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AI experts return from China stunned: The U.S. grid is so weak, the race may already be over

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“Everywhere we went, people treated energy availability as a given,” Rui Ma wrote on X after returning from a recent tour of China’s AI hubs. 

For American AI researchers, that’s almost unimaginable. In the U.S., surging AI demand is colliding with a fragile power grid, the kind of extreme bottleneck that Goldman Sachs warns could severely choke the industry’s growth.

In China, Ma continued, it’s considered a “solved problem.”

Ma, a renowned expert in Chinese technology and founder of the media company Tech Buzz China, took her team on the road to get a firsthand look at the country’s AI advancements. She told Fortune that while she isn’t an energy export, she attended enough meetings and talked to enough insiders to come away with a conclusion that should send chills down the spine of Silicon Valley: in China, building enough power for data centers is no longer up for debate.

“This is a stark contrast to the U.S., where AI growth is increasingly tied to debates over data center power consumption and grid limitations,” she wrote on X.

The stakes are difficult to overstate. Data center building is the foundation of AI advancement, and spending on new centers now displaces consumer spending in terms of impact to U.S. GDP—that’s concerning since consumer spending is generally two-thirds of the pie. McKinsey projects that between 2025 and 2030, companies worldwide will need to invest $6.7 trillion into new data center capacity to keep up with AI’s strain. 

In a recent research note, Stifel Nicolaus warned of a looming correction to the S&P 500, since it forecasts this data-center capex boom to be a one-off build-out of infrastructure, while consumer spending is clearly on the wane.

However, the clear limiting factor to the U.S.’s data center infrastructure development, according to a Deloitte industry survey, is stress on the power grid. Cities’ power grids are so weak that some companies are just building their own power plants rather than relying on existing grids. The public is growing increasingly frustrated over increasing energy bills – in Ohio, the electricity bill for a typical household has increased at least $15 this summer from the data centers – while energy companies prepare for a sea-change of surging demand. 

Goldman Sachs frames the crisis simply: “AI’s insatiable power demand is outpacing the grid’s decade-long development cycles, creating a critical bottleneck.” 

Meanwhile, David Fishman, a Chinese electricity expert who has spent years tracking their energy development, told Fortune that in China, electricity isn’t even a question. On average, China adds more electricity demand than the entire annual consumption of Germany, every single year. Whole rural provinces are blanketed in rooftop solar, with one province matching the entirety of India’s electricity supply. 

“U.S. policymakers should be hoping China stays a competitor and not an aggressor,” Fishman said. “Because right now they can’t compete effectively on the energy infrastructure front.”

China has an oversupply of electricty

China’s quiet electricity dominance, Fishman explained, is the result of decades of deliberate overbuilding and investment in every layer of the power sector, from generation to transmission to next-generation nuclear.

The country’s reserve margin has never dipped below 80%–100% nationwide, meaning it has consistently maintained at least twice the capacity it needs, Fishman said. They have so much available space that instead of seeing AI data centers as a threat to grid stability, China treats them as a convenient way to “soak up oversupply,” he added.

That level of cushion is unthinkable in the United States, where regional grids typically operate with a 15% reserve margin and sometimes less, particularly during extreme weather, Fishman said. In places like California or Texas, officials often issue warnings about red-flag conditions when demand is projected to strain the system. This leaves little room to absorb the rapid load increases AI infrastructure requires, Fishman ntoed. 

The gap in readiness is stark: while the U.S. is already experiencing political and economic fights over whether the grid can keep up, China is operating from a position of abundance.

Even if AI demand in China grows so quickly renewable projects can’t keep pace, Fishman said, the country can tap idle coal plants to bridge the gap while building more sustainable sources. “It’s not preferable,” he admitted, “but it’s doable.”

By contrast, the U.S. would have to scramble to bring on new generation capacity, often facing years-long permitting delays, local opposition, and fragmented market rules, he said. 

Structural governance differences

Underpinning the hardware advantage is a difference in governance. In China, energy planning is coordinated by long-term, technocratic policy that defines the market’s rules before investments are made, Fishman said. This model ensures infrastructure buildout happens in anticipation of demand, not in reaction to it.

“They’re set up to hit grand slams,” Fishman noted. “The U.S., at best, can get on base.”

In the U.S., large-scale infrastructure projects depend heavily on private investment, but most investors expect a return within three to five years: far too short for power projects that can take a decade to build and pay off.

“Capital is really biased toward shorter-term returns,” he said, noting Silicon Valley has funneled billions into “the nth iteration of software-as-a-service” while energy projects fight for funding. 

In China, by contrast, the state directs money toward strategic sectors in advance of demand, accepting not every project will succeed but ensuring the capacity is in place when it’s needed. Without public financing to de-risk long-term bets, he argued, the U.S. political and economic system is simply not set up to build the grid of the future.

Cultural attitudes reinforce this approach. In China, renewables are framed as a cornerstone of the economy because they make sense economically and strategically, not because they carry moral weight. Coal use isn’t cast as a sign of villainy, as it would be among some circles in the U.S. –  it’s simply seen as outdated. This pragmatic framing, Fishman argued, allows policymakers to focus on efficiency and results rather than political battles.

For Fishman, the takeaway is blunt. Without a dramatic shift in how the U.S. builds and funds its energy infrastructure, China’s lead will only widen.

“The gap in capability is only going to continue to become more obvious — and grow in the coming years,” he said.



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Fortune Brainstorm AI San Francisco starts today, with Databricks, OpenAI, Cursor, and more on deck

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It’s been a crazy few weeks in AI.

Granted, it feels like it’s always been a crazy few weeks in AI. But this cycle has been especially notable: Reports that Sam Altman has declared a “code red” around improving ChatGPT have made waves, while Databricks is reportedly in talks to raise at a jaw-dropping $134 billion valuation. Anthropic is reportedly looking at a real-life IPO, and everyone’s always watching for news from perhaps the biggest ascent of the year: Cursor, the AI coding juggernaut that’s now valued at more than $29 billion. 

And today, Brainstorm AI starts, and so many of these key players will be with us live in San Francisco, including Databricks CEO Ali Ghodsi, OpenAI COO Brad Lightcap, Cursor CEO Michael Truell, San Francisco Mayor Daniel Lurie, Google Cloud CEO Thomas Kurian, and Rivian CEO RJ Scaringe, plus some starpower from Joseph Gordon-Levitt and Natasha Lyonne. 

If you’re attending the conference, come find me! I’ll realistically be the one running around in a bright pantsuit. And if you can’t make it, we’ll be livestreaming the show, too – tune in here.

See you soon,

See you tomorrow,

Allie Garfinkle
X:
@agarfinks
Email:alexandra.garfinkle@fortune.com
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Joey Abrams curated the deals section of today’s newsletter.Subscribe here.

Venture Deals

Antithesis, a Tysons Corner, Va.-based platform designed to validate that software works before it launches, raised $105 million in Series A funding. JaneStreet led the round and was joined by AmplifyVenturePartners, SparkCapital, and others.

ParadigmHealth, a Columbus, Ohio-based clinical research platform, raised $78 million in Series B funding. ARCHVenturePartners led the round and was joined by DFJGrowth and existing investors.

Oxzo, a Santiago, Chile-based provider of oxygenation services for aquaculture, raised $25 million in funding from S2GInvestments.

Quanta, a San Francisco-based accounting platform, raised $15 million in Series A funding. Accel led the round and was joined by OperatorCollective, NavalRavikant, DesignerFund, and others.

LizzyAI, a New York City-based AI-powered talent interviewing company, raised $5 million in seed funding. NEA led the round and was joined by Speedinvest and ZeroPrimeVentures

PvX, a Singapore-based provider of user-acquisition financing for gaming companies, raised $4.7 million in a seed extension from Z Venture Capital, DrivebyDraftKings, and existing investors.

Corma, a Paris, France-based developer of a copilot for AI teams, raised €3.5 million ($4.1 million) in seed funding. XTXVentures led the round and was joined by TuesdayCapital, KimaVentures, 50Partners, OlympeCapital, and angel investors.

Private Equity

NITEOProducts, a portfolio company of HighlanderPartners, acquired Folexport, a Tualatin, Ore.-based manufacturer of carpet, fabric, and hard surface cleaning products. Financial terms were not disclosed.



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Why the worst leaders sometimes rise the fastest

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History is crowded with CEOs who have flamed out in very public ways. Yet when the reckoning arrives, the same question often lingers: How did this person keep getting promoted? In corporate America, the phenomenon is known as “failing up,” the steady rise of executives whose performance rarely matches their trajectory. Organizational psychologists say it’s not an anomaly. It’s a feature of how many companies evaluate leadership.

At the core is a well-documented bias toward confidence over competence. Studies consistently show that people who speak decisively, project certainty, and take credit for wins—whether earned or not—are more likely to be perceived as leadership material. In ambiguous environments, boards and senior managers often mistake boldness for ability. As long as a leader can narrate failure convincingly—blaming market headwinds, legacy systems, or uncooperative teams—their upward momentum may continue.

Another driver is asymmetric accountability. Senior executives typically oversee vast, complex systems where outcomes are hard to tie directly to individual decisions. When results are good, credit flows upward. When results are bad, blame diffuses downward, and middle managers, project leads, and market conditions become convenient shock absorbers. This allows underperforming leaders to survive long enough to secure their next promotion.

Then there’s the mobility illusion. In many industries, frequent job changes are read as ambition and momentum rather than warning signs. An executive who leaves after short, uneven tenures can reframe each exit as a “growth opportunity” or a strategic pivot. Recruiters and boards, under pressure to fill top roles quickly, often rely on résumé signals, like brand-name firms, inflated titles, and elite networks, rather than deep performance audits.

Ironically, early visibility can also accelerate failure upward. High-profile roles magnify both success and failure, but they also increase name recognition. An executive who runs a troubled division at a global firm may preside over mediocre results, yet emerge with a reputation as a “big-company leader,” making them attractive for a CEO role elsewhere.

The reckoning usually comes only at the top. As CEO, the buffers disappear. There is no one left to blame, and performance is judged in the blunt language of earnings, stock price, profitability, or layoffs. The traits that once fueled ascent, such as overconfidence, risk-shifting, and narrative control, become liabilities under full scrutiny.

The central lesson for aspiring CEOs is that the very system that rewards confidence, visibility, and narrative control on the way up often masks weak execution until the top job strips those protections away. Future leaders who want to avoid “failing upward” must deliberately build careers grounded in verifiable results and direct ownership of outcomes because at the CEO level, there is no narrative strong enough to substitute for performance.

Ruth Umoh
ruth.umoh@fortune.com

Smarter in seconds

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Old guard upgrade. How the bank founded by Alexander Hamilton is transforming for the future of finance

Pressure test. Inside the Fortune 500 CEO pressure cooker: surviving is harder than ever and requires an ‘odd combination’ of traits

Rank racing. The one-upmanship driving CEOs

Leadership lesson

Anthropic’s Dario Amodei on when a startup gets too big to know all employees: “It’s an inevitable part of growth.”

News to know

Investors are questioning OpenAI’s profitability amid its massive spending while increasingly viewing Alphabet as the deeper-pocketed winner in the AI race. Fortune

Trump warned that Netflix’s $72 billion bid for Warner Bros. Discovery could face antitrust scrutiny, suggesting it would create an overly dominant force in streaming. Fortune

An etiquette camp is trying to help Silicon Valley shed its sloppy image by teaching tech elites how to dress and behave as their influence grows. WaPo

IBM is reportedly in advanced talks to buy data-infrastructure firm Confluent for about $11 billion, bolstering its AI data capabilities. WSJ

Even as women reach top roles in politics and business at record levels, public confidence in their leadership is stagnating or declining. Bloomberg

Terence “Bud” Crawford, the undefeated 38-year-old boxing champion, has earned more than $100 million and even turned Warren Buffett into a fan. Forbes

Big Tech leaders now warn that artificial intelligence is advancing to the point where it could begin replacing even CEOs, reshaping the very top of corporate leadership. WSJ

This is the web version of the Fortune Next to Lead newsletter, which offers strategies on how to make it to the corner office. Sign up for free.



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The workforce is becoming AI-native. Leadership has to evolve

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One of the most insightful conversations I have had recently about artificial intelligence was not with policymakers or peers. It was with a group of Nokia early-careers talents in their early 20s. What stood out was their impatience. They wanted to move faster in using AI to strengthen their innovation capabilities. 

That makes perfect sense. This generation began university when ChatGPT launched in 2022. They now account for roughly half of all ChatGPT usage, applying it to everything from research to better decision-making in knowledge-intensive work. 

Some people worry that AI-driven hiring slowdowns are disproportionately impacting younger workers. Yet the greater opportunity lies in a new generation of AI-native professionals entering the workforce equipped for how technology is transforming roles, teams, and leadership.

Better human connectivity 

One of the first tangible benefits of generative AI is that it allows individual contributors to take on tasks once handled by managers. Research by Harvard Business School found that access to Copilot increased employee productivity by 5% in core tasks. As productivity rises and hierarchies flatten, early-career employees using AI are empowered to focus on outcomes, learn faster, and contribute at a higher level.

Yet personal productivity is not the real measure of progress. What matters most is how well teams perform together. Individual AI gains only create business impact when they align with team goals and that requires greater transparency, alignment, and accountability.

At Nokia, we ensure that everyone has clear, measurable goals that support their teams’ objectives. Leaders need to be open about their goals to their managers and to their reports. And everyone means everyone. Me included. That way goals are not only about recognition and reward. They become an ongoing dialogue between leaders and their teams. It’s how we’re building a continuous learning culture that thrives on feedback and agility, both essential in the AI era. 

Humans empowered with AI, not humans versus AI

AI’s true power lies in augmenting human skills. Every role has a core purpose – whether in strategy, creativity, or technical problem-solving – and AI helps people focus on that. 

During the COVID-19 pandemic, more than 60 chatbots were deployed in 30 countries to handle routine public health queries, freeing up healthcare workers to focus on critical patient care. Most health services never looked back. 

The same pattern applies inside companies. Some of the routine tasks given to new hires are drudge work and not a learning experience. AI gives us a chance to rethink the onboarding, training, and career development process.

Take an early-career engineer. Onboarding can be a slow process of documentation and waiting for reviews. AI can act as an always-on coach that gives quick guidance and helps people ramp up. Mentors then spend less time on the basics and more time helping engineers solve real problems. Engineers can also have smart agents testing their designs, ideas, and simulating potential outcomes. In this way, AI strengthens, rather than substitutes, the human connection between junior engineers and their mentors and helps unlock potential faster.

Encourage experimentation and entrepreneurship 

During two decades of the Internet Supercycle (1998-2018), start-ups created trillions of dollars in economic value and roughly half of all new jobs in OECD countries

As AI lowers the barriers to launching and scaling ventures, established companies must find new ways to encourage experimentation, nurture innovation through rapid iterations, and give employees the chance to commercialize and scale their ideas.

There is a generational shift that increases the urgency: more than 60% of Gen Z Europeans hope to start their own businesses within five years, according to one survey. To secure this talent, large organizations must provide the attributes that make entrepreneurship attractive. Empowering people with agility, autonomy, and faster decision-making creates an edge in attracting and keeping top talent.

At Nokia, our Technology and AI Organization is designed to strengthen innovation capabilities, encourage entrepreneurial thinking, and give teams the support to turn ideas into real outcomes.

More coaching, less managing 

Sporting analogies are often overused in business as the two worlds don’t perfectly align, yet the evolution of leadership in elite football offers useful lessons. Traditionally, managers oversaw everything on and off the pitch. Today, head coaches focus on building the right team and culture to win. 

Luis Enrique, the manager of Paris-St. Germain football club, last season’s UEFA Champion’s League winner, exemplifies this shift. He transformed a team of stars into a star team, while also evolving his coaching style, elevating both individual and collective potential.

Of course, CEOs must switch between both roles (as I said, the worlds don’t perfectly align) – setting vision and strategy while also cultivating the right team and culture to succeed. AI can help leaders do both with more focus. It gives us quicker insight into what is working, what is not, and where teams need support.

I have been testing these tools with my own leadership team. We are using generative AI to help us evaluate our decisions and to understand how we work together. It has revealed patterns we might have missed, and it has helped us get to the real issues faster. It does not replace judgment or experience. It supports them.

Yet the core of leadership does not change. AI cannot build trust. It cannot set expectations. It cannot create a culture that learns, improves, and takes responsibility. That still comes from people. And in a world shaped by AI, the leaders who succeed will be the ones who coach, who listen, and who help teams move faster with confidence.

Nokia’s technology connects intelligence around the world. Inside the company, connecting intelligence is about how people work together. It means giving teams the tools, support and culture they need to grow and perform with confidence. Connecting intelligence is how teams win.

The opinions expressed in Fortune.com commentary pieces are solely the views of their authors and do not necessarily reflect the opinions and beliefs of Fortune.



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