Apollo chief economist Torsten Slok wrote in The Daily Spark of 24 October 2026 that, despite massive investment, artificial intelligence “has delivered zero financial payoff to corporate America outside of tech.” Slok wrote that “mainstream corporate America is pulling back and starting to view token spending not as a source of growth but as a cost center that weighs on margins.”
The note, titled “No Signs of AI Payoff Outside the Tech Sector,” sets the Magnificent 7 against the other 493 companies in the S&P 500 and ends: “the AI story will be decided in the S&P 493, not the Mag 7.”
This Week In The AI Supercycle · VIDEO
The Business Engineer’s explainer for this week’s issue, 18 to 24 October 2026: the companies selling AI’s parts say they are booked for years, while the companies paying for the build found money dearer. It does not discuss Slok’s note.
Business Pill · COST CENTER
A short explainer of a cost center: a part of the business judged on what it spends, not what it earns. It teaches the general idea only and says nothing about Apollo or Torsten Slok.
The key insight: As we read it, Slok’s note moves the AI question from the sellers to the buyers: Slok’s charts show revenue per worker and profit margins rising for the Magnificent 7 but flat for the other 493, and Slok writes that mainstream companies are starting to treat token spending as a cost center.
Slok’s case rests on three charts. In Slok’s words, “Revenue per worker is rising for the Mag 7 but is flat for the S&P 493,” “Profit margins are rising for the Mag 7 but are flat for the S&P 493,” and “there are still no signs of AI boosting productivity growth.” The charts do not print the values, so this piece does not read numbers off them.
On who is buying, Slok wrote: “VC-backed companies are spending more and more on tokens, but mainstream corporate America does not need the latest model and is unwilling to pay for it.” Slok adds that “as long as agentic AI and token spending are confined to a small part of the economy, the macroeconomic effects of AI will be very limited.”
Slok also sets out a limit on what cheaper models can do: “AI may be a great calculator, but in business, intelligence is mostly judgment.”
Share of spend held by the top 10% of firms in each category, as printed in chart 4 of Apollo’s Daily Spark of 24 October 2026 (Torsten Slok). Rows re-ordered by share.
What Was Posted on X
Apollo chief economist Torsten Slok just published a gloomy report on AI.
imo, other signals Iโm watching donโt really support these.
> Slok says mainstream firms donโt need the latest model and wonโt pay for it, and with no bottom-line gain they now treat token spending as a cost center that weighs on margins.
> He says, total factor productivity growth sits near 0%, and Slok expects AIโs macro effect to stay very limited while agentic AI and token spending remain confined to a small slice of firms.
> Argues cheaper, commoditized models may not close the gap, because per him, businessvalue depends on judgment, accountability, trust and unwritten rules that AI doesnโt understand.
Rohan Paul (@rohanpaul_ai) summarised a new Apollo report by Torsten Slok on 25 Oct: mainstream firms treat token spending as a cost center, total factor productivity growth sits near 0%, and agentic AI and token spending remain confined to a small slice of firms. Rohan Paul added a dissent: “imo, other signals I’m watching don’t really support these.”
Polymarket (@Polymarket) posted on 25 October that its market gives a 9% chance the AI bubble bursts by the end of the year.
The Spending Figures in the Note
Two of Slok’s five charts carry figures. The first is a table titled “AI spending is extremely concentrated in a small number of firms,” which gives the share of spend in each category held by the top 10% of firms:
Spend category
Top 10% of firms
Bottom 90% of firms
Model serving & inference
99.5%
0.5%
Neocloud
99.0%
1.0%
Cloud computing
95.7%
4.3%
OpenAI + Anthropic
95.6%
4.4%
Paid ads
91.9%
8.1%
SaaS excluding AI
91.8%
8.2%
CRM
84.2%
15.8%
Source: Apollo, The Daily Spark, 24 October 2026 (Torsten Slok), chart 4. Rows re-ordered by top-10% share.
The second, titled “Circularity in AI shows up in token spending too,” splits firms by financial backing: among the top 1% of AI spenders, 80.4% are VC-backed and 19.6% are not, against 13.1% VC-backed and 86.9% not for the median spender.
Connecting the Coverage
Our Ramp piece of 23 October reported Ramp’s finding that 1% of firms drive 80% of spend on OpenAI and Anthropic among firms on Ramp, and that Apollo’s 22 October note had already shown the VC-backed split. Slok’s 24 October note carries that split again and adds the revenue-per-worker, margin and productivity charts.
Our collision piece of 24 October set an H100 rent 44% higher than in December, by our arithmetic from Silicon Data, beside token prices about 50% lower year on year in YipitData’s panels. Our Rippling piece reported that Rippling moved most of its coding work to OpenAI as the company sought to cut costs and OpenAI proved cheaper, chief executive Parker Conrad told The Information.
Our TS Lombard piece reported a crash scenario in which equity holders lose about $20 trillion, and our Gates piece set out how China, Japanese employers and Bill Gates frame AI’s effect on jobs.
The Structural Read
As we read it, the spending data in the note point the same way as the charts: in chart 4 the top 10% of firms hold 99.5% of model-serving and inference spend, and in chart 5 80.4% of the top 1% of AI spenders are VC-backed.
As we read it, this sits beside our Rippling piece: Rippling’s chief executive told The Information that the company sought to cut costs and OpenAI proved cheaper.
As we read it, Slok’s test is the S&P 493: Slok writes that so far there is no evidence revenuegrowth or margins are improving outside the tech sector.
Torsten Slok, Apollo, The Daily Spark, 24 October 2026
“the AI story will be decided in the S&P 493, not the Mag 7”
Three Implications
FOR AI SELLERS Slok writes that mainstream corporate America “does not need the latest model and is unwilling to pay for it.”
FOR BUYERS OUTSIDE TECH Slok’s charts show margins rising for the Magnificent 7 but flat for the other 493 companies.
FOR THE CONCENTRATION OF SPEND In the note’s table, the top 10% of firms hold 99.5% of model-serving and inference spend.
The guide puts it this way: “For two years, AI was a CIO line item and a CEO talking point. In 2026 it became a CFO problem, because the economics finally turned legible — and unforgiving.”
As we read it, Slok’s note is that CFO view in macro form: Slok writes that mainstream companies are starting to treat token spending as a cost center that weighs on margins. The guide was published in June 2026 and does not discuss Slok’s note.
What Is Not Established
Slok’s note is an economist’s commentary, not a company disclosure. The note’s revenue-per-worker, margin and productivity charts carry no printed values, and the note does not state the source of its category table; our Ramp piece tied the VC-backed split to Ramp data, as Slok wrote on 22 October. The note does not say how many companies have cut AI spending. We did not contact Apollo.
This Week In The AI Supercycle
Execution Fault Lines, Concentrated Demand, and Geopolitical Firewalls
This week’s issue: the AI build is not short of demand for its parts. It is short of cheap money, and its end revenue rests on a narrow base of large, often venture-funded buyers.
Slok wrote that AI has so far paid off for the Magnificent 7 but not for the other 493 companies in the S&P 500, that mainstream companies are starting to treat token spending as a cost center, and that 80.4% of the top 1% of AI spenders in the data Slok cites are VC-backed.
A note on sourcing. This piece reports Apollo’s Daily Spark of 24 October 2026 by Torsten Slok, read in full, including the values printed in its fourth and fifth charts; its first three charts print no values and none are read off them. Connections draw only on our own earlier pieces and the sources they cite. We did not contact Apollo.
Gennaro Cuofano is a CRO and tech executive who has worked in AI since late 2015, starting with bringing NLP, natural-language generation, voice and chatbot products to the marketing industry. His background is in law and finance: he holds a Master's degree in Law and an International MBA with an emphasis on corporate finance (LUISS Business School and the University of San Diego, 2012), and worked as a financial analyst at a real-estate investment firm in San Diego and as an assistant controller. His work focuses on business model strategy, business engineering and, more broadly, structural analysis: how companies make money, read from their own filings. He created FourWeekMBA and leads research there and at The Business Engineer, his newsletter on AI and business strategy, with over 95,000 subscribers and more than 1,000 published analyses. His writing has also appeared on Entrepreneur (for example, How to Digitize a Family Business in Europe) and HackerNoon. Find him on LinkedIn and Substack. See how we source.
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