Month: November 2025

• Consumers can’t get enough of AI, but businesses are still trying to figure it out, Goldman Sachs analysts say.
• Investors are questioning whether the AI spending frenzy has raced ahead of real returns.
• McKinsey finds most companies talk up AI, but few are seeing it actually pay off.

Artificial intelligence may be transforming how consumers use technology, but the revolution is still lagging when it comes to businesses, according to a pair of Goldman Sachs analysts.

“A lot of consumer applications, they’re exemplifying the value of AI, whether it’s ChatGPT or Claude application at the consumer level. But at the enterprise level and user level, there are some signs of life, but we’re not where we expected,” said Kash Rangan, a US software equity research analyst, on Goldman Sachs’ “Exchanges” podcast published on Tuesday.

While tools like ChatGPT have rapidly captured consumer attention, corporate adoption has been slower.

Rangan said companies are “well below” where he thought they would be in AI adoption.

“It’s not where we expected it to be a year ago, two years ago, but rather to where we were six months ago, nine months ago,” he said.

Eric Sheridan, a US internet equity research analyst, said the AI infrastructure buildout has “surprised to the upside.” That surge, he added, reflects how demand for computing power from generative models such as ChatGPT and Google Gemini has already outpaced available capacity.

High spending has left some investors questioning whether the returns will ever match the outlay. Sheridan said the rapid rise in AI infrastructure investment has created growing doubts about the long-term return on investment, even as spending keeps accelerating.

Sheridan pointed to Nvidia’s forecast of $3 trillion to $4 trillion in cumulative AI infrastructure spending by the end of the decade.

“I think most investors we talk to would struggle to justify the return profile on 3 to 4 trillion of cumulative spend, unless AI is the main driving factor in an enormous amount of the economic output of society in some sort of end state,” he said.

The Goldman analysts’ comments come amid investor jitters over the scale of AI spending that has pushed the S&P 500 and Nasdaq to record highs in recent weeks. Stocks pulled back last week on concerns that markets may have run ahead of fundamentals.

That gap between excitement and execution echoes what consultants at McKinsey are seeing.

In its State of AI 2025 report, released last week, McKinsey found that while nearly 88% of companies report using AI in at least one business function, only about a third have scaled it across the entire enterprise.

In its survey of nearly 2,000 companies across industries, 64% said that AI is enabling their innovation. However, 39% reported AI’s impact showing up in the bottom line.

“While AI tools are now commonplace, most organizations have not yet embedded them deeply enough into their workflows and processes to realize material enterprise-level benefits,” wrote McKinsey’s consultants.

• Eric Schmidt warned that most countries may adopt Chinese open-source AI models.
• It comes down to the cost: open-source models are free.
• Tech execs are urging nations to build sovereign AI systems to avoid dependency on other countries.

Google’s former CEO said he worries that most countries could end up using Chinese AI models because of the cost.

“This produces a bizarre outcome where the biggest models in the United States are closed source and the biggest models in China are open-source,” Eric Schmidt said in an episode of the “Moonshots” podcast released on Tuesday. “The geopolitical issue there, of course, is that open source is free and the closed source models are not free.”

Open-source AI models allow for the free and open sharing of software to anyone, for any purpose.

“So the vast majority of governments and countries who don’t have the kind of money that the West does will end up standardizing on Chinese models not because they’re better, but because they’re free,” Schmidt said.

Those who support open source say it allows technology to develop rapidly and democratically, as anyone can modify and redistribute the code. On the other hand, advocates for closed-source models argue that they’re more secure because the code is kept private.

This year’s popularity of Chinese models like DeepSeek and Alibaba’s Qwen3 has raised concerns about data privacy, national security, and America’s competitive advantage.

Schmidt was Google’s CEO from 2001 to 2015 and led the company through its 2004 initial public offering. He is now a founding partner at venture capital firm Innovation Endeavours and runs an aviation startup called Relativity Space. He has a net worth of nearly $50 billion, per Bloomberg.

“Sovereign AI,” which refers to a country’s control and governance of AI technologies, data, and infrastructure, has been gaining attention in tech and political circles.

Executives, including Nvidia chief Jensen Huang and the CEO of French AI startup Mistral, Arthur Mensch, have said that it is important for countries to build independent AI systems.

In a March podcast appearance, Mensch compared AI to electricity in the 1900s and said that nations that don’t set up their own AI systems risk money flowing to other countries.

“100 years ago, if you weren’t building electricity factories, you were preparing yourself to buy it from your neighbors, which, at the end of the day, isn’t great because it creates some dependencies.”

In February, Huang told government officials at the World Governments Summit in Dubai that countries needed to work toward building sovereign AI.

He said that if he led a developing nation, “the first thing that I would do, of course, is I would codify the language, the data of your culture into your own large language model.”

Like Schmidt, Huang and Mensch are proponents of open source models.