Everyone is mapping which jobs AI will destroy. Nobody is mapping what comes next. That asymmetry is making us stupid about the future. Here's an attempt to fix that.

TDLR:

• The Hidden Assumption 🔍

• Six Ways Demand Expands

• The Human Premium 🤝

• Healthcare: A Case Study 🏥

• The New Job Families 💼

• The Bro's Take 🤔

Every AI jobs apocalypse narrative rests on the same flaw.

AI increases the supply of labour, so workers get displaced. But that assumes demand stays constant. It never has.

Not once in the history of major technological shifts. The lump of labour fallacy has been wrong every single time.

The right question isn't which jobs disappear. It's where demand expands next.

AI doesn't just make things cheaper. It unlocks demand in at least six distinct ways.

Price elasticity: things people wanted but couldn't afford. Access elasticity: things people wanted but couldn't reach. Complexity elasticity: things people needed but couldn't navigate.

Continuity elasticity: things people would benefit from having always on. Personalisation elasticity: things people want made for them specifically. Relational elasticity: things people want to feel human.

Each of these is a category of net new demand. Not the same pie, sliced differently. A bigger pie entirely.

Here's the answer to the AGI objection. Won't stronger AI just eat the new jobs too?

Not the ones protected by what I'd call the human premium.

Seven categories of value that don't automatically transfer when you remove the human: relationship, embodied presence, trust, accountability, translation, behaviour change, and provenance.

AGI can perform tasks. It can't always satisfy the demand behind them. People want someone who knows them, someone they can hold accountable, someone whose involvement makes the service feel real.

Healthcare has every type of demand elasticity simultaneously. It's the clearest example of what AI-unlocked job creation actually looks like.

A continuous preventative care model becomes viable when AI handles data collection, monitoring, triage, and documentation. That creates net new human roles that didn't exist before.

Continuous care navigators managing flagged cases and patient relationships. Care plan outcome specialists bridging medical advice and real-world execution. Health data operations specialists owning the integrity of the data layer.

Conservative estimates put continuous care navigators alone at 270,000 to 1.2 million new US jobs. That's the scale of high school teaching as a profession.

The New Job Families 💼

Zoom out and the same patterns appear across healthcare, legal, education, mental health, and personal finance.

Six broad job families emerge. Navigators helping people move through complex systems.

Continuous support workers providing the human layer around AI monitoring. AI-augmented service operators delivering professional services to markets that couldn't afford them before.

Data and ops specialists keeping AI-enabled services reliable. QA and compliance roles ensuring safety and accountability. Escalation specialists handling the hardest cases AI routes upward.

None of these are prompt engineering jobs. They're service jobs made possible by AI.

The AI jobs debate is stuck because it's only asking one question: can AI do this task?

The better question is whether AI delivery alone satisfies the demand. In most cases that involve trust, relationships, accountability, or human presence, it doesn't.

More AI means more supply. More supply changes cost structures. Changed cost structures unlock demand that didn't exist before. More demand means more work. That's not optimism. That's economics.

And that's it for today! Thanks for reading ♥️

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