Sam Altman Warns Rising AI Costs Are Squeezing Big Companies: CEOs Struggle to See Revenue Despite Massive Spending

Sam Altman warns rising AI costs are squeezing big companies as CEOs report spending “going up and up” without clear revenue returns. OpenAI CEO addresses “most fair criticism” of AI: massive capex on infrastructure, chips, software with uncertain ROI, widespread waste, and hoarding of underused computing resources.

Sam Altman warns rising AI costs are squeezing big companies, revealing that CEOs are increasingly frustrated as AI spending “is going up and up” without seeing clear revenue returns or measurable productivity gains.

Speaking during multiple recent interviews, the OpenAI CEO has acknowledged this is the “most fair criticism right now of AI”—companies are pouring billions into AI infrastructure, chips, and software while struggling to see meaningful financial returns.

The Core Problem: Spending vs. Returns

What CEOs Are Telling Altman

According to Altman, the most common feedback he receives from companies investing heavily in AI centers on:

CEO Complaint	Reality Check
“Spending is going up and up”	AI costs rising faster than returns
“Where is the revenue?”	No clear financial returns despite heavy investment
“Tons of waste everywhere”	Companies paying for more computing power than they use
“How long until ROI?”	Wait time for revenue uncertain and prolonged

During a live interview with Matt Comyn at a Commonwealth Bank AI event, Altman revealed that one question continues to dominate conversations with business leaders: “Where is the revenue?”

The Scale of AI Spending

Massive Investment Without Clear ROI

Big Tech companies are investing staggering amounts in AI infrastructure:

Microsoft, Meta, Amazon, and Google are projected to spend $320 billion this year on AI development

Companies are pouring billions into infrastructure, chips, and software

Cloud optimization platform Cast AI reports many companies are paying for far more AI computing power than they actually use

The Hoarding Problem

Recent data reveals a troubling trend:

Companies are hoarding scarce AI chips simply because they fear missing out (FOMO), not because they have immediate needs

This has resulted in a growing stockpile of underused computing resources

Laurent Gil, Cast AI cofounder and president, said companies are not using the computing power they’ve purchased

Altman’s Concession: “The Most Fair Criticism”

What Altman Said on CNBC

During a CNBC interview on Monday, the OpenAI CEO made a surprising admission:

“So I think this is the most fair criticism right now of AI. You hear companies saying, ‘I am spending a ton of money on AI. And I know some great stuff is happening, but I know there’s a ton of waste.'”

Altman went on to summarize the core concerns:

“How long do I have to wait for it to really show up in revenue, and how long do I have to wait to really get the costs under control? I assume that the industry will figure that out pretty quickly, but I think that is a fair, a fair issue.”

This is a significant acknowledgment from Altman, who has previously been one of AI’s most enthusiastic advocates.

The Productivity vs. Revenue Gap

Employees More Productive, But Revenue Not Growing

Altman revealed a paradox:

Company employees are becoming more productive with AI tools

Yet executives struggle to see meaningful revenue growth

Measurable productivity gains remain elusive despite employees using AI

This suggests that while AI is helping individuals work better, it’s not yet translating to broader economic growth or company-level financial improvements.

Technology vs. Economics

Despite rapid advances in large language models and AI assistants, Altman noted:

Promised Outcome	Reality
Broad economic growth	Taking longer than predicted
Measurable efficiency gains	Difficult to translate tech breakthroughs
Revenue from AI productivity	Not appearing at expected scale

“Translating those technological breakthroughs into broad economic growth has proven more difficult than anticipated.”

Earlier Warnings: AI Bubble Concerns

Altman’s Previous Comments on AI Bubble

This is not the first time Altman has expressed caution about AI investment:

August 2025: Altman said the AI market may be in a bubble, comparing it to the dotcom boom of the late 1990s
October 2025: He warned investors are becoming “overenthusiastic” even as Big Tech spends $320 billion
Quote: “When bubbles occur, intelligent individuals can become overly excited about a fragment of reality.”

Yet Altman also noted:

“Is AI the most significant development we’ve seen in long time? I also think that’s true.”

He believes AI has substantial long-term potential, even if some investors may face losses as excitement diminishes.

The Economic Reality: AI Services Are Expensive

Higher Costs Than Traditional Internet Services

In a Forbes interview, Altman highlighted a less-discussed aspect of AI expansion:

Delivering AI services is more expensive than traditional internet services
Companies need to find ways to make markets financially viable at scale
Even if AI becomes cheaper per task, the sheer scale of usage could drive up total global energy consumption

AI Cheaper Than Human Labor

Paradoxically, Altman also told Forbes:

“AI is becoming cheaper than human labor for intellectual tasks.”

Key points:

AI is already more energy-efficient than human work at inference stage
Cost of running AI models significantly lower than human intellectual work energy consumption
Per-unit basis: AI systems are highly efficient and improving
Bigger picture: Large-scale usage drives up total costs

Industry Response and Trends

Companies Cutting Spending

Forbes reports that AI costs are rising faster than returns, pushing:

Big Tech to cut spending
Startups to reduce investment
Model providers to scale back
New risks for margins across the industry

Altman Softens Job Warning

In a CNBC interview on Monday (June 2, 2026), Altman also softened his earlier warnings about AI eliminating jobs:

“The companies that I know that have adopted AI the most are also the ones hiring the most. The companies, as a general rule, that are talking about doing layoffs because of AI are the ones adopting AI the least.”

This suggests companies using AI aggressively are expanding their workforce, not reducing it.

When Will Altman Be More Concerned?

Despite current concerns, Altman said he would become more concerned only if companies are still asking the same questions a year from now.

This implies he believes:

The industry will figure out cost control quickly
Revenue will eventually materialize
Current concerns are transitional, not permanent

The Bottom Line

Sam Altman warns rising AI costs are squeezing big companies represents a significant moment of honesty from one of AI’s most vocal advocates. The OpenAI CEO acknowledges that:

Massive spending ($320B+) is happening without clear returns
Waste is widespread—companies hoarding unused computing power
Productivity gains aren’t translating to revenue
The ROI timeline is uncertain
This is the “most fair criticism” of AI right now

While Altman still believes in AI’s long-term potential, the short-term economics are challenging, and companies are rightfully asking: “Where is the revenue?”

The question now is whether the industry can figure out cost control and revenue generation before investor patience runs out—or if we’re witnessing the early stages of an AI bubble burst.