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TL;DR
Apollo economist Torsten Slok says aggregate data show no clear financial payoff from AI for corporate America outside the technology sector. The claim is based on trends in worker revenue, margins and productivity—not a direct measurement of AI’s effect—and company-specific experiments show gains in some tasks. At the same time, infrastructure commitments and borrowing are expanding, raising questions about who will earn enough from AI to cover the cost.
Apollo chief economist Torsten Slok said an October analysis found no visible financial payoff from AI across corporate America outside technology, even as companies make large commitments to data centers, servers and computing capacity. The claim describes broad economic indicators rather than a direct test of AI’s effect, and evidence from individual workplaces shows gains in some tasks.
Apollo’s October 24 note compared revenue per worker and profit margins at the seven largest technology companies with the other 493 companies in the S&P 500. Its charts show revenue per worker and margins rising for the seven, while the figures for the other companies remain broadly flat. The note also cited San Francisco Federal Reserve productivity measures, which it said show no sign yet of an AI-driven increase in productivity growth.
That finding is not the same as proving that AI has produced no benefit. A flat average can conceal companies or business functions that gained or lost, and the figures do not isolate AI from other influences such as labor costs, interest rates or tariffs. Apollo’s Ramp spending data also cover Ramp’s business customers, not the S&P 500 as a whole. Slok’s conclusion that AI has delivered “zero financial payoff” is an interpretation of these aggregate trends.
The scale of investment is clearer in corporate filings. Meta reported $34.91 billion in capital expenditures in the third quarter and narrowed its 2026 capital spending forecast to $135 billion to $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. Meta’s October 22 filing listed about $825 billion in future commitments, including leases and contracts for capacity and equipment; the total is not all AI-related and extends over several 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.
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The Cost of Building AI Capacity
The gap between capital going into AI infrastructure and documented returns is relevant to investors, companies and customers. Firms investing in computing capacity need revenue, cost savings or productivity growth to justify the expense. If returns are concentrated among technology companies and a limited number of heavy AI users, the benefits and financial risks could be unevenly distributed across the economy.
The financing picture is also part of the debate. The source report says SpaceX borrowed $40 billion to buy AI chips and cites rising insurance costs for debt issued by Meta and CoreWeave. These details raise questions about how infrastructure plans will be funded, but do not establish that the companies cannot meet their obligations or that the investments will fail.
Task-level results provide additional context for Apollo’s economy-wide assessment. The report cites a customer-support study in which workers resolved 14% more issues per hour, with a 34% gain for novice workers. It also describes retail experiments with sales changes ranging from zero to 16.3%, depending on the workflow. These examples show variation across applications; they do not establish a comparable gain across companies or the economy.
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What Apollo’s Aggregate Measures Show
Apollo’s note, titled “No Signs of AI Payoff Outside the Tech Sector,” drew on five charts. It compared the Magnificent Seven—Alphabet, Amazon, Apple, Meta, Microsoft, Nvidia and Tesla—with the rest of the S&P 500, examined productivity indicators and used Ramp data to show that AI spending is concentrated among a small share of businesses. According to the report, the top 10% of firms account for most spending on model inference, neocloud services and OpenAI and Anthropic services among Ramp customers.
The concentration figures describe spending within Ramp’s customer base, which the source says includes more than 85,000 U.S. businesses. They should not be treated as a census of all companies. The report also says 80.4% of the top 1% of AI spenders are venture-backed, compared with 13.1% of the median spender, raising a question about how much current demand comes from companies financed to grow quickly.
Meta’s commitments include roughly $355.73 billion in leases not yet started and $454.52 billion in non-cancelable contractual commitments, according to its filing, with additional contingent purchases possible. The figures cover obligations extending into the future and include items beyond AI. Separately, projections cited by Investing.com put capital spending by Amazon, Alphabet, Meta, Microsoft and Oracle near $780 billion in 2026; those are forecasts, not filed commitments.
““No Signs of AI Payoff Outside the Tech Sector.””
— Torsten Slok, Apollo chief economist, in the October 24 Daily Spark note
Apollo’s figures do not establish how much of the observed corporate performance is caused by AI. Aggregate revenue and margin measures can mask differences between firms, while productivity statistics may not capture benefits that are still developing or limited to particular tasks. The source material does not provide a common, economy-wide accounting of AI costs and returns.
It is also unclear whether reported task-level gains will translate into lasting improvements in company-wide productivity, profits or wages. The customer-support and retail examples cover specific settings, and their results vary. The source’s reported survey finding that 83% of nearly 9,000 executives saw no productivity impact so far is a measure of what respondents reported, not proof that AI had no effect in every workplace.
Meta’s commitment total is not the same as money already spent: it combines future leases and contractual obligations, some of which relate to non-AI operations. The company’s negative free cash flow in the third quarter is a single-period figure, and the cited forecasts for other large technology companies are not commitments. The full pace of spending, its financing and eventual returns remain unsettled.
Returns Will Be Tested Over Time
The next evidence will come from company filings and subsequent productivity data, including whether large technology firms sustain investment plans and whether measurable returns appear beyond the technology sector. Meta’s future spending and cash-flow disclosures will help clarify how its commitments translate into actual outlays; the source material does not provide a specific next reporting date or a confirmed timetable for those commitments.
Investors and businesses will also be watching whether AI applications move from isolated workflow improvements to results visible in company-wide revenue, margins or output per hour. Until comparable data show that change, Apollo’s conclusion remains a reading of current aggregate indicators—not a final verdict on the long-term value of AI investment.
Key Questions
What does Apollo mean by “zero financial payoff”?
It is Torsten Slok’s interpretation of aggregate trends: revenue per worker and profit margins are rising for the seven largest technology companies but broadly flat for the other 493 S&P 500 companies. It is not a direct measurement proving that every non-tech company has received no benefit from AI.
Has AI improved productivity in any workplaces?
The source report cites task-level examples, including 14% more customer-support issues resolved per hour in one study and retail sales results ranging from zero to 16.3% across experiments. Those examples do not establish an economy-wide productivity gain.
What is included in Meta’s roughly $825 billion figure?
Meta’s filing lists about $355.73 billion in leases not yet started and $454.52 billion in non-cancelable contractual commitments, plus possible contingent purchases. The total is a figure for future commitments, not spending already paid, and it includes obligations that are not all AI-related.
Why are economists questioning the AI spending boom?
Companies are committing large sums to data centers, servers, chips and cloud capacity, while broad measures have not yet shown a clear productivity lift outside technology. The central question is whether future savings or revenue will justify those costs; current aggregate evidence does not settle it.
Source: ThorstenMeyerAI.com
