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NewsMaterial4 min readDisconfirmAI Editorial

The Big Picture blogger Invictus: IT contribution to US GDP growth reaches 35%, far exceeding the 1990s

Invictus, based on data from the U.S. Bureau of Economic Analysis, compares two expansion periods—1995–1999 and 2024Q4–2026Q3—and finds that the share of GDP growth contributed by information-processing equipment and software rose from approximately 16% to 35%, while contributions from the rest of the economy (excluding IT) fell by about 56%. The author argues this indicates insufficient breadth in growth but explicitly states this is not a prediction of an AI bubble collapse; rather, it points out that the current expansion relies more heavily on a single engine than the 1990s did.

2026-11-01 23:00 GMT+8

The surface data of the U.S. economy appears robust—real GDP continues to expand at an annualized rate of 3.4%, consumers keep spending, and businesses keep investing. But Invictus, the author behind The Big Picture blog, points out in this analysis that a less conspicuous problem is emerging: the share of recent economic growth coming from information-processing equipment and software is unusually large.

Comparing the five-year expansion period from 1995 to 1999 with the most recent eight quarters ending in September 2026 reveals two very different pictures. In the late 1990s, average annualized real GDP growth was approximately 4.17%; over the latest eight quarters, it was only 2.34%. More noteworthy is the composition of growth: investment in information-processing equipment and software contributed an average of 0.68 percentage points to quarterly annualized growth in the late 1990s, rising to 0.81 percentage points over the most recent eight quarters. In absolute terms, the pull from technology investment is actually stronger now, but the proportion is the issue—in the late 1990s, IT and software accounted for about 16% of total growth, whereas this ratio reached 35% during the period from 2024Q4 to 2026Q3.

Invictus uses a simple thought experiment to highlight this shift: subtracting the contribution of IT and software from total growth. In the late 1990s, the rest of the economy contributed approximately 3.49 percentage points of annualized growth after excluding IT; over the most recent eight quarters, this figure was only 1.53 percentage points, a decline of about 56%. He specifically emphasizes that this does not mean the non-IT economy is contracting, but rather that its contribution to total growth is much smaller than it was in the 1990s.

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Other data further corroborates these concerns. Residential investment had a positive contribution to GDP growth in the late 1990s but turned negative over the most recent eight quarters; consumer spending remains an important source of growth, but its contribution is far less significant than before. Invictus uses a metaphor: several legs supporting the chair that is the U.S. economy are wobbling. The economy of the late 1990s had multiple powerful engines running simultaneously, whereas today’s economy relies more heavily on just a few.

Why is AI capital expenditure a core variable? Invictus explains that companies are pouring huge sums into computing power, data centers, networking equipment, and software, anticipating future demand and productivity gains. These expenditures count toward GDP today, but whether they ultimately generate sufficient financial returns is another question. If expected returns are disappointing, businesses may scale back investment—the author believes signs of this have already appeared. A reduction in investment would directly weaken GDP growth and could indirectly affect employment, construction, suppliers, and consumer spending, with economic consequences potentially extending well beyond the technology sector itself.

However, Invictus simultaneously provides important caveats. First, the BEA’s classification covers a scope far broader than artificial intelligence itself; the 35% share does not mean AI contributed 35% of economic growth; these categories capture important components of the entire investment boom surrounding computing infrastructure and software. Second, this counterfactual comparison is not perfect: a significant amount of AI capital expenditure has shifted from other investment areas because it is the current hotspot, and managers tend to chase performance; without the AI investment boom, this capital might have flowed to other industries. Furthermore, the late 1990s were hardly free of speculative bubbles—the dot-com bubble eventually burst, leading to a recession in 2001. Invictus also acknowledges an important distinction between concentrated growth and systemic fragility: American households, banks, and corporations currently may still possess the financial strength to cushion against investment reversals, and U.S. consumer resilience continues to exceed expectations. GDP contribution data alone cannot answer this question.

Invictus’s conclusion is: the issue is not whether the U.S. economy is growing—it is; the issue is whether this growth rests on a sufficiently broad foundation to support the foreseeable future. The data shows that today’s expansion is slower and more concentrated in information-processing equipment and software than the late 1990s. This does not mean a recession is imminent, but it implies that a reversal in technology investment could be particularly disruptive. A healthy economy requires more than one powerful engine, and the data suggests the U.S. has become overly dependent on that single driver of economic expansion.

Sources

  • ritholtz.comThe Big Picture↗
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