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October 05, 2026
Partner, Chief Economist
Total factor productivity (TFP) measures how much output the economy produces from a given quantity of labor and capital. It is what remains of growth after accounting for more hours worked and more machines installed. When firms produce more without adding inputs, TFP rises. For that reason it is the closest available proxy for technological progress and for genuine improvements in how inputs are combined.
Labor productivity, or output per hour, is a different concept. It can rise for three reasons: workers are given more or better equipment (capital deepening), the composition of the workforce shifts toward higher-skilled labor or TFP improves. Only the third reflects true innovation. Giving every employee a second monitor lifts output per hour without making the firm any smarter about how it operates.
That distinction is central to the AI debate. Hundreds of billions of dollars are flowing into data centers, chips and model training, and that capital deepening should mechanically lift output per hour. The harder question is whether AI is also raising TFP, meaning whether it is making the economy fundamentally more efficient.
So far, the data says no. The chart below shows utilization-adjusted TFP from the San Francisco Fed, and it is currently sitting slightly below zero with no sign of acceleration since the AI capex cycle began. Output per hour, by contrast, is running near 2.5%, comfortably above its post-2005 average, and that strength is exactly what gets cited as evidence that AI is already working. But strong output per hour alongside flat TFP is the signature of capital deepening, not of a technology shock.
TFP has swung between roughly -3% and +4% over the past 40 years with no discernible trend, so the current sub-zero reading is not in itself unusual. Electricity and IT both took a decade or more to show up in aggregate numbers.
The bottom line is that the AI boom is clearly visible in investment data and in equity valuations, but it is not yet visible in the productivity statistics, which means the productivity payoff from AI remains a forecast rather than an observation.
Note: Total Factor Productivity (TFP) is the utilization-adjusted series from the San Francisco Fed (Fernald, 2014), adjusted for cyclical variation in factor utilization. Sources: Federal Reserve Bank of San Francisco, US Bureau of Labor Statistics, Apollo Chief Economist
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