet was the future. The benefit of hindsight shows us that they were right. But they severely overestimated the short-term ROI. That bubble reached its peak in 2000 when the Nasdaq stock index hit its all-time high<\/a>. It burst quickly after, and, by 2002, the crash had wiped out more than $5 trillion in market value.<\/p>\n\n\n\n The Internet, however, didn\u2019t disappear. It remained and got integrated so deeply into society that everyday life without it now looks unimaginable. <\/p>\n\n\n\n The same thing will likely happen to AI. In fact, AI being in a bubble right now only serves to benefit the technology, since only bubbles can build the necessary infrastructure<\/a> for revolutionary new general-purpose technologies to enter their golden age.\u00a0<\/p>\n\n\n\n According to Carlota Perez, each technological revolution is divided into an installation phase and a deployment phase<\/a>.\u00a0<\/p>\n\n\n\n Within the installation phase, there\u2019s a period of frenzy, when speculative investment overtakes actual production values. This inevitably comes to a turning point when the speculative bubble bursts, causing a financial crash. <\/p>\n\n\n\n What follows is the deployment phase \u2014 the so-called golden age of each technology \u2014 that\u2019s driven by actual production capital<\/strong>. This is when the technology matures, gets regulated, gets widely adopted, creates new jobs, increases productivity, and brings about economic growth. <\/p>\n\n\n\n Perez argues that this speculative mania is a necessary evil, since conservative capital could never take the financial risk needed to build a nationwide or global infrastructure ahead of actual demand. It took the dot-com bubble to deploy fibre-optic cables around the world that made the golden age of the Internet we now live in possible. <\/p>\n\n\n\n MIT Institute Professor and Nobel laureate Daron Acemoglu calculates that, in the next 10 years, AI will increase the GDP by just 1%<\/a>. OpenAI released a study saying that there\u2019s no correlation between revenue per employee and tokens spent<\/a>.<\/p>\n\n\n\n AI isn\u2019t the first general-purpose technology that was released to much fanfare yet offered little to no productivity gains. Examining why this was the case with previous GPTs helps shed light on what you can expect from AI moving forward.<\/p>\n\n\n\n Electricity may be the best example of this. The first commercial electric power stations opened in the 1880s, but it wasn\u2019t until the 1920s that we got the massive productivity boom from electrification. So, why the 40 year long gap?<\/p>\n\n\n\n Further reading<\/strong><\/p>\n\n\n\n One of the reasons for AI\u2019s mediocre performance is its prohibitive cost, which is only expected to rise. Read more about it here:<\/p>\n\n\n\n Well, for 40 long years, the new technology was just being retrofitted onto existing processes<\/a> designed with the steam engine in mind!<\/p>\n\n\n\n Before electricity, factories had massive, centralized steam engines that powered machines through ceiling mounted drive shafts. Because of the limitations of these engines, factories had to be tall, multi-floored buildings \u2014 it was just more practical to transfer power vertically than horizontally.<\/p>\n\n\n\n The reason electricity didn\u2019t result in any productivity gains for so long was because factories simply replaced their massive, centralized steam engines with massive, centralized electric motors. They retrofitted the technology, treating it as a 1-to-1 substitution.<\/p>\n\n\n\n The productivity gains came when engineers figured out they could fit a small, cheap electric motor on each individual machine. This allowed them to flatten factories and organize them with the flow of raw materials in mind, paving the way for the assembly line.<\/p>\n\n\n\n AI is going through the same retrofitting process. Nowadays, one of the main pushes for AI is in coding, but while AI has increased the volume of code written, this hasn\u2019t translated to more products\/features being shipped<\/a>. This is because more time is spent on code review, since humans have to check all the AI code.<\/p>\n\n\n\n Further reading<\/strong><\/p>\n\n\n\n If you\u2019re worried about AI making your job redundant, check out this guide to learn how to make yourself AI-proof:<\/p>\n\n\n\n When the AI bubble bursts, the headlines will announce the death of artificial intelligence. But the technology won\u2019t go away \u2014 it will just get democratized.<\/p>\n\n\n\n If history is any indicator, that\u2019s when the real productivity gains will be made \u2014 when the speculators leave and a market driven by actual production capital can innovate new use cases for the technology. <\/p>\n\n\n\n The money that\u2019s being poured into the speculative market may disappear, but the infrastructure built will remain. This may be the data centers \u2014 if they ever get built<\/a> \u2014 or the countless GPUs Nvidia is producing that have nowhere to be plugged in<\/a>.\u00a0<\/p>\n\n\n\n It\u2019s impossible to imagine what the future will look like. No one could have predicted remote work, cloud technology, or smart TVs during the dot-com era \u2014 the Internet back then was basically just webpages, accessible through directory-based searches on dial-up.<\/p>\n\n\n\n Until then, AI will continue to offer meaningful productivity gains in only a handful of use cases, much like how computers significantly boosted the productivity of accountants when they came out, while offering very little in the way of productivity to most other professions. <\/p>\n\n\n\n So don\u2019t feel pressured to retrofit AI onto your existing processes if it doesn\u2019t provide a clear benefit. Keep using the tools that actually maximize productivity and profitability.<\/p>\n\n\n\n \n Elevate productivity with CAKE.com<\/p>\n \n Combine time tracking, team communication, and project management to boost your organization\u2019s productivity \u2014 with the CAKE.com Suite.<\/p>\n \n Learn why artificial intelligence won’t go away when the AI bubble bursts.<\/p>\n","protected":false},"author":10,"featured_media":5271,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[12],"tags":[],"class_list":["post-5269","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-technology-corner"],"acf":[],"yoast_head":"\n![\"AI](\"https:\/\/cake.com\/blog\/wp-content\/uploads\/2026\/10\/AI-the-Technology-vs-AI-the-Asset-Class.webp\")
<\/figure>\n<\/div>\n\n\nHow bubbles form and what they leave behind<\/h2>\n\n\n\n
The Carlota Perez Framework \u2014 how bubbles build infrastructure<\/h2>\n\n\n\n
Why AI feels lackluster at the moment \u2014 the productivity paradox across previous GPTs<\/h2>\n\n\n\n
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What this means for future of AI and your productivity<\/h2>\n\n\n\n
![\"Elevate](\"https:\/\/cake.com\/blog\/wp-content\/uploads\/2025\/12\/banner-productivity-suite.png\")
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