Bloomberg cites updated total factor productivity estimates from the San Francisco Federal Reserve, indicating poor results; in contrast, growth from labor and capital inputs during the internet boom was clearly better. This comparison circulates among macro accounts, juxtaposing the path after the release of ChatGPT with the information technology cycle driven by browsers at that time.

The San Francisco Fed's May 2026 economic letter notes that labor productivity (output per hour) has seen a solid increase in recent years, but total factor productivity, excluding equipment and technology inputs, has only recorded relatively modest growth. As of Q4 2025, the model estimates the probability of being in a high productivity growth state at approximately: 57% for labor productivity and 21% for total factor productivity. Neither is strong enough to conclude that the economy has entered a sustained high productivity regime.

The letter likens the current divergence where labor productivity is outpacing total factor productivity to the early period of the late 1990s information technology boom: at that time, investment was already underway, but official efficiency figures had not fully caught up. The authors write that AI-related investments may enable workers to use better tools through new software and computing power, but broader efficiency gains have yet to materialize. Analysis cites four quarters up to Q2 2026: general total factor productivity increased by about 1.1%, while utilization-adjusted total factor productivity decreased by about 0.44%, with capital inputs growing at an annual rate of about 3.2% during the same period.

Demand-side figures appear ahead of supply-side ones. Tracking by the St. Louis Fed shows that generative AI has entered GDP through investments in hardware, software, R&D, and data centers; by August 2025, about 55% of Americans and 37% of workers had used such tools. Mark Zandi of Moody's Analytics states that the broad technology sector accounts for about 10% of GDP but represents about half of the S&P 500 market value, contributing approximately two-thirds of the stock price increase since the emergence of ChatGPT; growth is more driven by demand-side construction, while productivity has not yet shown a synchronous increase.

Corporate surveys provide a micro-level comparison: AI adoption among typical U.S. companies is widespread but shallow, with most adopters renting upstream intangible capital rather than building it themselves; executives perceive productivity to be higher than measurable gains, with recent net employment impact being small, and layoffs more concentrated in routine clerical positions at large firms, with jobs shifting towards technical roles. The Fed's background paper also states that generative AI has characteristics of a general-purpose technology and "the invention of methods of invention," but diffusion to measurable labor productivity will take a long time.

In market mechanisms, buyers treat capital expenditures as future efficiency from cloud vendors, model labs, and thematic stock funds, while sellers are upstream providers of accelerators, server rooms, and electricity. The event is driven by updates to total factor productivity and comparisons to the internet. Funds flow from software subscriptions, corporate human resource budgets, and venture capital into chips and data centers. Beneficiaries include upstream entities that can bill and valuation accounts, while those measuring whether the macro account has grown using total factor productivity are under pressure.

Source: Public information