When will AI pay off for the billions being invested?

The NewYorkTime.com reported that “Corporate spending on artificial intelligence is surging as executives bank on major efficiency gains. So far, they report little effect to the bottom line.”  The August 13, 2025 article entitled “Companies Are Pouring Billions Into A.I. It Has Yet to Pay Off” (https://www.nytimes.com/2025/08/13/business/ai-business-payoff-lags.html) included these comments from the author Steve Lohr:

Nearly four decades ago, when the personal computer boom was in full swing, a phenomenon known as the “productivity paradox” emerged.

It was a reference to how, despite companies’ huge investments in new technology, there was scant evidence of a corresponding gain in workers’ efficiency.

Today, the same paradox is appearing, but with generative artificial intelligence. According to recent research from McKinsey & Company, nearly eight in 10 companies have reported using generative A.I., but just as many have reported “no significant bottom-line impact.”

A.I. technology has been racing ahead with chatbots like ChatGPT, fueled by a high-stakes arms race among tech giants and superrich start-ups and prompting an expectation that everything from back-office accounting to customer service will be revolutionized. But the payoff for businesses outside the tech sector is lagging behind, plagued by issues including an irritating tendency by chatbots to make stuff up.

That means that businesses will have to continue to invest billions to avoid falling behind — but it could be years before the technology delivers an economywide payoff, as companies gradually figure out what works best.

Call it the “the gen. A.I. paradox,” as McKinsey did in its research report. Investments in generative A.I. by businesses are expected to increase 94 percent this year to $61.9 billion, according to IDC, a technology research firm.

But the percentage of companies abandoning most of their A.I. pilot projects soared to 42 percent by the end of 2024, up from 17 percent the previous year, according to a survey of more than 1,000 technology and business managers by S&P Global, a data and analytics firm.

What do you think?