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It’s easy to look at AI’s rapidly expanding capabilities and imagine a future where millions of jobs simply vanish. If a machine can draft a report, write code, design a logo, or answer customer queries in seconds, why would we need as many people? The assumption is that productivity gains will mean fewer human hours required — and therefore fewer jobs.
But history offers a caution against such straight-line predictions. The problem — or perhaps the comfort — lies in a deceptively simple idea first published in 1955: Parkinson’s Law. “Work expands to fill the time available for its completion.” Every wave of productivity technology in the last century has run headlong into it, and AI may prove no different.
The Paperless Office That Used More Paper
Consider the great “paperless office” revolution. With computers, email, and digital file storage, the need for printed documents should have collapsed. In reality, paper consumption soared for decades. Printing became cheaper and easier. Drafts multiplied because editing was instant. Email attachments were printed for meetings. Compliance departments still demanded physical archives. The constraint was gone, but the workload didn’t shrink — it simply expanded in new ways.
Other Historical Rhymes
The pattern repeats across technologies:
- PCs replacing typing pools freed managers to type their own documents — and they produced far more memos and revisions.
- Household appliances cut the labour time for individual chores — but people cleaned more often, raised cleanliness standards, and bought larger homes.
- Faster transport could have shortened commutes — instead, people moved farther away, keeping travel time the same.
- Email replacing letters removed the wait — and unleashed inbox overload.
In each case, efficiency gains didn’t translate into a proportional drop in total human effort. They often led to more work — just of a slightly different kind.
AI’s Dual Effect: Acceleration and Unlocking
With AI, the dynamic will be even stronger because there’s a second force at play beyond Parkinson’s Law: the unlock effect.
Some tasks were once too costly, time-consuming, or complex to be worth doing at all. AI changes that calculus. Suddenly, it’s viable to:
- Personalise every marketing message to every customer.
- Analyse every dataset from every angle before making a decision.
- Generate hundreds of design variations “just in case one works better.”
- Offer 24/7 real-time, tailored customer service across dozens of languages.
- Interpret advanced medical imaging and genetic tests instantly, making them viable for far more cases.
- Run full blood panels and predictive health screenings at scale, expanding diagnostics from rare, high-risk patients to routine population-wide use.
These weren’t human jobs before — they didn’t exist, or they existed only in narrow, high-value contexts. AI makes them affordable and scalable, and organisations will create them simply because they can. It’s the same reason digital photography exploded in volume: when each shot cost nothing, people took thousands more pictures.
Why Job Loss Is Not the Automatic Outcome
Put Parkinson’s Law and the unlock effect together, and the story changes:
- Displacement is real. Certain roles will shrink or disappear. AI can already automate routine legal drafting, basic customer support, and entry level coding.
- But total human workload may not fall. Freed-up capacity often gets redirected into either doing more of the same or doing new things that were previously out of reach.
- Some industries may even expand headcount. If AI lets a small firm offer global customer support, it might need more salespeople, more compliance staff, and more engineers to handle the resulting growth.
Historically, technology waves — from mechanised looms to spreadsheets — have eliminated certain roles while creating others. The net effect on jobs has varied, but outright collapse of employment has never been the default outcome. AI is faster and broader, but it’s still hitting the same human and organisational tendencies that have blunted efficiency gains for decades.
The Real Risk Isn’t No Jobs — It’s Different Jobs
The danger is not that there will be nothing for humans to do, but that the work available will change shape faster than people and institutions can adapt. If AI automates a lawyer’s routine filings, that lawyer may spend more time on complex cases, client counselling, or cross-border negotiations — but only if they’ve been trained and positioned to shift into those areas.
At the macro level, the question is not “Will AI cause mass unemployment?” but “Will workers be able to move quickly enough into the new roles AI makes possible?” Displacement without reskilling could still cause pain, even if total job numbers hold steady or rise.
What Jobs Could AI Make Possible?
If we follow history’s lessons, AI won’t just replace tasks — it will invent work we couldn’t justify doing before. Some of these are already taking shape:
- Mass-scale personalisation — from tailoring marketing to each individual to designing unique educational content for every student.
- Micro-market services — products and services for tiny niche audiences that weren’t profitable before AI cut production costs.
- Hyper-local journalism — AI can help gather, analyse, and present community-level data that was too time-intensive for traditional newsrooms.
- Ultra-responsive customer support — humans supervising AI agents that handle the first contact, focusing on empathy, escalation, and complex resolutions.
- Virtual world design — creating training simulations, digital spaces and immersive content at a fraction of previous costs.
- Always-on monitoring — from environmental sensors to supply chains, with humans interpreting and acting on AI-generated alerts.
- Decision-support specialists — experts who translate AI’s analytical output into strategy, policy, or creative direction.
These aren’t just “old jobs done faster.” They’re new lines of work that were previously impractical because of time, money, or complexity. AI lowers those barriers — and once the barriers fall, history shows we almost always rush in to fill the space.
The challenge, then, is less about whether there will be jobs, and more about whether we can train, adapt, and move people into them fast enough. AI’s real revolution may not be in replacing human labour — but in reshaping it into forms we haven’t yet imagined.
These pieces are being published as they have been received – they have not been edited/fact-checked by ThePrint.