AI: The Financial Reckoning Begins

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By: Peter Lauria

It was only a matter of time.

For those keeping score, the second quarter of 2024 is likely to mark the end of the era of blank-check spending on artificial intelligence. To be sure, corporate leaders and other experts still firmly believe AI is the key to the future of work, but a new voice has entered the fray: the Money Folks.

This includes chief financial officers, outside analysts, and—perhaps above all—investors. Many of these stakeholders are furiously demanding to know where all the billions are going: At last count, tech firms alone were pouring $200 billion a year into AI, a figure that’s expected to reach $1 trillion by 2030.

Olaf Groth, faculty director of emerging technology strategy at UC Berkeley’s Haas School of Business, says AI deployment has entered the phase where investors want measurable results. The problem is that the technology is still too young for most companies to show any. “CFOs need something to communicate to investors besides what they are spending,” says Groth. Leaders are trying to navigate the ever-present tension between long-term strategy and short-term performance. And that, of course, is a pattern that has played out with nearly every other new tech, from the internet to cloud computing.

Except in this case, the funds involved are so much bigger, and any profits are hard to quantify. All of which scares investors and budget setters. “Any forward projection comes with the caveat that they have to get it right,” says Groth. So far, studies on AI failure rates, along with data on the technology’s effect on employee productivity, don’t inspire confidence. “Skepticism is growing,” says Nicole Tanenbaum, partner and chief investment strategist at Chequers Financial Management.

Experts say the data to date underscores a fundamental problem confronting leaders: Even as they’ve poured billions into AI, they’ve failed to invest adequately in training employees to use it. A recent survey found that just 38 percent of employers provide AI training, and only one-fourth of employees who can make use of it do. It doesn’t take a data scientist to recognize that most AI projects are starting off with a low probability of success. Indeed, in all, companies are only earmarking about a quarter of their training budgets for AI. “Companies that underinvest in the human component won’t get the returns they are hoping for out of AI,” says Korn Ferry senior client partner Maria Amato.

Leaders have tried to justify more spending by pointing to strong forward demand and increases to their cloud revenues from AI, but investors haven’t been sold. Tanenbaum says companies were able to keep investors at bay last year only by cutting costs to offset increased spending, mostly through layoffs. “The market has rewarded workforce reductions,” says Tanenbaum, “and management teams have been quick to highlight this narrative with investors.”

The challenge now for leaders is to get investors back on board with their AI story without having to add another chapter on layoffs. It won’t be easy. Deepali Vyas, global leader of the Applied Intelligence practice at Korn Ferry, says returns on AI “likely won’t catch up to investments for at least another five or 10 years.”

Photo Credits: Blue Light Studio/Getty Images