"Every generation believes its breakthrough technology will change everything overnight. The computer. The internet. The smartphone. Today? Generative AI. Each wave begins the same way: visible transformation, invisible results. Leaders feel the shift in their daily work, yet productivity numbers stay stubbornly flat. In the 1980s, economist Robert Solow captured this tension perfectly: "You can see the computer age everywhere but in the productivity statistics.""
"When Solow observed in 1987 that computers were "everywhere but in the productivity statistics," he wasn't dismissing technology's power - he was highlighting the delay of benefits. New tools spread faster than organizations can absorb them and productivity doesn't rise simply because companies buy hardware or software. It improves only after they learn how to use those tools effectively. His remark, now known as Solow's productivity paradox, described a world saturated with computers but lacking measurable economic payoff."
Generative AI is following a familiar pattern where visible change appears before measurable productivity gains. Historical experience with computers shows that tools spread faster than organizations can absorb them, producing delayed economic payoff. Productivity does not rise simply because companies acquire new hardware or software; improvements require learning how to use tools effectively and changing workflows. Gartner's Hype Cycle maps the emotional market arc from inflated expectations to disillusionment and eventual maturity. Long-term benefits depend on organizational adaptation: patience, restructuring, and retraining will determine which organizations capture sustained productivity improvements.
Read at MarTech
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