"Since generative AI surged into mainstream usage with the launch of ChatGPT in 2022, it has largely followed the same path that computers did in their infancy. The world can't stop talking about LLMs and AGI. Yet as late as last year, even the buzziest of AI companies earned shockingly little. OpenAI, for example, had annualized revenue of around $20 billion as of the end of last year. For comparison, the pest control industry is about the same size, and the pizza industry is about two times bigger."
"The chasm between excitement and actual economic impact shows up in bigger datasets, too. A massive study published in February asked 6,000 business leaders how AI was impacting their operations. The answer? Not at all. While 63% of business leaders say they've adopted AI, 90% found it had no impact on their firm's employment or productivity."
"Official stats tell largely the same story. A study from the Federal Reserve Bank of Saint Louis found that generative AI led to a 5.4% improvement in worker productivity -hardly the"
Generative AI has rapidly gained mainstream attention, but early economic impact has lagged behind excitement. Personal computers and early internet technologies once appeared everywhere while productivity statistics showed little improvement, a pattern later called Solow’s Paradox. By the mid-1990s, productivity rose sharply as technology translated into economic value. Current evidence suggests AI may be approaching a similar tipping point. Even with broad adoption, many firms report no measurable effects on employment or productivity. Business leader survey results show high adoption rates alongside mostly negligible operational impact. Official productivity estimates also indicate modest gains so far, implying that benefits may take time to materialize.
Read at Fast Company
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