🔍 Read the full analysis: An Economist On Why AI Returns Remain Scarce Outside Tech on ThorstenMeyerAI.com
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TL;DR
Apollo chief economist Torsten Slok’s October 24 note finds revenue per worker and profit margins rising among seven major technology companies while remaining broadly flat across the other 493 S&P 500 firms. The comparison does not prove AI caused the gap or that every non-tech company has seen no benefit; research cited in the source shows measurable gains in some specific tasks, while broad productivity effects remain unclear.
Apollo chief economist Torsten Slok says recent company and productivity data show no broad financial payoff from AI outside technology, even as businesses commit large sums to computing infrastructure. His October 24 analysis compares revenue per worker and profit margins at seven major technology companies with those at the other 493 S&P 500 firms; it documents a gap, but does not establish that AI alone caused it.
Apollo’s charts show inflation-adjusted revenue per worker rising among the “Magnificent 7” — Alphabet, Amazon, Apple, Meta, Microsoft, Nvidia and Tesla — while the measure for the other 493 S&P 500 companies has remained broadly flat. The source’s reading of the chart puts the seven near $780,000 per employee in the third quarter of 2026, compared with about $525,000 for the other companies. It also shows margins near 30% for the seven and around 10% for the rest.
The analysis points to San Francisco Federal Reserve productivity measures that, according to Apollo, show no visible AI-related lift in productivity growth so far. It also cites Ramp spending data from more than 85,000 U.S. business customers: the top 10% of firms account for 99.5% of spending on model serving and inference, 99.0% of neocloud spending and 95.6% of spending on OpenAI and Anthropic. Those figures describe Ramp’s customers, not the S&P 500 as a whole.
The investment behind the debate is substantial. Meta’s third-quarter release reported $34.91 billion in capital expenditures and negative free cash flow of $2.12 billion, compared with positive free cash flow of $10.6 billion a year earlier. Its filing lists roughly $355.73 billion in leases not yet started and $454.52 billion in non-cancelable contractual commitments, plus up to $14.72 billion in contingent cloud purchases. The source says these commitments total about $825 billion, though they include items not exclusively tied to AI.
Infographic 01 · The “zero” in numbers
What “zero financial payoff” actually measures.
Apollo’s headline rests on five charts. Here are their numbers, and what they can and cannot prove.
Who pays for AI? Share of spending by the top 10% of firms
Ramp customer data via Apollo · non-AI categories in grey for comparison
Spending is concentrated in every category, not only AI; AI is the most extreme.
What the five charts do and do not show
shown not shown
- Shown: revenue per worker and margins rising for the 7 tech giants, flat for the other 493
- Shown: no AI lift yet in US productivity statistics (San Francisco Fed TFP, output per hour)
- Shown: AI spending sits in few, mostly venture-funded firms (Ramp, 85,000+ US businesses)
- Not shown: that AI caused the gap; rates, tariffs and wages move the same lines
- Not shown: gains inside single functions, which can cancel out in an average
- Not shown: the S&P 493 itself in the Ramp data; those are Ramp’s customers
“The AI story will be decided in the S&P 493, not the Mag 7.”Torsten Slok, Apollo chief economist, 24 Oct 2026 (opinion)
Sources: Apollo Daily Spark (24 Oct 2026) with charts by Bloomberg, Macrobond, SF Fed, BLS and Ramp; Apollo (20 Oct 2026); Ramp AI Index. Values with ≈ are read off Apollo’s charts. Assessment: Thorsten Meyer.
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The Gap Between AI Spending and Returns
The contrast matters because companies are making large, long-term investments in data centers, servers and cloud capacity before broad gains appear in conventional measures of productivity or corporate performance. If returns remain concentrated among technology firms and a small group of heavy AI users, investors and business leaders may question whether current spending will generate enough revenue or cost savings to justify its scale.
That is a concern, not a settled verdict. A company can gain from faster service, improved decisions or reduced workload without those benefits appearing immediately in revenue per employee or aggregate productivity statistics. The source cites customer-support research showing 14% more issues resolved per hour, rising to 34% for novice workers, and retail experiments with sales changes ranging from zero to 16.3%, depending on the workflow. These examples suggest that returns can be real but uneven and tied to particular uses.
The source also reports that 83% of nearly 9,000 executives said AI had not yet affected their productivity, with an estimated average effect of 0.2% a year. The survey and the task-level studies measure different things, so they do not cancel each other out. Together, they point to a gap between localized improvements and a measurable economy-wide impact.
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What Apollo’s Comparison Measures
Slok’s October 24 “Daily Spark” note, titled “No Signs of AI Payoff Outside the Tech Sector,” drew attention to differences between the seven largest technology companies and other S&P 500 firms. Apollo’s measures describe company-level outcomes and broader productivity indicators; they do not isolate the effect of AI from other forces, such as labor costs, interest rates or tariffs.
Slok argued in a separate October 20 note that a core risk for the AI investment case is that the marginal cost of compute may exceed the benefit users receive. He also described venture-backed spending on AI services as circular. Those are his economic interpretations, not findings that the supplied data independently prove. The source says 80.4% of the top 1% of AI spenders in Ramp’s data are venture-backed, compared with 13.1% of the median spender.
Meanwhile, capital spending plans continue to expand. Meta narrowed its 2026 spending outlook to $135 billion to $145 billion. The source also cites forecasts that five major technology spenders — Amazon, Alphabet, Meta, Microsoft and Oracle — could spend almost $780 billion in 2026 and more than $1 trillion annually from 2027 through 2030. Those figures are projections, not reported spending or binding commitments.
“No Signs of AI Payoff Outside the Tech Sector”
— Torsten Slok, Apollo chief economist, in the October 24 Daily Spark note
What the Data Cannot Establish
Apollo’s comparison does not show that AI caused the performance gap between the seven technology companies and the other 493 S&P 500 firms. The groups differ in business models and market positions, and a flat average can conceal companies whose gains and losses offset one another. The source also notes that Ramp’s spending data represent its own customer base rather than all U.S. businesses.
It is also unclear how much of Meta’s roughly $825 billion in future commitments will ultimately be used, when the costs will be recognized, or what share is directly attributable to AI. The total includes leases, cloud and equipment contracts, and some non-AI items, including Reality Labs hardware. Commitments should not be treated as equivalent to cash already spent.
Finally, the cited task-level examples do not establish how common those gains are across industries or whether they persist over time. The source does not provide enough detail on the studies’ methods to compare their results directly with Apollo’s economy-wide measures. The broad return on AI investment remains an open question.
Evidence to Watch in Future Results
The next useful evidence will come from company reports showing whether AI-related investment translates into sustained revenue growth, lower costs or improved output per worker. Meta’s forthcoming financial results and updates to its capital spending plans will help clarify how spending and cash generation develop, but a single quarter will not establish an economy-wide trend.
Investors and policymakers will also be watching productivity measures over time and research that tracks specific AI deployments against comparable workflows. For now, the confirmed picture is mixed: infrastructure spending is large, Apollo’s broad indicators show little visible payoff outside major technology companies, and some targeted uses have reported task-level improvements. Whether those gains spread widely enough to justify the investment remains to be seen.
Key Questions
What did Apollo’s economist conclude about AI returns?
Torsten Slok’s October 24 note said broad financial returns were not visible outside major technology companies in the measures he reviewed. The comparison is about aggregate indicators, not proof that every non-tech company has received no benefit.
Does Apollo prove that AI caused the gap between tech firms and other companies?
No. The charts show differences in revenue per worker and margins, but they do not isolate AI’s effect from other factors or establish causation.
What does Meta’s roughly $825 billion figure represent?
It is a total of reported future leases and contractual commitments, plus contingent cloud purchases, according to the source. It is not all AI spending or cash already paid; some commitments relate to other activities and may be paid over time.
Are there examples of AI producing measurable gains?
Yes. The source cites customer-support research reporting 14% more issues resolved per hour, with a larger result for novice workers, and retail experiments with sales effects ranging from zero to 16.3%. Those findings apply to particular tasks and workflows, not every company.
Source: ThorstenMeyerAI.com
