Billionaire investor Mark Cuban has some counterintuitive career advice for job seekers entering the AI era: forget the big tech giants and look at small businesses instead.

Why Small Companies Need AI Skills More

Cuban is steering both of his children and anyone starting their career toward small and medium-sized businesses rather than corporate behemoths, arguing that artificial intelligence is fundamentally reshaping where opportunities exist. The reason? Smaller companies don't have massive IT departments, which means someone with AI skills can actually make a noticeable difference.

The numbers back this up. More than half of U.S. small businesses now use AI, representing a doubling of adoption since 2023. That rapid growth is creating serious demand for people who can actually implement these tools.

Making an Immediate Impact

Cuban explained that entrepreneurially minded smaller companies can benefit immediately from hiring recent graduates who know how to create AI tools that automate processes and boost both productivity and profitability. It's about driving real business results, not just sitting in a department studying algorithms.

He's practiced what he preaches. Cuban previously pointed to his company, Cost Plus Drugs, as an example of how AI-driven automation can make a business more competitive. Meanwhile, he warns that large corporations already have deep AI expertise in-house, which means fewer opportunities for newcomers to stand out.

The Data Supports His Argument

A report from the Massachusetts Institute of Technology confirms Cuban's perspective: 95% of companies haven't yet seen measurable revenue from their AI investments, with early-stage startups actually leading in returns.

The takeaway is that AI is leveling the playing field, letting small businesses compete by automating tasks and innovating more efficiently. That's creating demand for AI-savvy entry-level employees who can execute, not just theorize.

Cuban's bottom-line advice to his kids and other young workers? Focus on actually using AI in real business processes rather than just studying it academically. In other words, go where you can build things and see results.