Insider Brief
- Studies show that artificial intelligence is shifting economic rewards from workers toward owners of capital, data, and intellectual property.
- A 2024 PLOS ONE study finds that industries adopting AI see income shares tilt away from labor and toward capital, while cross-country research links AI deployment with rising wealth inequality.
- U.S. labor market data from 2015–2023 reveal that workers in high-automation-risk jobs face higher unemployment risk and are more likely to move into self-employment, often through small, necessity-driven ventures.
- The ultimate advice: If your boss can replace you with AI, you can replace your boss with AI.
Artificial intelligence (AI) is shifting rewards from workers to owners, and new studies suggest that becoming an “owner” rather than an “employee” may be the surest way to survive an AI-dominated workforce.
According to research, AI is tilting the balance of economic rewards from labor toward capital. Instead of wages rising with productivity, a growing body of research shows that returns from AI flow to those who own the technology, the data, and the intellectual property that make it run.
In this landscape, becoming an AI-powered “owner” rather than an AI-replaced “employee” may be the surest way to secure a future. To be even more direct: If your boss can replace you with AI, you can replace your boss with AI.
Why Workers Need a Strategy
It’s becoming clear that AI will almost certainly have an effect, if not a significant effect, on the workforce. Whether that will be positive, or negative is a question that scientists and economists are grappling with now. Likely, the effect will be both positive and negative, depending on where a person falls on
A 2024 study in PLOS ONE finds that when industries adopt AI, the share of income going to capital owners rises while the share going to workers falls. That means the biggest winners are not those doing the work but those who control the assets that AI makes more valuable.
Reinforcing that trend, researchers writing in Technological Forecasting & Social Change report a statistically significant link between AI capital accumulation and widening wealth inequality across countries. In plain terms, the more AI a country deploys, the more its wealth tilts toward the already wealthy.
The economic consequences could be stark, according to a recent Scientific Reports paper. The researchers modeled the Australian economy projects that even modest increases in the AI-capital-to-labor ratio could double labor under-utilization by mid-century, while reducing disposable incomes. In such a scenario, traditional employment is less reliable as a path to security, and ownership of productive assets becomes the buffer.
Crafting an Ownership Strategy
One way to deal with this labor competition with AI is to move up the capital chain — and workers seem to be moving toward ownership, rather than employment to deal with the change. A 2025 PLOS ONE study of U.S. labor markets shows that employees in occupations with higher automation risk are significantly more likely to move into entrepreneurship.
When faced with shrinking opportunities as wage earners, they increasingly opt to become self-owners, carving out new paths in an economy reshaped by machines.
The researchers tracked nearly 1.4 million monthly observations of U.S. workers between 2015 and 2023 and found a consistent pattern: the greater the automation risk of an occupation, the higher the chance its workers would become unemployed or shift into self-employment.
According to the paper, a A meaningful jump in automation risk — enough to move an occupation from average to higher-risk — in automation risk raised the likelihood of unemployment by about 36 percent. At the same time, the probability of workers moving into unincorporated self-employment — a proxy for necessity-driven entrepreneurship — rose by roughly 26 percent. These businesses tend to be small, informal, and survival-oriented, suggesting that entrepreneurship in this context is less a bold opportunity than a fallback strategy.
The study also found that the type of automation technology matters. Occupations exposed to industrial robots were more likely to see both unemployment and necessity entrepreneurship. On the other hand, exposure to AI was linked with lower unemployment and reduced necessity entrepreneurship, pointing to a more complementary relationship between human skills and AI systems. Gender differences were also a factor, the researchers report: men in automation-prone jobs were more likely than women to make the leap into entrepreneurship, reflecting wider disparities in risk tolerance and access to resources.
The early months of the COVID-19 pandemic amplified these dynamics. As companies rushed to automate for safety and efficiency, workers in high-risk occupations faced sharper displacement and turned to self-employment at higher rates. By 2022, the trend moderated as the labor market stabilized, but the evidence highlights how sudden shocks can accelerate shifts from employee to ownerjournal.pone.0331244.
The implication, fortunately, is that workers do not passively accept displacement — they adapt by becoming owners of their labor and, in limited ways, of their businesses. But because this shift often results in precarious, necessity-driven ventures rather than scalable enterprises, it also raises questions about whether “ownership” in an AI economy will deliver stability or merely replace one form of insecurity with another.
Preparing for an Ownership Economy
If automation risk pushes workers out of wage jobs and into necessity-driven ventures, the question becomes what workers can do now to avoid being trapped in precarious self-employment. Economists argue that the difference between vulnerable gig work and resilient ownership often comes down to how much control an individual has over capital, networks, and rights.
Build Equity, Not Just Income
Income alone will likely not be enough. Workers should look for ways to gain stakes in what they create—stock, co-op shares, or intellectual property. Even small stakes can matter. Company stock programs let employees share in firm growth. Cooperative shares give workers a slice of the enterprise rather than just a paycheck.
Equity is more than just buying stock and receiving dividends. Although, it’s not necessarily classified as equity, intellectual property — patents, code, data, or creative works — can generate licensing income long after the original work is done. Platforms and digital ventures that allow contributors to hold tokens or equity stakes are emerging as another path. Each of these models shifts workers from pure labor to partial ownership, creating a cushion against wage shocks.
Develop Complementary Skills
The PLOS ONE study shows robot exposure pushes workers into unemployment and necessity businesses, while AI exposure is more likely to preserve jobs.
Workers should train toward skills machines cannot easily replace—analysis, judgment, design, and interpersonal work. Certifications in data analysis, project management, or design thinking can keep careers aligned with AI rather than competing with it. Workers in manufacturing-heavy sectors should prepare for robot risk by cross-training into roles that supervise, program, or maintain automated systems.
Start Small Ventures Early
Most displaced workers turn to necessity businesses after the fact. Starting early makes a difference. Side hustles — whether consulting, e-commerce, or creative projects — can be incubated while still employed. Workers can test market demand, build customer bases, and learn basic business skills before displacement forces their hand. Over time, these ventures can evolve into opportunity-driven firms with real growth potential, rather than survival-only shops.
Think Collective
Ownership does not have to be solo. Employee stock ownership plans (ESOPs) and worker co-ops allow groups to pool resources and share in profits. Platform cooperatives are emerging in sectors from ride-hailing to creative work, offering alternatives to being just another gig worker. These structures spread risk and give workers leverage in markets that tilt toward capital. For those without the means to launch a business on their own, collective ownership offers a way into the ownership economy.
Push For Safety Nets
Reskilling programs, portable benefits, and microfinance can soften the landing. Some states already fund retraining in coding, cybersecurity, and clean energy trades. Portable health and retirement benefits make it easier for workers to leave jobs without losing protections. Microloans and community finance programs can help necessity entrepreneurs survive the fragile first years. Workers should track what is available locally and push for more, since these supports often determine whether entrepreneurship is a springboard or a dead end.
Creating the Ownership Mindset
Preparing for automation is not only about skills or side hustles. Most of this transition will require a shift in mindset from being a worker to being an owner. Bluntly: Workers raised to think of themselves as employees must start to think like owners.
That begins with viewing wages as one stream of income, not the whole picture. Owners look for ways to convert labor into assets — stock, intellectual property, or business equity — that continue to produce value after the work is done.
Owners also think in terms of risk and return. Taking a stake in a company or launching a venture carries risk, but so does relying on a job that may not exist tomorrow. The ownership mindset treats risk as something to manage, not avoid.
Another aspect of the ownership mindset is that owners plan long term. They invest in networks, reputation and knowledge that compound over time. Where employees ask “what will my paycheck be this month,” owners ask “what will this asset be worth in five years.”
Shifting to this shift does not require quitting a job tomorrow. It requires reorienting how workers see their role in the economy: not as labor rented out, but as capital built and grown.
Learning to Use AI as an Owner
One final step on this journey to ownership is to shake the fear of AI. And that’s easier said than done in this environment, especially when confronted with “AI Replaces Jobs” headline on every other social media post. Workers who treat AI only as a competitor risk missing its potential as a tool. The same technology that replaces some tasks can also lower barriers to entrepreneurship.
AI tools already draft code, generate designs and handle back-office tasks that once required a full staff. For necessity entrepreneurs, that means lower startup costs and faster execution. For workers with equity in a company, it means greater productivity and more leverage.
The key is not to resist AI but to master it. Learning how to integrate AI into daily work—whether automating invoices, running marketing campaigns, or analyzing data—can turn a displaced worker into a lean owner. Those who control the tools, rather than avoid them, are better positioned to capture value.
In practice, this means approaching AI the way an owner would: not asking “will this replace me?” but “how can I use this to grow my stake?” Workers who adopt that stance move from being at risk to being in control.
