Meta’s CEO says AI will eventually create more employment. His own company is already showing the other side of that bet: individual companies may need fewer workers.
Zuckerberg says artificial intelligence could lead to more jobs, not fewer. Less than three months earlier, Meta cut around 8,000 employees. That contrast sits at the centre of his AI argument.
Zuckerberg believes AI will allow companies to accomplish far more with smaller teams. But he also expects those same capabilities to make it easier to start businesses, creating enough new companies and occupations to produce more employment across the economy over time.
Meta may already be demonstrating the first half of that prediction.
Meta cut 8,000 workers. Then Zuckerberg predicted more jobs.
Meta laid off about 10% of its global workforce—roughly 8,000 people—on May 20 as part of a sweeping restructuring. Another 7,000 employees were transferred to initiatives involving AI workflows.
Then, on August 10, Zuckerberg published The Future is for Everyone, an essay laying out his vision for personal superintelligence and its effects on society.
His prediction for employment was optimistic.
Zuckerberg wrote that AI could produce “more employment over time rather than less.” He later argued there are reasons to expect an “abundance of jobs” as people use AI to create products, services and businesses that previously would have been too difficult or expensive to build.
That prediction sounds strange immediately after cutting thousands of employees.
But Zuckerberg’s argument accounts for companies doing exactly what Meta just did.
Zuckerberg’s bet: smaller companies, more companies
One of the most consequential lines in Zuckerberg’s essay is also one of the simplest:
“Company sizes may shrink.”
He expects AI to let individuals and small teams perform work that once required much larger organizations.
A founder who previously needed engineers, designers, analysts, marketers and support staff may increasingly be able to handle much of that work with AI. Existing teams gain similar leverage.
Zuckerberg expects the result to be a larger number of companies with fewer people inside each one. He predicts that small groups equipped with personal AI agents will eventually be capable of running businesses at significant scale.
He also points to jobs that are uncommon today, including one-person product studios, world builders, experience designers and “personal biologists” using AI to develop personalized treatments.
The economic bet is straightforward:
AI reduces the number of people required to build a company, while simultaneously increasing the number of people capable of building one.
If the second effect is large enough, total employment can rise even while individual companies get smaller.
Meta is already showing us the first half
Zuckerberg’s own company makes the tension concrete.
Months before the layoffs, he told investors Meta was starting to see projects that once required big teams being completed by a single highly capable person. Reuters later reported that Meta was preparing for greater efficiency from AI-assisted workers while spending heavily on AI infrastructure.
At the same time, that infrastructure is extraordinarily expensive.
In an April 30 town hall, Zuckerberg told employees that Meta essentially has two major cost centres: computing infrastructure and people. Spending more capital on AI computing meant having less available for the other side of that equation, he said.
Meta did not say 8,000 employees were replaced by AI.
Zuckerberg specifically told employees that improved productivity from internal AI tools wasn’t what was driving the layoffs, and he said the cuts were separate from Meta’s reorganization around an “AI-native” structure. He instead pointed to the enormous capital requirements of AI infrastructure as a reason Meta needed to reduce its size.
Still, the economic pressures are difficult to separate.
Meta is spending heavily to build AI while seeing evidence that smaller groups can accomplish work that once required larger teams.
For a company deciding where its next dollar goes, those two forces make headcount harder to defend.
The new jobs have to arrive fast enough
Zuckerberg acknowledges the biggest weakness in his optimistic scenario.
Automation could move faster than people gain new capabilities, causing job displacement followed by what he describes as a “difficult period” while workers learn new jobs.
His preferred outcome depends on people gaining AI-powered leverage at least as quickly as businesses use AI to automate existing work.
That’s a huge assumption.
Technological shifts have created entirely new categories of employment before. Zuckerberg points to app developers, social media creators, electric vehicle technicians and data centre operators as examples of jobs that were uncommon or nonexistent a generation ago.
AI will likely produce new job categories too.
But workers don’t experience economic transitions as long-term charts.
They experience them one paycheque at a time.
Someone whose role disappears this year needs another source of income this year—not an occupation that becomes widespread several years from now.
So the important questions aren’t simply whether AI creates jobs eventually.
How quickly will those jobs appear?
Will there be enough of them?
And can the people displaced from existing roles realistically move into them?
Those questions will determine whether Zuckerberg’s transition feels like an entrepreneurial boom or a painful labour-market shock.
Productivity doesn’t have to mean cutting the team
For small businesses, productivity gains can cut costs—or expand ambition.
Suppose five employees can use AI to produce what once required 15.
One option is obvious: keep the same output and reduce the workforce.
But the company could also keep those five people and attempt far more.
Launch another product. Serve more customers. Test ideas that previously weren’t affordable. Enter a new market. Finally tackle the backlog that’s been sitting there for two years.
For smaller businesses, that may be one of AI’s biggest opportunities.
A company that couldn’t afford dedicated researchers, analysts, developers, copywriters or support teams can increasingly give existing employees access to some of those capabilities.
The productivity gain is the same.
What management chooses to do with it is different.
And that distinction could help determine whether AI becomes primarily a labour-cutting technology or an engine for creating more economic activity.
Meta has shown the first half. The second remains unproven.
Zuckerberg’s prediction is less contradictory than it first appears.
Meta can cut 8,000 workers while its CEO genuinely believes AI will eventually increase employment across the broader economy.
His thesis depends on something much bigger than Meta.
In his view, AI makes teams smaller. Smaller teams make businesses cheaper to build. Cheaper businesses lead to more entrepreneurs and more companies. Those companies create enough new work to offset the jobs automation removes.
The smaller-team part of that chain is becoming easier to see.
Meta itself has acknowledged that work once requiring large teams can increasingly be handled by much smaller ones. Other companies are making similar calculations as AI becomes more capable.
The wave of new companies and jobs he predicts has yet to arrive.
For business owners, the opportunity isn’t simply figuring out how many positions AI can eliminate.
It’s figuring out what becomes possible when each person on the team can accomplish more than before.
For workers, the signal is equally clear: tasks that AI can reproduce cheaply will become harder to build a career around.
The advantage will belong to people who can decide what should be done, why it matters and how to use AI to get it done.
Meta has already shown us what the smaller-company side of Zuckerberg’s future can look like.
Now we find out whether the jobs show up too.
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