a16z: AI is not the end of jobs but the beginning of an era of intelligent inclusivity

Author: David George, General Partner at a16z; Source: a16z; Translation: Shaw, Golden Finance

The panic about a “permanent underclass of unemployment” promoted by artificial intelligence (AI) alarmists is fundamentally unfounded, and has long been old news. It’s simply labor supply fallacy repackaged and reappeared.

The core idea of the labor supply fallacy is: The total amount of work society needs to complete is fixed. It assumes that current workers, other practitioners, machines, and even today’s AI are in a zero-sum game relationship. According to this logic: since the total useful work in society is constant, the more AI does, the less humans can do.

But this premise completely contradicts all our understanding of human nature, markets, and economics. Human desires and needs are never fixed. Nearly a century ago, Keynes famously predicted that automation would reduce humans to working only 15 hours a week. Clearly, he was wrong. He correctly foresaw that automation would lead to labor surplus, but humans did not simply lie down to enjoy leisure; instead, they kept exploring entirely new productive activities, enriching their own time.

Admittedly, AI will replace some tasks and compress certain jobs (evidence already shows this process is underway). Every disruptive technology reshapes labor market patterns—this has always been the case. But claiming AI will cause permanent large-scale unemployment across society is just clickbait marketing, a fallacious economic argument, and a gross neglect of historical laws. On the contrary, increased productivity will boost labor demand because labor itself will become more valuable.

Below is our complete logical reasoning.

Humans Are Not Doomed? Overstatement

We agree with the doomsayers—indeed, any clear-eyed observer can see: the cost of cognitive labor is plummeting dramatically. Tasks once considered exclusive to the human brain are now increasingly performed well by AI.

The alarmist argument is: “If AI can think for us, then humans’ protective moat will vanish instantly, and human ultimate value will drop to zero.” Humans will thus be completely replaced. In their view, the work and thinking humans need and want have reached an end; now AI will shoulder an ever-growing share of mental load, and humans will gradually become redundant, phased out by the times.

But the reality is quite the opposite: historical precedents and logical reasoning show that when a powerful production factor’s cost drops significantly, the economy never stagnates. Lower costs, improved quality, and faster efficiency make new products feasible, and overall demand expands outward. The Jevons paradox applies perfectly here.

When fossil fuels made energy cheap and abundant, humans didn’t just eliminate traditional jobs like whalers and lumberjacks; we also invented entirely new things like plastics.

Contrary to doomsayers, we have every reason to believe AI will produce similar effects. As AI takes on more and more mental work, humans gain freedom—opening up unprecedented, larger-scale, more ambitious frontier fields.

If we look to history, we can foresee: Technological revolutions will ultimately enlarge the entire economic cake.

Every dominant economic sector in the past has eventually yielded to larger, emerging industries… and this process only makes the overall economy bigger.

Today’s tech industry already surpasses the old finance, railway, and industrial sectors in scale; yet, from the perspective of total economy and market share, there is still vast room for growth. Productivity gains are not a zero-sum game but a powerful positive-sum growth engine. Humanity delegates much work to machines, and the result is: the economy and labor markets will only grow larger, more diverse, and more complex.

Doomsayers deliberately ignore human innovation history, cherry-picking only the current moment of mental cost collapse, treating it as the entire story. They see only AI replacing individual tasks, stopping there, without deeper analysis.

“Humans’ mental output will increase tenfold, but we won’t do more thinking or creating; instead, we’ll just relax, nap early and often, and everyone will do the same.” This idea is not only unimaginative but also severely detached from reality. Doomsayers package this narrative as “realism,” but history has never shown such a scenario.

The Failure of Luddites

Let’s review history to see what actually happened when productivity breakthroughs impacted the economy.

Agriculture

In the early 20th century, before widespread mechanization, about one-third of U.S. labor force worked in agriculture. By 2017, that share had fallen to about 2%.

If automation truly caused permanent unemployment, tractors should have completely destroyed the labor market. But the reality was the opposite: agricultural output nearly tripled, supporting a massive population increase. Those who left farming didn’t face permanent unemployment; instead, they flooded into previously unimaginable new industries: factories, supermarkets, office buildings, hospitals, labs, and later, service and tech sectors.

Undeniably, technology disrupted traditional farming careers; but at the same time, it released vast amounts of labor and resources, spawning a whole new economic system.

Electrification

The process of electrification follows a similar logic.

Electricity was not just a simple energy substitute. It replaced traditional drive shafts and belts with independent electric motors, forcing factories to reorganize around new production processes, and also gave rise to entirely new categories of consumer and industrial products.

This is a typical feature of every stage of technological revolution, as summarized by Carlotta Perez in Technological Revolutions and Financial Capital: early stages involve huge upfront investments and financial capital chasing after them; durable goods costs plummet; then durable goods manufacturers enter a long, multi-generational boom.

It took a long time for electricity to unleash its full productive power. In the early 20th century, only 5% of American factories used electric power, and less than 10% of households were wired.

By 1930, nearly 80% of manufacturing power came from electricity, and over the following decades, labor productivity doubled.

Productivity growth did not weaken labor demand; on the contrary, it spurred manufacturing expansion, increased sales staff, expanded credit, and boosted commercial activity. Not to mention the secondary effects of labor-saving devices like washing machines and cars: they enabled more people to engage in higher-value work previously out of reach.

As car prices fell, production and employment in the auto industry exploded.

This is the true role of general-purpose technology: restructuring economic frameworks and continuously expanding the boundaries of useful work.

This pattern repeats throughout history. Did spreadsheet software like VisiCalc and Excel eliminate bookkeepers? Absolutely not. The technological leap in calculation efficiency actually led to a surge in bookkeeping jobs, and even created a whole new industry: financial planning and analysis (FP&A).

We reduced about 1 million bookkeeping jobs but created roughly 1.5 million new financial analyst roles.

New service industry jobs

Of course, task automation doesn’t always lead to employment growth in adjacent sectors. Sometimes, productivity surplus spurs entirely new, unrelated industries, creating fresh incremental jobs.

But some ask: If AI only makes a small handful of people super-rich, leaving others far behind, what then?

At minimum, these ultra-rich will spend their wealth, generating an entirely new service sector—history shows this pattern:

The dramatic increase in productivity and wealth creation spurs a host of new careers. Even before the 1990s, these careers were technically feasible; but without rising incomes and ample labor supply, they could never have materialized.

No matter how one views services for the wealthy, the ultimate outcome is that everyone’s life improves. Demand expansion pushes median wages higher, creating more people who enter the ranks of the affluent.

Stripe economist Ernie Tedeschi offers a representative case: Travel agents.

Does technology reduce demand for travel agencies? Certainly:

Today, the total salary payout for travel agencies is about half of what it was at the turn of the century, almost entirely due to technological advances.

Does this mean technology has killed jobs? No. Travel agents haven’t faced permanent unemployment. They found new roles elsewhere in the economy; after adjusting for demographic aging, the employment ratio is roughly the same as in 2000.

Meanwhile, those remaining in the tech-enabled travel industry benefit from productivity gains, with wages now higher than before.

“In 2000, during the industry’s peak, travel agents’ average weekly wages were only 87% of the overall weekly median wage. By 2025, that ratio rose to 99%, meaning travel agency wages outpaced other private sector fields during this period.”

So even in this scenario, while technology did impact travel agency jobs, overall employment among the relevant workforce remains stable; and those who stayed in the industry now earn at record levels.

Empowerment Over Replacement (And New Jobs Yet to Come)

This final point is crucial and again underscores: AI doomsayers only see the tip of the iceberg.

For some jobs, AI is a disruptive survival threat. But for many more, AI is an enabler, greatly increasing the value of those roles. Behind every job at risk of being replaced by AI, there’s a different set of careers that will benefit.

Goldman Sachs estimates that the AI substitution effect has already been offset—and more—by AI-enabled productivity gains.

Notably, corporate management now clearly values AI empowerment more than job replacement.

To date, mentions of “AI enabling efficiency” in earnings calls outnumber “AI replacing jobs” roughly 8 to 1.

Even though Goldman Sachs hasn’t listed software engineers among “AI-enabled roles,” they are arguably the most typical example of AI’s productivity-boosting effect.

AI is a force multiplier for programming work. Code commits are soaring (new apps and startups are booming), and demand for software engineers is rebounding, returning to growth.

Since early 2025, software development roles—both in absolute numbers and as a share of the overall job market—have been increasing.

Is this due to AI? It’s too early to say definitively, but there’s no doubt AI has greatly empowered software engineering. Moreover, every corporate executive now ranks AI as a top priority.

All industries are trying to integrate AI into their operations, leading to large-scale hiring and transformation efforts. This only increases the value of specialized talent.

AI-related roles are driving salary growth faster than industry averages, especially in system design.

While these salary benefits may still be limited, they are in the very early stages. As more professionals acquire relevant skills, employment opportunities will expand. None of this supports the doomsayers’ narrative.

Meanwhile, Lennie Lazich, founder of the well-known tech community Lenny’s Newsletter, notes: the number of job openings for product managers (PMs) has rebounded since the industry rate environment plummeted, reaching a new high since 2022.

The simultaneous growth in hiring for software engineers and product managers is a perfect example that labor supply fallacy is false. If AI replaced human mental work one-to-one, logically, we’d see: “Fewer engineers needed, so fewer product managers,” or vice versa. But that’s not what’s happening. Both roles are hiring more, because AI enables us to do more and larger-scale work.

This is the core flaw of AI doomsayers: Lack of imagination. They focus only on scattered tasks that automation can replace, ignoring the emerging frontiers of demand that will give rise to entirely new careers we can’t even imagine today.

Most new jobs created since 1940 didn’t exist in 1940. In 2000, it was easy to foresee many travel agent layoffs; but it’s hard to imagine an entire cloud migration industry serving mid-sized companies—until cloud computing arrived a decade later.

What does the current situation tell us?

So far, our analysis has been based on theory and historical precedent, both of which favor the optimistic view.

And it’s true. Every productivity breakthrough unleashes potential, expanding demand or reallocating surplus to other parts of the economy. This means jobs will increase: existing roles will be greatly enhanced, and many new careers will emerge that we can’t even imagine now.

If, by some chance, this time is an exception in history, doomsayers will need to produce rigorous, solid evidence—not just panic and hollow rhetoric.

Job displacement does not destroy human civilization; quite the opposite, this logic is sound. Human nature is never content with the status quo or stagnation. We complete one task, then pursue the next.

Setting aside theory and history, what does the actual data say about AI and employment? It’s important to note that we are still in early stages, and the full pros and cons are not yet clear; but current mainstream data does not support the doomsayers’ claims. Even conservatively, data shows no significant disruption in the job market; and increasingly, new data points to the opposite: AI creates more jobs than it displaces.

Let’s look at some academic studies—not exhaustive, just recent representative papers:

• Artificial Intelligence, Productivity, and Labor: Evidence from Firm Executives (National Bureau of Economic Research Working Paper 34984): The results show that, although AI’s proliferation has not yet significantly changed overall employment levels, it is beginning to reshape internal task division and occupational structures within firms. Routine clerical and administrative jobs are more easily replaced by AI; analysis, technical, and managerial roles tend to be complemented and empowered by AI.

• Firm-Level Data on Artificial Intelligence (Federal Reserve Bank of Atlanta, Working Paper 2026-3): Based on four surveys, over 90% of firms believe AI has had no impact on their employment over the past three years.

• Microstructure of AI Diffusion: Evidence from Firms, Business Functions, and Employee Tasks (U.S. Census Bureau, CES 26-25): The study finds that employment changes driven by AI are generally mild; only about 5% of firms using AI report affected employee numbers. Firms with increased jobs (2.3% weight, 3.7% employment weight) and those with decreased jobs (2.0% weight, 2.4% employment weight) are roughly evenly split.

• Tracking AI’s Impact on the Labor Market (Yale Budget Laboratory, April 16, 2026): “Despite widespread societal concern that AI will disrupt the labor market, our data suggests these fears are largely subjective guesses. The overall impact of AI on the labor market appears stable, with no macroeconomic disruptive shocks.”

The logic is straightforward. Recent studies repeatedly convey the same conclusion: overall employment remains stable, but there is a structural reconfiguration of jobs and tasks. Some research even shows that AI’s net effect on hiring is positive.

An exception worth noting: studies from Stanford, Dallas Fed, and Census Bureau find (to varying degrees) that entry-level jobs with high AI penetration are becoming harder to find.

But before jumping to the conclusion that “AI is destroying entry-level jobs,” it’s important to note that these studies also find that the number of entry-level jobs empowered by AI is increasing, and the number of unaffected entry-level roles is also rising.

Even if we accept that some entry-level jobs are being replaced by AI—due to factors other than macro hiring cycles or demographic aging—the broader data clearly indicates that AI’s overall effect on employment is close to zero.

This may be the most concise summary of the current impact of AI on employment.

“Currently, there is no statistically significant correlation between AI and unemployment or employment growth rates.”

At the market level, two trends may coexist: on one hand, talent flows into AI-empowered roles; on the other, AI-replaced roles push out existing workers.

Industries with higher AI-empowerment hiring growth tend to have lower unemployment, while those with higher AI-replacement risks tend to have higher unemployment.

In other words, overall employment remains neutral, but internal structures have shifted: some jobs disappear, others emerge; some roles weaken in value, while others see their worth rise and command premiums. Based on current growth rates, demand for programmers will surpass pre-pandemic levels within two years. AI alone has stabilized the San Francisco office market.

This aligns with our initial view: AI will inevitably eliminate and compress some jobs and industries, but to think that’s all is a mistake. Facing a transformative technology, we should see labor markets rebalancing and ultimately growing, not large-scale unemployment. History has repeatedly proven this pattern, and it’s almost certain to repeat now, with the trend already underway.

Knowledge Work Is Just Beginning

Though this is a well-worn phrase, it’s true: this is not the end of knowledge work, but rather just the beginning.

Automation strips away repetitive, low-level tasks, pushing human labor toward higher-value levels. The logic is simple: humans are inherently driven to expand outward. When a scarcity at one level is broken, people move toward new, higher-level needs. When food costs decline, more spending shifts to housing, healthcare, education, travel, entertainment, convenience, pets, safety, beauty, anti-aging, and more.

The labor market is no different. New careers will continually emerge because human ambition is endless; conquering old domains spurs the birth of new frontiers waiting to be explored.

Currently, new business registrations are exploding, and there is a high correlation with AI deployment.

The number of new applications launched in app stores is growing at a 60% year-over-year rate.

There is no reason to see the modern economy as a museum of old careers. Instead, it’s a creative resource allocation machine, constantly generating new jobs, new work, new goals, and new innovations.

For a long time, robotics was mostly considered science fiction because the computational demands in dynamic environments were too high. Now, AI is turning a new robot industry from concept to reality.

Data sets in robotics are exploding; in just two years, the industry’s ranking jumped from tenth to first place.

Massive numbers of robotics-related jobs previously had no market demand—until AI unlocked this latent need.

Again, I emphasize: none of the above means all existing jobs will survive intact. The U.S. Bureau of Labor Statistics projects roles like customer service reps and medical transcriptionists will shrink, and this decline may already be underway.

Some jobs will disappear; others will shrink. Industry structures will inevitably adjust, and the transition will involve pain. Productivity improvements will gradually permeate the entire economy, often taking time. We should empathize with the shocks this brings and actively promote a smooth transition, including proactive retraining—something a16z is very eager to support.

The purpose of productivity growth is to help humans escape dull, heavy mechanical labor—and this AI revolution will be no different.

But the so-called AI job apocalypse only holds under a ridiculous assumption: that human desires and innovative thinking will come to a complete halt the moment intelligent technology becomes cheap and widespread. That’s obviously nonsense. Personally, I do not buy into the “Wall-E” style passive end-of-days narrative, and I believe many others share this view.

From a macro perspective, the future is not universal unemployment or idleness spent binge-watching streaming media or riding robots all day.

The future looks like this: dramatically lower costs of intelligence, continuous market expansion, new startups emerging, and new industries being born. Humans will engage in higher-level, more creative work. The total amount of work is never fixed, and mental demand is no exception—neither in the past nor in the future. AI is not the end of labor, but the beginning of an era of intelligent inclusivity.