Goldman Sachs US economist Elsie Peng published a research note in July 2026 titled “From Innovation to Productivity Boom: Lessons from the ICT Revolution for the AI Era.” The core argument is deceptively simple: transformative technologies historically take about 20 years from their breakthrough moment to deliver meaningful productivity gains at the macroeconomic level. If that pattern holds for generative AI, we’re looking at the early-to-mid 2030s before the real payoff arrives.
The J-curve problem
Peng’s note focuses on the information and communications technology revolution that unfolded between 1980 and 2000. The personal computer showed up in offices in the early 1980s. Productivity growth didn’t meaningfully accelerate until the late 1990s.
The explanation, in hindsight, was what Peng describes as a J-curve pattern. Before a technology can boost output, organizations need to invest heavily in what economists call “organizational capital” — retraining workers, redesigning workflows, and fundamentally rethinking how they operate.
According to Peng’s analysis, significant labor productivity boosts from ICT didn’t show up until roughly 50% of businesses had adopted the technology. Not bought it, not piloted it. Actually adopted it into their core operations.
