The Morning Download: Why Nvidia Leads Our List of the Best Companies for the Future

Good morning. It’s no surprise that Nvidia tops the inaugural ranking of the Best Companies for the Future from the WSJ Leadership Institute. Why it’s there requires a bit of explanation, though.

Nvidia has been built to peer around corners and anticipate the future. It grasped early on how its graphics processing units were ideal chips for training frontier AI models. The company anticipated the next steps in AI, such as running AI models after they have been trained, also known as inference. It also was early to the game of accelerating existing computing infrastructure to handle modern workloads. And it has invested early and heavily in emerging markets such as robotics and ramped up its focus on quantum computing, too.

The company has constructed a vast portfolio of software, AI models, networking gear, robotics, quantum computing efforts and more. And while that has made it among the most valuable companies in the world, Nvidia shares took a hit during Friday’s broad carnage in chip stocks, a reminder of just how volatile the AI and tech sector can be.

Nvidia’s global economic impact has been enormous, and includes a broad ecosystem of customers, tech partners and startups in its investment portfolio. That ecosystem is all about creating a foundation for the future upon which its partners can build.

Its position at the top of our ranking, created in partnership with Bendable Labs,  reflects its broad strength across a range of essential, forward-looking metrics. It landed the first or second spot in five of the six categories—AI readiness, innovation, talent readiness, financial fitness and agility. It ranked 110th on resilience, in part because of its dependence on Taiwan and China.

You can find full coverage of the project here. You can read more about the methodology here.

(WSJ Leadership Institute members receive exclusive access to insights through our competitive intelligence tool.)

Nvidia’s focus on the future reflects the vision of co-founder and CEO Jensen Huang. His singular mindset is evident in the very nature of the company.

I’ve observed Huang up close on many occasions, including two massive GTC developers conferences in San Jose, Calif. and one in Washington, D.C. I’ve listened to his keynotes and participated in his press conferences. Last year, in the midst of this reporting, I started to piece together some ideas about what makes this company and its leader function at such a high level. These ideas formed the basis of a column in April 2025, “Nvidia’s Dominance Reflects the CEO’s Unique Business Logic.” Here are highlights from that column:

Nvidia avoids doing things. It seemed clear to me that Nvidia’s impact on the market has as much to do with its forward-looking leadership and business model as it has to do with technology. It does many things, but in a disciplined and intentional way. The AI powerhouse has become ubiquitous, paradoxically by doing only what it deems essential. “If we can avoid doing something, we will,” Huang said during a March 19, 2025 press conference.

Room for the ecosystem to operate. During the event last year, Huang fielded a question about the company’s many partners and whether it was putting itself in a difficult position by competing in some instances with them. He acknowledged that Nvidia provides technology across AI infrastructure, networking, switches, storage and of course computing of every size, shape and form. “However—this is the however—we build everything, but we offer it to the world however they would like to take it,” he said. “And the reason for that is we are not a solutions company.”

Instead of selling its customers or partners finished solutions, Nvidia typically leaves them to decide how much of the last 50% of value creation they want to develop on their own. That makes it easier for enterprise tech companies to work with Nvidia, according to Huang. In theory, it also makes it easier for multiple companies in a single industry such as automobiles to build on top of Nvidia platforms and still differentiate themselves.

Nvidia’s discipline functions internally as well. Its 36,000 employees make it much smaller than other big tech companies in Silicon Valley, and Huang wants to put that “very scarce energy” to best use, he said last year as he received an Edison Achievement Award for innovation and innovators. That means focusing on work that Nvidia’s people consider worthy of their time, which is a strong motivator, he said.

A Learning Mindset

“Notice, when you come talk to us, not one employee ever says, ‘We fight for share,’” Huang said at the Edison ceremony. “Why fight for share? Create something new.”

As much as any single technological innovation, Nvidia’s success, to my mind, turns on its ability to create an interconnected system in which customers and partners contribute to its infrastructure or build on top of it.

While that in itself isn’t unique, the implementation is, thanks to the breadth of the core infrastructure, the focus on supremely difficult and essential problems, and a strategic sense of where not to apply its resources.

Like all great tech companies, Nvidia is a learning community. Like Google and Bell Labs before it, it has something of the feel of a university, with a hunger to take on the very biggest and most complex problems. Those problems, by their nature, point to the future, steering it to forward-looking markets from intelligence to robotics and climate science.

It’s filled with people who share that ambition and curiosity, and not just at the C-suite level or the research run by Chief Scientist Bill Dally, whom I spoke to back in 2023.

I visited Nvidia headquarters last year for a demonstration of one of its AI models. The demonstrator was patient with my questions, and impressed me with the thoroughness of her answers. It turns out that she had a Phd. I imagine that might have made her overqualified for a similar role at another company, but not at Nvidia, where learning is integral to a clear, pervasive and palpable culture that starts at the top and is geared toward looking ahead.

Now hiring: AI agent managers. Tyson Chen, founder and co-CEO of Avoca, recently noticed an interesting phenomenon among customers of his startup, which builds AI agents that support home services business.

Some of his customers had begun hiring AI agent managers: essentially people to oversee the bots that his startup provides. Those AI agents do things like answer the phone and book new customers, he told me on Thursday evening at a dinner hosted by venture-capital firm Amplify Partners in New York City.

“One day, all of a sudden, I saw one of our larger customers posted a LinkedIn role for a new job, and they were like, ‘This new job is literally built because of your technology, because we need someone to manage all the agents that you guys have produced for us.’” Chen said.

So what do these AI agent managers do? “You can give them feedback like, ‘Hey, be more empathetic here,’ or ‘I need you to make sure that we're always collecting the email address of the person,’” Chen told me.

In other words, it’s not too far off from overseeing humans, but the difference is that AI agents are “infinitely scalable,” Chen said. Bots don’t get tired and don’t get paid, but there’s certainly a token and compute cost.

—Belle Lin

• Sen. Adam Schiff (D., Calif.) is introducing legislation to require human oversight of Pentagon AI use and bar it from domestic surveillance, part of a wave of Democratic AI bills spurred by growing calls from many consumers and security experts for AI regulation. The proposals span military guardrails, data center costs, copyright disclosure, and even government ownership stakes in AI firms, the Journal reports.

• Twenty-six percent of companies say they have a comprehensive view of their AI costs, while 50% have some visibility and 22% report no visibility or visibility after billing, according to an as-yet-unreleased survey from KPMG.

• OpenAI is planning a ChatGPT overhaul, transforming the chatbot into a "superapp" combining coding tools and agents as it pushes to win business customers and boost revenue ahead of an IPO, the FT reports. The shift reflects a growing conviction inside OpenAI that the future of AI lies in agents that perform tasks, not chatbots that answer questions. Codex, its coding product, will be a centerpiece of the push.

• Nvidia is partnering with South Korean tech giants SK Telecom, SK Hynix, and Naver to build AI infrastructure across Asia, combining its chips and platform with local networks, data centers, and memory technology, the WSJ reports. The deals, announced during CEO Jensen Huang's second visit to Seoul in under a year, deepen Nvidia's foothold in a region that produces the world's leading memory chips.

• Data centers in Ireland use a fifth of the country’s electricity. Now, Ireland is trying a new approach: B.Y.O.P., or Bring Your Own Power, WSJ reports. New data centers and expansions of existing facilities are welcome, but must have their own power plants on site or contracts for new, largely renewable sources of energy to be produced nearby. 

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Follow Isabelle Bousquette on LinkedIn, Instagram, X, and TikTok for more behind the scenes on her tech and AI coverage, and lately, her contributions to the WSJ Leadership Institute's new Executive Resilience series, where she's profiling America's top execs about their fitness and wellness habits.

Follow Belle Lin on LinkedIn and X for her latest reporting on enterprise technology and AI.

Steven Rosenbush is chief of the enterprise technology bureau at the WSJ Leadership Institute. He also has a column. You can follow him on LinkedIn.

Tom Loftus is the editor of The Morning Download. He suggests following Isabelle, Belle and Steve on their various social channels. But if you insist, here's his LinkedIn.