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When will AI start living up to the hype?

Bangkok Post

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August 18, 2025

Corporate spending on artificial intelligence is surging as executives bank on major efficiency gains. So far, they report little effect on the bottom line, writes Steve Lohr from New York

- Steve Lohr

early 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 & Co, nearly eight in 10 companies have reported using generative AI, but just as many have reported “no significant bottom-line impact.”

AI technology has been racing ahead with chatbots like ChatGPT, fuelled by a high-stakes arms race among tech giants and superrich startups and prompting an expectation that everything from back-office accounting to customer service will be revolutionised. 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.AI paradox," as McKinsey did in its research report. Investments in generative AI by businesses are expected to increase 94% this year to $61.9 billion, according to IDC, a technology research firm.

But the percentage of companies abandoning most of their AI pilot projects soared to 42% by the end of 2024, up from 17% 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.

Projects failed not only because of technical hurdles, but often because of “human factors” like employee and customer resistance or lack of skills, said Alexander Johnston, a senior analyst at S&P Global.

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