Industries with fixed demand (accounting) will see job losses as AI handles the necessary workload. Sectors with expandable demand (software engineering) may absorb AI's productivity gains by creating vastly more output, thus preserving jobs for a longer period.

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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.

The primary economic incentive driving AI development is not replacing software, but automating the vastly larger human labor market. This includes high-skill jobs like accountants, lawyers, and auditors, representing a multi-trillion dollar opportunity that dwarfs the SaaS industry and dictates where investment will flow.

Increased developer productivity from AI won't lead to fewer jobs. Instead, it mirrors the Jevons paradox seen with electricity: as building software becomes cheaper and faster, the demand for it will dramatically increase. This boosts investment in new projects and ultimately grows the entire software engineering industry.

AI makes tasks cheaper and faster. This increased efficiency doesn't reduce the need for workers; instead, it increases the demand for their work, as companies can now afford to do more of it. This creates a positive feedback loop that may lead to more hiring, not less.

AI will primarily threaten purely cognitive jobs, but roles combining thought with physical dexterity—like master electricians or plumbers—will thrive. The AI-driven infrastructure boom is increasing demand and pushing their salaries above even those of some Silicon Valley engineers.

The narrative of AI destroying jobs misses a key point: AI allows companies to 'hire software for a dollar' for tasks that were never economical to assign to humans. This will unlock new services and expand the economy, creating demand in areas that previously didn't exist.

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.

Companies are preemptively slowing hiring for roles they anticipate AI will automate within two years. This "quiet hiring freeze" avoids the cost of hiring, training, and then laying off staff. It is a subtle but powerful leading indicator of labor market disruption, happening long before official unemployment figures reflect the shift.

The real inflection point for widespread job displacement will be when businesses decide to hire an AI agent over a human for a full-time role. Current job losses are from human efficiency gains, not agent-based replacement, which is a critical distinction for future workforce planning.

The Jevons Paradox observes that technologies increasing efficiency often boost consumption rather than reduce it. Applied to AI, this means while some jobs will be automated, the increased productivity will likely expand the scope and volume of work, creating new roles, much like typewriters ultimately increased secretarial work.

AI Will Disrupt Jobs in Inelastic Markets Like Accounting Before Elastic Markets Like Software | RiffOn