Why AI Has to Create Jobs—or Fail Spectacularly

Imagine graduating college in 2025 and finding that every entry-level job you’re qualified for has been automated. The data entry positions? Gone. Basic customer service roles? Handled by chatbots. Junior coding tasks? AI writes better code than most humans. This isn’t dystopian fiction—it’s happening right now.

You hear a lot these days about how AI is going to change everything. It’s going to cure diseases, write code faster than any human, and maybe even make art that’s indistinguishable from the real thing. But here’s the thing: AI is systematically eliminating entry-level jobs—the traditional gateway into careers—and if it doesn’t create new pathways for people to enter the workforce and progress economically, then the whole enterprise is going to look like a massive failure. Not a technical failure—I’m sure the models will keep getting smarter—but a failure in the way that matters most: how it shapes society and economic mobility.

The Historical Pattern

Think about past technologies. The Industrial Revolution wiped out a lot of manual labor jobs, but it created factories, railroads, and eventually entire new industries like automobiles and aviation. Computers automated paperwork and calculations, but they spawned software engineering, web design, and data analysis roles that no one could have imagined in the 1950s.

The pattern is clear: big tech shifts displace workers in the short term, but they succeed when they generate net new opportunities. AI has to follow that script, or we’re in trouble.

The Entry-Level Crisis

Right now, the displacement side looks scary. AI is already automating routine tasks in manufacturing, data entry, customer service, and even some creative fields. Entry-level jobs are vanishing as tools handle what used to be human work.

Recent reports show that 14% of workers have already been displaced by AI, with the hit landing hardest on younger and mid-career folks in tech and creative sectors. Economists are estimating that 6% to 7% of U.S. jobs could be fully replaced if AI keeps rolling out widely.

But it’s not inevitable doom. If done right, AI could free people up for more interesting roles—things like overseeing AI systems, designing ethical frameworks, or building entirely new businesses around personalized tech. The industry needs to invest in that transition: retraining programs, new skill development, and incentives for companies to create rather than just cut.

Without it, we’ll end up with widespread unemployment, where the gains go to shareholders while everyone else struggles.

Economic Velocity Matters

It’s not just about jobs, though. AI has to make the economy hum more efficiently, getting money to flow faster and more broadly. Velocity of money—the speed at which dollars change hands—matters because a stagnant economy where wealth piles up at the top kills growth.

AI could supercharge this by optimizing supply chains, predicting trends, and enabling quicker, smarter transactions. It might boost productivity across sectors like banking, retail, and healthcare, creating ripple effects that lift everyone.

The Inequality Trap

The catch? Without careful design, AI will widen inequality. The benefits could flow mostly to those who own the tech or have the skills to use it, leaving others behind. In developing countries, lack of infrastructure might mean they miss out entirely, exacerbating global divides.

We’ve seen this with previous tech waves: innovation drives growth, but if the spoils aren’t shared, it leads to polarization.

The Stakes

If AI flops on these fronts, the consequences are grim. Widespread job loss without replacements means lower consumer spending, which creates a vicious cycle—even AI companies suffer when markets shrink. Add in social unrest, strained governments, and a growing gap between haves and have-nots, and you have a recipe for trouble.

It could turn society more feudal, with a tech elite on one side and everyone else on the other.

The Path Forward

The AI industry can’t just optimize for shareholder returns. It needs to build ecosystems that recirculate value—through open tools, education initiatives, or policies that distribute productivity gains.

Fresh data from this year’s reports suggests that when companies think big with AI—using it to enhance rather than just automate—job creation can outpace displacement. If it does, AI could be the biggest boon since electricity. If not, it’ll be remembered as the tech that promised the moon but delivered a crater.

The choice is ours, but the clock is ticking.

What do you think? Share this with your network and let’s start the conversation about building AI that works for everyone.

Gavin Guo (国振)