Astronomical AI Spending Is Causing Jitters on Wall Street

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published 26 July 2024

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Emerging artificial intelligence technology has set off a frenzy of competition among tech giants. The resulting avalanche of tech spending has led to soaring revenue at AI suppliers, especially Nvidia (NVDA), which makes must-have AI chips.

There’s a problem, though: Growing concerns that generative AI will take too long to pay off. “Tech giants and beyond are set to spend over $1 trillion on AI capex in coming years, with so far little to show for it,” reads the opening of a recent Goldman Sachs publication, “Gen AI: Too Much Spend, Too Little Benefit?” The report cobbles together analysis from interviews with Goldman Sachs analysts and outside experts.

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It underscores an emerging skepticism, even from AI backers, as pressure builds for real products and real profits. Facebook owner Meta (META), for example, will spend up to $40 billion on capital expenditures this year. Alphabet (GOOG), Amazon (AMZN), Apple (AAPL) and Microsoft (MSFT) are spending huge sums on Nvidia chips and related tech infrastructure. Other tech and nontech companies are investing heavily, too.

The supercharged AI chatbots from ChatGPT and others can create text, images, video, data analysis and much more. The tech can assist in medical discovery and legal research or generate computer code and flag security threats. Users interact with the chatbots in plain English, much like an online search engine, so no special technical know-how is necessary. That means, in theory, that millions of consumers and workers can adopt the tech rapidly, especially as tech giants push hard to integrate it into their products and services.

But previous new technology platforms have taken a decade or more to garner mass adoption and yield widespread productivity gains. And the new crop of AI has the distinctive challenge, at least right now, of being an extremely high-cost technology to build that isn’t quickly replacing or disrupting anything. It’s still early and costs will go down, but as more money gets poured into the tech, the return on investment will have to be that much bigger to justify the cost.

If there is a bubble in AI spending, there’s good reason to think it won’t burst soon, say some Goldman Sachs analysts. That’s not exactly a comforting thought, but note some stark differences between today’s AI mania and the 1990s dot-com debacle. Today’s tech giants are flush with cash and have huge customer bases. The level of spending is not that different from other huge technology shifts in the consumer and business market. Also, Wall Street is paying closer attention to return on investment now and is quicker to penalize companies that come up short. On top of that, today’s AI systems truly are amazing innovations with serious long-term potential.

What's next for Generative AI?

With lots of questions about the future, here are four forecasts for making sense of what’s next for generative AI.

Don’t hold your breath for a single breakthrough dominated by one event, app or company, as generative AI spreads. The tech is being integrated, sometimes seamlessly, into consumer and business products and services, such as work collaboration tools, e-mail, word processing, photo editing and online search. For example, Adobe (ADBE) Photoshop already uses AI to create images or transform photos, and LinkedIn uses it to help write user posts. For its part, Meta says its AI investment is helping improve personalized recommendations and ads.

Direct revenue will remain hard to come by. Getting consumers and businesses to fork over extra money for premium AI services won’t be easy, especially for start-ups. But look for early signs of moneymaking potential at Microsoft and Alphabet. Both are charging for their AI tools. Microsoft’s AI assistant CoPilot runs $30 per month per user. Alphabet is charging $20 per month per user for its Google Gemini service. The companies will be eager to highlight any positive signs of rising revenue from AI.

Business adoption will be a bumpy ride. Companies have to contend with cybersecurity risks and inaccurate responses generated by AI chatbots. However, they can look forward to new AI in coming updates of the software they use, which could lead to productivity wins. Surveys show that executives lack a clear plan and are worried about how to prove any benefits. That’s true even if many of their workers are already using generative AI tools, often on the down-low, for work tasks.

Expect a shakeout of sorts in the next year or so. That time horizon is when analysts are looking for hit products and services that gain mass adoption. Expect a harsher assessment of leading AI companies by Wall Street if they aren’t showing clear signs of growing AI adoption, new hit services and increasing sales. In a couple of years, don’t be surprised if big tech and other companies start reassessing their AI spending, perhaps reining in some outlays while prioritizing more focused strategies.

This forecast first appeared in The Kiplinger Letter, which has been running since 1923 and is a collection of concise weekly forecasts on business and economic trends, as well as what to expect from Washington, to help you understand what’s coming up to make the most of your investments and your money. Subscribe to The Kiplinger Letter.

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John Miley is a Senior Associate Editor at The Kiplinger Letter. He mainly covers technology, telecom and education, but will jump on other important business topics as needed. In his role, he provides timely forecasts about emerging technologies, business trends and government regulations. He also edits stories for the weekly publication and has written and edited e-mail newsletters.

He joined Kiplinger in August 2010 as a reporter for Kiplinger's Personal Finance magazine, where he wrote stories, fact-checked articles and researched investing data. After two years at the magazine, he moved to the Letter, where he has been for the last decade. He holds a BA from Bates College and a master’s degree in magazine journalism from Northwestern University, where he specialized in business reporting. An avid runner and a former decathlete, he has written about fitness and competed in triathlons.