Madiha Yaqoob
AI training is still widely described as entry-level clickwork, and for a large slice of the market that description is now out of date. Deel’s analysis of more than one million worker contracts across 37,000 companies found that general AI trainer roles grew 283% cross-border during 2025, with the occupation spanning over 70,000 workers at more than 600 organizations and hourly pay running from $15 to $75. The distance between the bottom and the top of that range is not seniority or tenure. It is whether you bring subject expertise a model cannot extract from an annotation guideline.
The two tiers, and what separates them
The lower tier is volume annotation. You label images, rank two model responses against a rubric, flag unsafe outputs, transcribe audio. The instructions are written for you, throughput is measured, and the work is deliberately designed so that any careful person can do it after a short onboarding. That design is the point, and it is also the ceiling.
The upper tier is expert evaluation. Deel’s report describes trainers working in economics, medicine and translation, and characterises the occupation as ranging from basic annotators through to subject matter experts. Here the labs are not paying for your attention. They are paying for a judgment they cannot get anywhere else: whether a model’s clinical reasoning is defensible, whether a legal summary misstates the standard, whether an Urdu translation carries the register a native speaker would use.
Nobody moves from the first tier to the second by doing more of the first. The two are recruited through different channels and screened on different evidence.
Where the hiring is concentrated
Deel’s data puts 58.2% of AI trainers in the United States, the largest single concentration by a wide margin. The rest of the top six hiring countries are India, the Philippines, Canada, Kenya and Nigeria.
Pakistan does not appear in that list, and the omission is informative rather than discouraging. India and the Philippines built their positions on established outsourcing infrastructure and a long history of English-language contract delivery. Kenya and Nigeria arrived more recently through data-annotation firms that recruit locally at scale. All four routes are institutional. They ran through companies, not through individuals applying one at a time.
For a Pakistani professional the realistic entry is therefore direct rather than intermediated, which means the qualifying credential has to be visible on your own profile. We have looked separately at which AI training platforms actually accept Pakistani workers, and the practical constraint there is usually payment rails and identity verification rather than skill.
What counts as subject expertise here
This is where people misjudge themselves in both directions. You do not need a doctorate. You do need a domain where you can defend a judgment call in writing and be right more often than a well-read generalist.
Qualifying backgrounds that people routinely undersell: a pharmacy or nursing qualification, an LLB with practice experience, an ACCA or CA part-qualification, a civil or mechanical engineering degree with site experience, a genuinely native command of a language the labs are short of. Urdu, Punjabi, Pashto and Sindhi all sit in that last category, and translation is one of the three domains Deel names explicitly.
What does not qualify is broad familiarity with AI tools. Knowing how to prompt well is now assumed, not differentiating. The premium attaches to knowledge from outside the AI industry that the industry needs and cannot generate internally.
Is annotation work still worth doing?
For most people, yes, but as a bridge rather than a destination. It pays in dollars, it is genuinely accessible, and it teaches you how evaluation rubrics are constructed, which is directly useful when you later apply for expert work. Our earlier walkthrough of how RLHF and data labelling work pays out in practice covers that entry route in detail. Treat six months of it as paid training and it is a good deal.
Treat it as a career and the arithmetic turns against you. It is priced to be replaceable, the rate does not compound with experience, and it is the exact category of work that platform data shows is being compressed. Upwork’s second quarter 2026 results recorded gross services volume of $966.4 million, down 4% year over year, while AI-related work grew more than 22% and the AI Strategy and Consulting sub-category grew over 50%. The marketplace is not shrinking so much as reallocating, away from work that can be specified in a paragraph.
Moving from the first tier to the second
Three things do most of the work here.
Lead with the domain, not the AI. An application that opens with four years in hospital pharmacy will be read differently from one that opens with experienced in AI data labelling. The labs have no shortage of the second and a persistent shortage of the first.
Produce a written artefact that demonstrates the judgment. Take five model responses in your field, write a page on where each one is wrong and why a practitioner would notice, and attach it. This is the single highest-leverage thing you can do and almost nobody does it.
Apply where expert programmes actually recruit: directly with the AI labs, with the specialist evaluation vendors they contract, and through academic and professional networks in your own field. General freelance platforms are the weakest channel for tier-two work, though they remain a reasonable place to build a track record first.
A pay disparity worth naming
Deel’s US figures show male AI trainers typically earning around $20 per hour more than female counterparts, and the gap persists even in fields such as psychology where women are the majority of trainers. That is a finding about the market, not about capability, and it is worth knowing before you negotiate.
The practical response is the same one that works against underpricing generally: know the published range before the conversation, anchor to the expertise rather than to hours, and do not let a first-offer rate set your expectations for the next contract. The broader pattern that specialists are out-earning generalists holds here as sharply as anywhere.
What this means if you already hold a qualification
AI training has quietly become two occupations sharing one job title. One is accessible, honest, capped, and shrinking in real terms. The other pays multiples more, is recruited on credentials from outside the technology industry, and is expanding fast enough that labs are hiring across 600 organizations to fill it. If you already hold a professional qualification in medicine, law, finance, engineering or a language, you are closer to the second than to the first, and you are probably applying to the wrong one.
