Inside AI’s $1 Trillion Cash Bonfire

Generative AI has lured an enormous amount of capital. Indeed, Goldman Sachs estimates companies will spend $1 trillion to use AI chatbots in their operations. A recent example of such capital flows is OpenAI’s recent $6 billion capital raise. This October 2024 investment nearly doubled the ChatGPT provider’s private market value to $157 billion, according to The New York Times. A look inside the mindset of executives who are driving the investment of this capital reveals a powerful duality, according to my book Brain Rush. The battle between two fears, missing out on the next big thing and big lawsuits or reputational damage, makes it hard for companies to earn a return on that investment. Keeping that $1 trillion from going up in flames depends on whether generative AI can find a killer app. A case in point is Apple’s iTunes Store — which resulted in a near-quadrupling of iPod sales. The iTunes Store was a killer app because it made the iPod so much more useful for consumers. For example, joggers who formerly listened to music on a Sony Walkman flocked to the iPod. Why? It was smaller and lighter and enabled them to customize playlists. Could generative AI find a killer app? Some technology waves change the world — notably the World Wide Web. Others don’t — such as virtual reality. Despite the massive hype and enormous investment, generative AI appears unlikely to change the world. Waves that change the world pass three tests: They make life much better for people. Many people eagerly pay a high price for the new technology. Future profits more than offset the investment required to build it. Sadly, generative AI does not pass any of these tests. Before getting into the reasons, I have observed ChatGPT doing interesting things — but so far nothing significant enough to change the world. For instance, in January, one of my Babson College students uploaded a book I assigned for a course into ChatGPT. He told me he spoke his questions to ChatGPT and the book responded in “a very high quality” voice. I recently used Google’s Deep Dive to create a podcast about Brain Rush led by two AI hosts. Generative AI has yet to make peoples’ lives much better Such uses do not make people willingly pay a high price to keep using it. In a September Babson class, only two students — out of 30 — used ChatGPT occasionally for research. Because of hallucinations, the students had to double-check its results — reducing the technology’s value. Hallucinations are a feature — rather than a bug — of large language models. That’s because they are trained on data — not all of which is accurate — to make predictions about the next word in a sentence. Sometimes the LLM guesses right, sometimes not. The price users pay does not cover generative AI’s costs Neither ChatGPT nor Microsoft Copilot earn enough revenue to cover its costs. In 2024, OpenAI expects to generate about $3.7 billion in annual revenue while spending $8.7 billion — producing a $5 billion loss, noted the Times. While Microsoft declined to quantify its Copilot revenue in the most recent quarter, the AI-powered assistant’s costs are significantly higher than its revenue. For example, GitHub Copilot, a service that helps programmers create, fix, and translate code, costs between $20 and $80 per month to run — way above the service’s $10 per month subscription fee, according to The Wall Street Journal. People are not willing to pay enough for ChatGPT and Copilot because they fail the critical test of a killer app — they do not relieve customer pain more effectively than current products. Performance and cost issues with Copilot are causing customers to pause their $30-per-month-per-user Copilot contracts for Office 365, according to The Information. Profits may fall short of the investment needed to build AI chatbots A big part of companies’ investments in generative AI is the electricity the data centers need to keep AI chatbots running. Indeed, in September 2024, Microsoft spent an estimated $16 billion on a 10-year contract with Constellation Energy, the company that operates Three Mile Island — one of whose reactors famously melted down in 1979, according to my September 2024 Forbes post. As I noted in my Value Pyramid case study, most generative AI use cases help people overcome creator’s block — such as the anxiety about writing an email. Fewer generative AI applications help improve the productivity of business functions such as customer service or coding. And few, if any, applications of AI chatbots enable companies to add new sources of revenue. Until leaders deploy AI chatbots to make life much better for many people, their $1 trillion investment could go up in smoke. EXPERT OPINION BY PETER COHAN, FOUNDER, PETER S. COHAN & ASSOCIATES @PETERCOHAN