AI Is Getting Cheaper. That Won’t Fix Everything

For a technology that promises to help businesses cut costs, artificial intelligence has had a big problem with being so costly.

AI’s scaling laws, which say that you need more computing power to make more powerful models, have put tech companies on a race to spend billions of dollars building vast data centers and buying powerful chips — costs they can’t help passing on to their customers. Google’s AI tool for generating documents or emails for office workers is not cheap. It adds $20 to their employer’s monthly $6 bill for the company’s Workspace suite, per staff member. Microsoft Corp.’s Copilot AI assistant costs $30 a month per worker.

Meanwhile, the cost of deploying AI directly into a company’s systems can cost between $5 million and $20 million, according to research firm Gartner, which estimates that 30% of generative AI projects will be abandoned by the end of 2025 in part because of all that expense.

The good news for those customers is that AI costs appear to be coming down, helping to close the gap between benefit and investment. The bad news: That still doesn’t address the bigger issue of utility, which will take a few years yet to solve.

The prevailing wisdom in Silicon Valley is to keep spending to get a foothold on the future. On Tuesday, Microsoft announced that its capital expenditures hit a record $19 billion in the last quarter, more than 80% higher than last year. Chief Executive Officer Satya Nadella said all that investment would continue to “capture the opportunity of AI.” Alphabet Inc. CEO Sundar Pichai said much the same in a recent earnings call about Google’s results: “The risk of underinvesting is dramatically greater than the risk of overinvesting for us.” Investors aren’t entirely buying it: Microsoft’s shares are down about 2% since its latest earnings announcement, Google’s by 5%.

not cheap