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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.

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—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

The Industrial Revolution wiped out manual labor jobs but created factories, railroads, and entire new industries. Computers automated paperwork but spawned software engineering, web design, and data analysis roles. 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

AI is already automating routine tasks in manufacturing, data entry, customer service, and even some creative fields. Entry-level jobs are vanishing. 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.

But it’s not inevitable doom. If done right, AI could free people up for more interesting roles—overseeing AI systems, designing ethical frameworks, or building entirely new businesses. 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. AI has to make the economy hum more efficiently, getting money to flow faster and more broadly. Velocity of money 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.

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. 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.

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. 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.

If you’re building something or navigating your own path, I’m always open to conversations: zguo0525@berkeley.edu.

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Gavin Guo (国振)