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The AI labour-market scorecard. What 75%, 30%, and 14% mean for your job.
OSandMac
28 April 2026
The AI labour-market scorecard
Anthropic published its 2026 labour-market findings this month. The headline numbers are blunt. We have read the full report so you do not have to. Here is what matters, and what to do about it.
The three numbers that matter
75% is the share of programmer tasks now within an AI's reach. Customer service and data entry roles round out the top three exposures.
30% is the share of workers in roles with zero AI exposure today. Cooks, motorcycle mechanics, lifeguards, bartenders. Hands, places, presence. AI does not pour drinks, fix bikes, or tile a roof.
14% is the drop in job-finding rate for workers aged 22 to 25 in the most-exposed occupations since late 2022.
Two softer findings worth holding next to those. Workers in the top quartile of AI-exposed jobs earn 47% more on average than the unexposed group. And 17.4% of them hold graduate degrees, against 4.5% in unexposed roles.
The people most exposed to AI are also the ones with the most to lose. And the most to gain.
The split, by category
Computer and Math occupations sit at 94% theoretical AI coverage. Actual usage covers about 33% of those tasks today. The gap between those two numbers is the next two years.
Customer service and data entry are already deeply automated. Anthropic puts data-entry coverage at 67%.
Trades, hospitality, and physical-presence work sit at zero exposure. They are safe today. They are not safe forever in the sense that customers and markets shift around them. But they have time.
Everything in between is a spectrum. Most knowledge work is partly automated, partly augmented.
The question is which half of your week is which.
Three moves to make this quarter
1. Capture what is in your head before AI catches up to it
The workers who stay valuable are the ones whose judgement, taste, and method are documented.
Implied knowledge is what cannot be cloned. Get it out of your head and into structured assets your team owns. This is what we call IP Production. Voice notes become courses. Screen recordings become workflows. Repeated decisions become decision frameworks. The work compounds. The next person you hire ramps in days, not months. The next time the market shifts, you have something to update, not rebuild.
If you want help capturing it: osandmac.com/elearning.
2. Audit your stack before AI does it for you
Most small businesses pay for tools they barely use, miss tools that would save days, and still run workflows that AI now handles in seconds. The question is no longer "what software should we add". The question is "what should we stop doing manually this month".
A focused audit catches it in half a day on the books and gives you weeks back on the calendar. We do this as a service: tech-stack audit, workflow mapping, automation recommendations, and a written plan you can act on without us.
If you want it run on your business, you can also try tools like consolidatemytools.com
3. Train deliberately, not reactively
Knowing macOS is no longer enough. Knowing how to chain a tool to an AI to a calendar to a CRM is the new Mac fluency.
The 22-to-25-year-olds with a 14% job-finding drop are not lazy. They were taught yesterday's stack. We run targeted Mac and software training that puts the fluency back. One-on-one or in small teams. Cape Town in person, anywhere remote. The brief is always the same: less software trivia, more workflow leverage.
If you want it for yourself or your team: osandmac.com/support.
What the report does not say
Anthropic's data shows no systematic unemployment increase for highly exposed workers since late 2022. The story is not collapse. The story is repricing. Roles are being redrawn. The 47% premium for adapted workers is real. So is the floor falling on workers who do not move. The 30% with zero exposure have time. The 70% who are exposed have more upside, but less time.
What to do this week
Pick one of the three moves. Block two hours. Tell your team.