🔍 Read the full analysis: Why AI’s Benefits Are Still Concentrated In Tech on ThorstenMeyerAI.com
Get business pricing on office and shipping supplies
- Business-only prices and quantity discounts
- Tax-exempt purchasing
- Multiple users, one account, clear invoices
TL;DR
Apollo chief economist Torsten Slok says company-wide data show no clear financial payoff from AI outside the technology sector, with revenue per worker and margins rising among seven major tech firms but largely flat across the other 493 S&P 500 companies. The finding describes broad averages, not proof that AI produces no returns; studies cited in the source report gains in some customer-support and retail tasks, while infrastructure spending and financing needs continue to grow.
Apollo chief economist Torsten Slok says recent company and productivity data show no visible aggregate financial payoff from AI outside the technology sector, even as companies commit vast sums to computing infrastructure. His October 24 note compares seven major technology companies with the other 493 firms in the S&P 500, finding rising revenue per worker and profit margins for the first group but little movement for the rest. The finding is a reading of broad trends, not proof that AI has produced no gains in individual businesses or tasks.
Apollo’s analysis, titled “No Signs of AI Payoff Outside the Tech Sector,” draws on five charts. It reports that inflation-adjusted revenue per worker has risen for the “Magnificent 7”—Alphabet, Amazon, Apple, Meta, Microsoft, Nvidia and Tesla—while remaining broadly flat for the other 493 S&P 500 companies. The chart puts the seven near $780,000 per employee in the third quarter of 2026 and the other companies around $525,000. Apollo also shows margins near 30% for the seven and around 10% for the remaining firms.
The note cites San Francisco Federal Reserve productivity measures that, according to Apollo’s reading, show no signs yet of AI lifting productivity growth. It also uses spending data from Ramp, a corporate-card and spend platform with more than 85,000 U.S. business customers. In that dataset, 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 customers, not the entire U.S. economy.
The spending commitments are visible in company disclosures. Meta reported $34.91 billion in capital expenditures in the third quarter and narrowed its 2026 capital-spending outlook to $135 billion–$145 billion. Its operating cash flow was $32.79 billion, leaving free cash flow at negative $2.12 billion for the quarter, compared with positive $10.6 billion a year earlier. In its October 22 filing, Meta listed about $825 billion in future commitments, including leases not yet started and contractual purchases. The figure is not all AI-related, and it covers obligations extending over multiple years.
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.
Powered by Thorsten Meyer AI
The Gap Between AI Costs and Returns
The divide matters because investment decisions are being made before broad financial returns are clear. Technology companies are spending heavily on data centers, servers and cloud capacity, while many businesses adopting AI have yet to show that it raises total revenue, lowers costs or improves productivity enough to offset the expense. For investors, the difference between infrastructure spending and realized returns is a key risk in judging the sector’s prospects.
It also affects companies outside technology that are deciding whether and how quickly to adopt AI. A weak aggregate result does not mean every deployment fails, but it does suggest that purchasing access to AI tools alone may not translate into stronger company-wide performance. The evidence cited in the source points to better results where AI is applied to a defined workflow and outcomes can be measured.
Some task-level studies report gains: one customer-support study found 14% more issues resolved per hour, rising to 34% for novice workers. Retail experiments cited in the source range from no sales increase to a 16.3% increase, depending on the workflow. Those results concern particular settings and should not be treated as proof of broad gains across businesses.
AI workstation GPU for machine learning
As an affiliate, we earn on qualifying purchases.
As an affiliate, we earn on qualifying purchases.
What Apollo’s Averages Capture
Slok’s use of “zero financial payoff” refers to the lack of a clear effect in broad company-level trends, rather than a controlled estimate isolating AI’s impact. Revenue per worker and margins can be shaped by many forces, including labor costs, interest rates and tariffs. A flat average can also conceal companies whose gains and losses offset each other. Apollo’s charts therefore support the narrower conclusion that an economy-wide payoff is not yet visible in these measures.
The source also reports that 83% of nearly 9,000 executives said AI had no productivity impact so far, with an average reported effect of 0.2% a year. The underlying survey details and definitions are not supplied in the material, so those figures should be read as reported survey results, not as a direct measurement of AI’s contribution to national productivity.
Meanwhile, spending forecasts and contractual commitments describe different things. Meta’s reported commitments cover leases and purchases over time, and some are not exclusively for AI. Estimates that major technology companies may spend almost $780 billion in 2026 and more than $1 trillion a year from 2027 through 2030 are forecasts, not completed spending or booked commitments.
“No Signs of AI Payoff Outside the Tech Sector”
— Torsten Slok, Apollo chief economist, in the October 24 Daily Spark note
What the Aggregate Data Cannot Show
The available evidence does not establish that AI caused the difference between the seven major technology companies and the other S&P 500 firms. It also does not reveal how many companies have gained or lost from AI, or whether early task-level improvements will translate into durable company-wide results. Apollo’s “zero” is an interpretation of aggregate indicators; it is not a direct measurement showing that every non-tech company has earned no return.
The size of Meta’s reported commitments also requires care: the total spans years, includes some non-AI items and is not equivalent to cash already spent. The source says debt-insurance costs rose for Meta and CoreWeave and that SpaceX borrowed $40 billion to buy AI chips, but it does not provide enough detail to establish the terms, broader financing conditions or what those costs mean for each company’s ability to fund future investment. The timing and scale of any widespread productivity gains remain unknown.
Evidence to Watch in Company Results
Upcoming earnings reports and company filings will show whether spending plans are converted into completed infrastructure investment and whether firms can explain how that capacity supports revenue or cost savings. Investors will also be watching free cash flow, capital spending and financing costs, particularly as major technology firms maintain large data-center and computing plans.
For evidence beyond technology companies, the next test is whether productivity and operating results improve across a wider range of industries—not only in selected customer-support or retail workflows. The source material does not provide a scheduled milestone that will settle that question. For now, the confirmed picture is a growing infrastructure bill alongside limited aggregate evidence of returns outside tech.
Key Questions
What does Apollo mean by “zero financial payoff”?
It is Slok’s interpretation of aggregate trends: revenue per worker and margins rose for seven major technology companies but were broadly flat for the other 493 S&P 500 firms. It does not prove that every non-tech company or AI project has had no return.
Does the analysis show that AI has no productivity benefit?
No. Apollo cites productivity measures that show no clear economy-wide boost yet, but the source also describes task-level gains in some customer-support and retail experiments. Those narrower results do not establish broad or lasting gains across the economy.
What is included in Meta’s roughly $825 billion in commitments?
Meta’s filing lists leases not yet started and non-cancelable contractual commitments, including data-center, energy, network, cloud and server-related obligations. The total spans years, and not all of it is AI-related or already spent.
Why are AI gains concentrated in technology companies?
The source points to concentrated AI spending: a small share of Ramp’s business customers account for most spending on model services and neocloud capacity, and many of the top AI spenders are venture-backed. That indicates concentrated investment, but does not by itself explain the full cause of the gap in company results.
What evidence would show that AI is paying off more broadly?
Stronger evidence would include sustained improvements in productivity, revenue or margins across companies outside the technology sector, alongside clear links to AI use. Future company filings and productivity data may help show whether task-level gains are spreading and outweighing investment and operating costs.
Source: ThorstenMeyerAI.com
Halloween Picks
halloween
As an affiliate, we earn on qualifying purchases.
