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TL;DR
Apollo chief economist Torsten Slok says aggregate data show no visible financial payoff from AI outside the technology sector so far. The claim is an interpretation of broad trends, not proof that AI produces no gains: reported productivity effects vary by task, while spending commitments and financing needs continue to grow.
Apollo’s charts compare the **seven largest technology companies**—Alphabet, Amazon, Apple, Meta, Microsoft, Nvidia and Tesla—with the other **493 S&P 500 companies**. Apollo says inflation-adjusted revenue per worker and profit margins have risen for the seven, while the comparable measures for the other 493 have remained broadly flat. Its chart puts the seven near **$780,000 in revenue per employee** in the third quarter of 2026, versus about $525,000 for the other companies; the note also shows margins near 30% for the seven and around 10% for the rest.
Those figures show a difference between the groups, but do not isolate AI as the cause. Apollo also cited San Francisco Federal Reserve productivity measures that, in its reading, show **no sign yet of an AI-driven increase in productivity growth**. A separate survey of nearly 9,000 executives, cited in the source material, found **83% reported no productivity impact so far**, with the average estimated effect at 0.2% a year. Survey responses and economy-wide productivity statistics measure different things from task-specific trials.
The spending is easier to see in company disclosures. Meta’s October 21 third-quarter release reported **$34.91 billion in capital expenditures** and operating cash flow of $32.79 billion, leaving free cash flow at negative $2.12 billion, compared with positive $10.6 billion a year earlier. Meta forecast **$135 billion to $145 billion in capital spending for 2026**. Its October 22 filing listed about $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 combined figure is roughly $825 billion; the filing includes commitments that are not all AI-related.
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 costs and returns
The gap matters because companies are committing substantial money to data centers, servers and cloud capacity before broad improvements in productivity or margins are showing up in the cited aggregate measures. If returns remain concentrated among technology providers and a small group of heavy users, other businesses may face **higher operating or financing costs without a measurable company-wide payoff**.
That is not proof that the investments will fail. Aggregate averages can conceal firms or departments that benefit, while improvements in a specific workflow may not yet move a whole company’s financial results. Apollo’s analysis is best read as a warning about the lack of visible broad-based returns so far, rather than a finding that AI has no economic value.
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What Apollo’s ‘zero’ measures
Slok’s October 24 note, titled “No Signs of AI Payoff Outside the Tech Sector,” drew attention to a contrast between rising measures at the largest technology companies and largely flat measures across the rest of the S&P 500. Its charts also use Ramp spending data from a platform with more than **85,000 U.S. business customers**. Apollo says the top 10% of firms in that dataset account for 99.5% of model-serving and inference spending, 99.0% of neocloud spending and 95.6% of spending on OpenAI and Anthropic. These figures describe Ramp customers, not all U.S. companies.
The note arrives amid large infrastructure plans. A source cited in the material estimates that five major technology companies—Amazon, Alphabet, Meta, Microsoft and Oracle—could spend nearly **$780 billion in 2026**, with annual spending above $1 trillion from 2027 through 2030. Those are forecasts, not committed outlays. The same source reports that SpaceX borrowed $40 billion to buy AI chips, a sign that financing has become part of the debate alongside access to chips and power.
There is also evidence of narrower gains. The source material cites a customer-support study reporting **14% more issues resolved per hour**, rising to 34% for novice workers. Retail experiments ranged from no sales increase to a 16.3% gain, depending on the workflow. These results do not establish that every deployment will deliver similar outcomes or that gains will translate into higher profits.
““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
Apollo’s comparison cannot determine how much of the gap between technology companies and other S&P 500 firms was caused by AI. Other influences—including labor costs, interest rates and tariffs—may affect revenue per worker and margins. Flat averages can also mask companies that gained and others that did not, and the Ramp spending data represent that platform’s customers rather than the wider business population.
It is also unclear whether large infrastructure commitments will generate returns that match their cost, how quickly any gains may appear in financial statements, or how much of Meta’s listed commitments will ultimately be spent. The reported $825 billion includes non-AI items and obligations extending over multiple years. Estimates of future spending by other technology companies are forecasts, not confirmed commitments.
Companies face a returns test
Investors and companies will be watching upcoming earnings reports for evidence that AI spending is lifting revenue, productivity or margins enough to offset infrastructure and financing costs. Meta’s capital spending outlook and its disclosed commitments make its future cash flow and investment returns a central point of scrutiny. Apollo’s analysis may also be updated as new productivity data and company results become available.
For now, the confirmed picture is uneven: large-scale investment is visible, broad productivity gains are not in the cited data, and some task-level studies report improvements. Whether those gains spread beyond technology firms—and produce durable financial returns—remains open.
Key Questions
What did Apollo conclude about AI returns outside technology?
Apollo chief economist Torsten Slok said broad indicators showed no visible financial payoff outside the technology sector so far. That is an interpretation of aggregate trends, not proof that no individual non-tech company has benefited.
Does Apollo’s analysis prove AI has produced no productivity gains?
No. Apollo cited productivity measures that show no AI-driven boost in broad productivity growth yet, but averages may miss gains in particular companies or tasks. The source material also cites task-level studies with mixed results.
What does Meta’s roughly $825 billion figure include?
It combines about $355.73 billion in leases not yet started, $454.52 billion in non-cancelable contractual commitments and up to $14.72 billion in contingent cloud purchases. The commitments span multiple years and are not all AI-related.
How large were reported gains in specific AI uses?
The source material cites a customer-support study reporting 14% more issues resolved per hour, with a 34% increase for novice workers. Retail experiments ranged from no sales increase to a 16.3% gain, depending on the workflow; those results should not be treated as guaranteed outcomes for other businesses.
Source: ThorstenMeyerAI.com
