With over half of new startup pitches focusing on AI automating existing jobs, the primary solution to this massive displacement is not retraining, but fostering an ecosystem that aggressively creates new companies, new industries, and consequently, new roles.

Beyond displacing current workers, AI will lead to hiring "abatement," where companies proactively eliminate roles from their hiring plans altogether. This is a subtle but profound workforce shift, as entire job categories may vanish from the market before employees can be retrained.

Former OpenAI scientist Andrej Karpathy posits that once AGI handles most cognitive tasks, education will shift from a professional necessity to a personal pursuit. Similar to how people visit gyms for health and enjoyment despite machines handling heavy labor, learning will become an optional activity for fulfillment.

OpenAI is launching initiatives to certify millions of workers for an AI-driven economy. However, their core mission is to build artificial general intelligence (AGI) designed to outperform humans, creating a paradox where they are both the cause of and a proposed solution to job displacement.

If AI were perfect, it would simply replace tasks. Because it is imperfect and requires nuanced interaction, it creates demand for skilled professionals who can prompt, verify, and creatively apply it. This turns AI's limitations into a tool that requires and rewards human proficiency.

Tech leaders cite Jevon's Paradox, suggesting AI efficiency will create more jobs. However, this historical model may not hold, as the speed of AI disruption outpaces society's ability to adapt, and demand for knowledge work isn't infinitely elastic.

Instead of fearing job loss, focus on skills in industries with elastic demand. When AI makes workers 10x more productive in these fields (e.g., software), the market will demand 100x more output, increasing the need for skilled humans who can leverage AI.

Unlike past technological shifts where humans could learn new trades, AI is a "tractor for everything." It will automate a task and then move to automate the next available task faster than a human can reskill, making long-term job security increasingly precarious for cognitive labor.

By replacing junior roles, AI eliminates the primary training ground for the next generation of experts. This creates a paradox: the very models that need expert data to improve are simultaneously destroying the mechanism that produces those experts, creating a future data bottleneck.