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Companies Are Pouring Billions Into AI — It Has Yet To Pay Off

The Straits Times

|

August 18, 2025

8 in 10 firms use Gen AI, but just as many say 'no significant bottom-line impact'

- Steve Lohr

Companies Are Pouring Billions Into AI — It Has Yet To Pay Off

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 (Gen AI). According to recent research by McKinsey & Co, nearly eight in 10 companies have reported using Gen AI, but just as many have reported "no significant bottom-line impact".

AI technology has been racing ahead with chatbots such as ChatGPT, fueled by a high-stakes arms race among tech giants and super-rich 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 economy-wide payoff, as companies gradually figure out what works best.

Call it the "Gen AI paradox," as McKinsey did in its research report. Investments in Gen AI by businesses are expected to increase 94 per cent in 2025 to US$61.9 billion (S$79.5 billion), according to IDC, a technology research firm.

But the percentage of companies abandoning most of their AI pilot projects soared to 42 per cent by the end of 2024, up from 17 per cent 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 also because of "human factors" like employee and customer resistance or lack of skills, said S&P Global senior analyst Alexander Johnston.

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