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Data Joins Land, Labor and Capital as Tech Spending Hits 55% and GDP Gains Momentum

Tech capital spending hits 55% as data becomes a production factor, while Q2 GDP rises to 3.7%.

Elena Voss/3 min/US

Business & Markets Editor

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Data Joins Land, Labor and Capital as Tech Spending Hits 55% and GDP Gains Momentum
Source: StlouisfedOriginal source

TL;DR: Nominal capital spending in high‑tech has surged to a record 55%, and Q2 real GDP is tracking at 3.7%, underscoring data’s emergence as a fourth factor of production.

Context Economists have long focused on land, labor and capital to explain output. The rapid decline in data‑processing costs since the 1960s has turned data into a virtually unlimited input. Artificial‑intelligence tools now extract value from massive data sets, reshaping how firms allocate resources.

Key Facts - Nominal capital spending in high‑tech rose from roughly 20% to 55% over the past decades, the highest share on record. - Real GDP for the second quarter is growing at an annualized 3.7%, well above the long‑run average. - Information‑technology (IT) stocks in the S&P 400 and S&P 600 have outperformed the S&P 500 IT sector this year, reflecting stronger demand among mid‑cap firms.

What It Means The shift toward data‑driven production is forcing firms to invest heavily in compute and memory hardware. More data means higher storage needs, driving demand for semiconductor and memory chips. Mid‑cap companies, which often specialize in niche AI applications, are capturing a larger share of the market, as shown by their IT sector outperformance.

Higher tech spending boosts productivity, feeding back into GDP growth. The 3.7% Q2 rate suggests the economy is absorbing the new data‑centric investment without major slowdown. If AI continues to lower the cost of turning raw information into actionable insight, the share of capital directed at high‑tech could climb further, reinforcing the data‑capital feedback loop.

Watch for: semiconductor inventory trends, policy shifts affecting AI research funding, and any geopolitical events that could disrupt the global data supply chain.

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