🔍 Read the full analysis: Why The AI Spending Boom Hasn’t Spread Its Payoffs on ThorstenMeyerAI.com
Get the latest gadgets delivered free with Prime
- Fast, free delivery on millions of items
- Prime Video, Amazon Music and more included
- Member-only deals all year
TL;DR
A note by Apollo chief economist Torsten Slok says corporate results show no broad financial payoff from AI outside the technology sector so far. The claim reflects aggregate trends, not proof that AI produces no value: studies and experiments cited in the source show gains in some specific workflows, while infrastructure spending and financing commitments continue to grow.
Apollo chief economist Torsten Slok said October 24 that artificial intelligence has delivered “zero financial payoff” to corporate America outside the technology sector, pointing to flat revenue per worker and profit margins among most S&P 500 companies. The assessment comes as infrastructure costs climb: Meta disclosed about $825 billion in future commitments, while the source reports that SpaceX borrowed $40 billion to buy AI chips. The figures capture a growing gap between measurable spending and gains that, for most companies, have not yet appeared in broad financial indicators.
Slok’s argument rests on aggregate comparisons in an Apollo “Daily Spark” note, picked up by media outlets after its publication. Apollo’s charts show revenue per worker rising for the so-called Magnificent Seven — Alphabet, Amazon, Apple, Meta, Microsoft, Nvidia and Tesla — while remaining broadly flat for the other 493 S&P 500 companies. The same charts put the seven companies’ profit margins near 30%, compared with about 10% for the rest. Those comparisons describe company performance; they do not, by themselves, establish that AI caused the difference.
The productivity evidence is also inconclusive. The note cites San Francisco Federal Reserve measures of productivity that show no visible AI-driven lift so far. Separately, it cites a survey in which 83% of nearly 9,000 executives reported no productivity impact from AI to date, with an estimated average effect of 0.2% a year. The source does not provide enough detail here to assess the survey’s methods or how its estimate was calculated, so those figures should be read as reported findings rather than a definitive measure of AI’s economy-wide effect.
Specific uses provide a more mixed picture. The source cites research finding customer-support workers resolved 14% more issues per hour with AI assistance, rising to 34% among novice workers. Retail experiments ranged from no sales increase to a 16.3% increase, depending on the workflow. These results suggest that benefits can be measurable when AI is applied to a defined task, even as broad productivity statistics remain largely unchanged.
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 gap matters to businesses, investors and workers because companies are making large, long-term commitments before broad returns are easy to see. Meta’s third-quarter report showed $34.91 billion in capital expenditures and negative free cash flow of $2.12 billion, compared with positive free cash flow a year earlier. The company reported quarterly revenue of $64.60 billion, up 26%, and narrowed its 2026 capital-spending outlook to $135 billion to $145 billion. Those results do not isolate AI’s contribution, but they show the scale of the investment and the pressure it can place on cash generation.
Slok’s “zero” is best understood as a conclusion about visible aggregate results outside tech, not proof that no company or worker benefits. A flat average across hundreds of businesses can conceal individual gains and losses, and cannot separate AI’s influence from other economic forces such as labor costs, interest rates or tariffs. For executives deciding whether to expand AI use, the practical question is whether a particular deployment improves output or revenue enough to justify its costs. For investors, the question is whether infrastructure spending will eventually produce returns that support its financing.
The cost side is not limited to the equipment already purchased. Large future commitments can tie companies to data centers, energy infrastructure and cloud capacity for years. If demand or returns fall short, those obligations may become a financial burden; if adoption accelerates, they may provide capacity that companies need. The available disclosures do not settle which outcome is more likely.
Products Worth Considering
Apple iPad Air (2025) 13‑inch Wi‑Fi 256 GB – Space Gray (M3 chip)
Apple AirPods Pro 3 Wireless Earbuds with Active Noise Cancellation
Samsung 32-Inch Odyssey OLED G8 (G80SH) 4K Gaming Monitor
As an affiliate, we earn on qualifying purchases.
What Apollo’s Numbers Measure
Meta’s approximately $825 billion in commitments combines several types of obligations reported in its October 22 filing, rather than a single cash bill due immediately. The source describes about $355.73 billion in leases for data centers and related infrastructure that have not yet started, $454.52 billion in non-cancelable contractual commitments, mostly for cloud capacity and equipment, and up to $14.72 billion in contingent cloud purchases. Some commitments extend through 2036, and the total is not all AI spending; the source says Reality Labs hardware is included. The company’s filing, rather than the headline total alone, is needed to understand timing and categories.
Apollo also cites Ramp data on corporate spending. Among Ramp’s more than 85,000 U.S. business customers, the top 10% accounted 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 indicate concentrated spending within Ramp’s customer base; they are not a census of all U.S. companies. The note further reports that 80.4% of the top 1% of AI spenders were venture-backed, compared with 13.1% of the median spender.
Slok has framed the issue in several notes during October. On October 20, he described the gap between the cost of compute and the benefit it delivers to users as a central weakness in the AI investment case. On October 22, he called venture-funded token spending “circularity.” These are his economic interpretations, not established findings that apply to every AI product or company. The article’s central distinction is between large, documented spending and financial gains that remain difficult to identify across the wider economy.
“AI has delivered zero financial payoff to corporate America outside of tech.”
— Torsten Slok, Apollo chief economist, in the October 24 Daily Spark note
What the Aggregate Data Cannot Show
The evidence cited does not establish that AI caused the performance gap between the largest technology companies and other S&P 500 firms. It also does not show how many companies have successful uses that are offset by unsuccessful projects. The “zero payoff” wording is Slok’s interpretation of broad indicators, not a finding that every deployment has no financial value.
Other limits apply. Ramp’s spending data represent its own customers, not all businesses, and the source gives no basis for treating its concentration figures as economy-wide. The executive survey’s reported results do not, in the material provided, explain its full methodology. The cited productivity measures likewise cannot alone identify the cause of changes or the absence of changes. AI’s contribution remains hard to isolate from other business and economic conditions.
The financing outlook is also unsettled. The source reports rising insurance costs for debt tied to Meta and CoreWeave and describes growing investor attention to funding, but does not provide full details on the contracts, rates or terms behind those costs. Spending projections for major technology companies are forecasts, not contractual commitments. It remains unclear whether current infrastructure demand will translate into enough durable revenue and productivity gains to justify the outlays.
Returns Will Be Tested in Results
The next evidence will come from company disclosures showing whether AI-related revenue, costs and productivity change over time. Investors are likely to watch capital-spending plans, free cash flow and borrowing conditions alongside reports of new AI products and customer demand. Meta’s commitments span years, so the full financial effect will not be visible in a single quarter.
For companies adopting AI, the clearest near-term test is likely to be task-level performance: whether a system improves output, service speed or sales enough to outweigh model, infrastructure and staff costs. The cited customer-support and retail results point to potential gains in defined workflows, but they do not establish that the same results will carry across industries. For now, spending is easier to count than economy-wide returns, and subsequent company results and productivity data will determine whether that gap narrows.
Key Questions
What does Apollo mean by “zero financial payoff”?
Apollo chief economist Torsten Slok uses the phrase for the lack of visible improvement in broad financial indicators for companies outside the largest technology firms. It is an interpretation of aggregate trends, not proof that no individual company has benefited from AI.
Has AI improved productivity?
The source says broad productivity measures have not yet shown a clear AI-related boost. It also cites task-specific results, including 14% more customer-support issues resolved per hour in one study, showing that gains may appear in particular workflows before they are visible in economy-wide data.
Does Meta owe $825 billion immediately?
No. The reported total combines leases and contractual commitments with different timelines, including obligations extending through 2036. It is not a single bill due now, and the source says some of the commitments are not specifically AI-related.
Why are companies spending so much if returns are unclear?
Companies are building or reserving computing capacity, including data centers, servers and cloud services, in anticipation of demand for AI. The source documents large commitments but does not establish whether future returns will be sufficient to justify them. The investment case remains unproven at broad scale.
Source: ThorstenMeyerAI.com
