More Big Companies Bet They Can Still Grow Without Hiring

It’s the corporate gamble of the moment: Can you run a company, increasing sales and juicing profits, without adding people?

American employers are increasingly making the calculation that they can keep the size of their teams flat—or shrink through layoffs—without harming their businesses.

Part of that thinking is the belief that artificial intelligence will be used to pick up some of the slack and automate more processes. Companies are also hesitant to make any moves in an economy many still describe as uncertain.

JPMorgan Chase’s chief financial officer told investors recently that the bank now has a “very strong bias against having the reflective response” to hire more people for any given need. Aerospace and defense company RTX boasted last week that its sales rose even without adding employees.

Goldman Sachs , meanwhile, sent a memo to staffers this month saying the firm “will constrain head count growth through the end of the year” and reduce roles that could be more efficient with AI. Walmart , the nation’s largest private employer, also said it plans to keep its head count roughly flat over the next three years, even as its sales grow.

“If people are getting more productive, you don’t need to hire more people,” Brian Chesky , Airbnb’s chief executive, said in an interview. “I see a lot of companies pre-emptively holding the line, forecasting and hoping that they can have smaller workforces.”

Airbnb employs around 7,000 people, and Chesky says he doesn’t expect that number to grow much over the next year. With the help of AI, he said he hopes that “the team we already have can get considerably more work done.”

Many companies seem intent on embracing a new, ultralean model of staffing, one where more roles are kept unfilled and hiring is treated as a last resort. At Intuit , every time a job comes open, managers are pushed to justify why they need to backfill it, said Sandeep Aujla , the company’s chief financial officer. The new rigor around hiring helps combat corporate bloat.

“That typical behavior that settles in—and we’re all guilty of it—is, historically, if someone leaves, if Jane Doe leaves, I’ve got to backfill Jane,” Aujla said in an interview. Now, when someone quits, the company asks: “Is there an opportunity for us to rethink how we staff?”

Intuit has chosen not to replace certain roles in its finance, legal and customer-support functions, he said. In its last fiscal year, the company’s revenue rose 16% even as its head count stayed flat, and it is planning only modest hiring in the current year.

The desire to avoid hiring or filling jobs reflects a growing push among executives to see a return on their AI spending. On earnings calls, mentions of ROI and AI investments are increasing, according to an analysis by AlphaSense, reflecting heightened interest from analysts and investors that companies make good on the millions they are pouring into AI.

Many executives hope that software coding assistants and armies of digital agents will keep improving—even if the current results still at times leave something to be desired.

The widespread caution in hiring now is frustrating job seekers and leading many employees within organizations to feel stuck in place, unable to ascend or take on new roles, workers and bosses say.

Inside many large companies, HR chiefs also say it is becoming increasingly difficult to predict just how many employees will be needed as technology takes on more of the work.

Some employers seem to think that fewer employees will actually improve operations.

Meta Platforms this past week said it is cutting 600 jobs in its AI division, a move some leaders hailed as a way to cut down on bureaucracy.

“By reducing the size of our team, fewer conversations will be required to make a decision, and each person will be more load-bearing and have more scope and impact,” Alexandr Wang , Meta’s chief AI officer, wrote in a memo to staff seen by The Wall Street Journal.

Though layoffs haven’t been widespread through the economy, some companies are making cuts. Target on Thursday said it would cut about 1,000 corporate employees, and close another 800 open positions, totaling around 8% of its corporate workforce. Michael Fiddelke , Target’s incoming CEO, said in a memo sent to staff that too “many layers and overlapping work have slowed decisions, making it harder to bring ideas to life.”

A range of other employers, from the electric-truck maker Rivian to cable and broadband provider Charter Communications , have announced their own staff cuts in recent weeks, too.

Operating with fewer people can still pose risks for companies by straining existing staffers or hurting efforts to develop future leaders, executives and economists say. “It’s a bit of a double-edged sword,” said Matthew Martin , senior U.S. economist at Oxford Economics. “You want to keep your head count costs down now—but you also have to have an eye on the future.”

For decades, the world’s computing power has quietly expanded at an astonishing pace.

From the first transistor developed at Bell Labs in 1947 to modern processors containing billions and even trillions of transistors, each generation of technology has been faster, smaller and more powerful than the last.

But according to quantum physicist and technology entrepreneur David Reilly, that era of effortless progress is beginning to slow.

Reilly, CEO of Sydney-based Emergence Quantum and Professor of Physics at the University of Sydney, says the computing infrastructure underpinning modern economies is approaching fundamental physical limits.

And that could have enormous implications for finance, artificial intelligence and global investment.

Speaking at an industry event organised by Kanebridge International, Reilly said many critical parts of modern society depend on computing and the infrastructure used to process information.

The slowdown behind the tech boom

For years, the technology industry relied on a steady improvement known as Moore’s Law, where the number of transistors on a chip doubled roughly every two years.

More transistors meant more computing power, allowing faster software, smarter devices and ever-larger data systems.

Today, however, those gains are slowing.

“It feels to me very innate that I’m going to just find that next year there’s going to be another breakthrough,” Reilly said.

“But if you look at the data…there’s a slowing down, a roll off in performance that started some 10, 20 years ago.”

Rather than making chips dramatically faster, manufacturers are now largely increasing computing capacity by packing more transistors onto each processor.

The approach works, but it comes with growing complexity, higher costs and increasing energy demands.

The brute-force race for AI

That challenge is already visible in the massive data centres being built to support artificial intelligence.

In the race to dominate AI, companies are constructing vast computing facilities that consume huge amounts of electricity and water. Reilly described this expansion as a “brute force” approach driven by the global competition to develop advanced AI systems.

Yet the demand for computing power continues to accelerate.

Artificial intelligence, advanced robotics, healthcare research, pharmaceuticals and cybersecurity all require far more processing capacity than today’s systems can easily deliver.

The question now facing the technology sector is whether traditional computing can keep up.

Enter quantum computing

That is where quantum computing enters the conversation.

Unlike conventional computers, which process information using binary switches that represent ones and zeros, quantum computers exploit the unusual behaviour of particles at the atomic scale.

Reilly describes them as a fundamentally different type of machine.

“So a quantum computer is a wave computer,” he said.

Instead of processing information through simple on-off switches, quantum systems can use wave-like properties of particles to process many possible outcomes simultaneously.

Those waves can interact in complex ways, reinforcing correct solutions while cancelling out incorrect ones. In theory, this allows quantum systems to tackle certain types of problems dramatically faster than classical computers.

What it could mean for finance

The concept may sound abstract, but its potential applications are significant.

Quantum computers are expected to transform areas such as materials science, chemical modelling and pharmaceutical development.

They could also help solve complex optimisation problems in logistics, finance and risk management.

For financial institutions in particular, the technology could offer new tools for detecting fraud, analysing market behaviour and optimising portfolios.

But the shift will not happen overnight.

“One message to take away is that quantum is not going to suddenly solve all of your problems,” Reilly said.

Instead, he said quantum systems will likely complement existing computing technologies as part of a broader and more diverse computing ecosystem.

Why data centres may soon “go cold”

One key change already emerging is how computing systems are physically designed.

Many next-generation technologies, including quantum processors, operate far more efficiently at extremely low temperatures. As a result, future data centres may rely heavily on cryogenic cooling systems to manage heat and energy consumption.

Reilly believes that the shift will gradually reshape the computing industry.

“Over the next five years, you’re going to see data centres go cold,” he said.

“And as that happens, they almost drag with them new compute paradigms.”

Emergence Quantum, the company he co-founded, is focused on developing technologies to support that transition, including cryogenic electronics and integrated hardware platforms designed for quantum computing and energy-efficient systems.

A new technological era

For investors and businesses, the technology remains in its early stages. But the scale of global interest is growing rapidly.

Governments, research institutions and technology companies are investing heavily in quantum research, betting it could become a foundational technology for the next generation of computing.

For Reilly, the moment feels similar to earlier technological turning points.

In the 19th century, new discoveries in thermodynamics helped drive the development of steam engines and the Industrial Revolution. In the 20th century, advances in electromagnetism led to radio, television and eventually the internet.

Quantum physics, he suggests, could represent the next chapter in that story.

“Today we have, as a society, in our hands new physics that we’re just beginning to figure out what to do with,” Reilly said.

“But I think it’s an exciting time to be alive and watch what happens over the coming decades.”