"This is not the Industrial Revolution. Don't believe me? Try this thought experiment . . . and be honest. You are the CEO of a multinational company with 100,000 employees. Rate all of their jobs on a scale from 'lowest' to 'highest' skill. Now consider a near future in which AI and automation have disrupted the bottom 80% of those jobs by skill-level."
"AI hasn't created any new lower-skill jobs because if they fall below the skills threshold then those jobs are in turn automated as well. So ask yourself these questions: will many, if any, of those lower-skilled employees be qualified to fill these new top-20% roles in your company, even with reskilling?"
"Today, how easy is it to recruit for and fill those top 20% positions that already exist in your company? How would that change if you have five, ten, twenty times as many 'top jobs' to fill? And what if we're not talking about the top-20% but the top-1%?"
Current policy assumes university education and programming skills prepare workers for AI-driven disruption, but analysis of 11 million programmers reveals a different reality. Unlike the Industrial Revolution, AI automation eliminates jobs across all skill levels without creating proportional lower-skill replacements. In a hypothetical scenario where 80% of jobs disappear due to automation, companies face a paradox: while high-skill jobs increase five-fold, the displaced workforce lacks qualifications to fill these elite positions. Recruiting for top-tier roles already proves difficult; multiplying these positions exponentially compounds the challenge. Traditional reskilling and university education cannot bridge this gap, suggesting current policy approaches fundamentally misunderstand the nature of AI-driven economic transformation.
Read at Fast Company
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