Key findings
- 1
33 platforms listed the 238 open roles in Data Annotation & Labeling; RWS TrainAI Community held 49 of them (20.6%) and the three largest 105 (44.1%) (HHI 930, unconcentrated, against 522 for all AI training work).
- 2
172 of the 238 open roles in Data Annotation & Labeling (72.3%) stated an hourly rate, with a median of $30/hr (typical pay $15 to $100), 25% below the $40/hr of all AI training work.
- 3
Each open role in Data Annotation & Labeling drew 12.61 apply clicks a week on AITraining.jobs, 3.70x the average AI training role: the highest of 12 kinds of work whose demand reads on its own.
- 4
45 of the 238 open roles in Data Annotation & Labeling (18.9%) accepted applicants from any country, against 18.5% of all AI training roles; of the 20 countries compared, residents of the United States (154), India (93) and the United Kingdom (81) could apply to the most, and residents of Palestine to the fewest (64).
- 5
The words used most in the titles of open roles in Data Annotation & Labeling were Evaluator or reviewer (68), Annotator or labeler (63) and Specialist (45), of 238 open roles.
- 6
Of the 217 open roles in Data Annotation & Labeling with a full description, 21 (9.7%) mention a PhD or master's degree, 45 (20.7%) a professional credential and 30 (13.8%) an assessment or test; the 36 stating years of experience ask for a median of 2 years.
- 7
Over the 31 days from 1 Oct 2026 to 31 Oct 2026, platforms listed 69 new roles in Data Annotation & Labeling and removed 87, and a removed role had been listed for a median of 47 days (30 across all AI training work).
- 8
Within Data Annotation & Labeling, roles listed during the window drew 5.42 apply clicks per role a week, against 17.28 for roles listed more than 12 weeks before the window.
Figure 1
Open roles, week by week
Is the number of open roles in Data Annotation & Labeling rising or falling?
| Week | Open roles (fixed panel) | Index |
|---|---|---|
| 1 to 4 OctPartial week | 120 | 102.2 |
| 5 to 11 OctPartial week | 117 | 100.0 |
| 12 to 18 OctPartial week | 112 | 88.9 |
| 19 to 25 OctPartial week | 108 | 85.7 |
| 26 to 31 OctPartial week | 105 | 83.3 |
Sample. Average open roles in Data Annotation & Labeling over each week's days, on the 18 platforms tracked since 1 Oct 2026 (the fixed panel; 15 of them list this work), 1 Oct 2026 to 31 Oct 2026.
The index is the panel's open roles against the week of 5 Oct 2026 (100), chained week to week, beside the same index for all AI training work on the same platforms.
This site changed how it reads 5 platforms' boards in this span (Alignerr on 14 Oct 2026; OpenTrain AI on 14 Oct 2026; Handshake AI on 14 Oct 2026; Prolific on 18 Oct 2026; Outlier (Scale AI) on 30 Oct 2026). From each change to the end of its week the roles that came into view are counted as already listed, not as new listings, and the roles that left view are not counted as removals; changes in open roles are measured like for like across it, on the roles that did not move with it. Each platform's own report says what changed.
Perle Labs (first tracked 10 Oct 2026), SuperAnnotate (SME) (first tracked 10 Oct 2026), Turing (first tracked 10 Oct 2026), RemoExperts (first tracked 10 Oct 2026), Vetto (first tracked 14 Oct 2026), OneForma (first tracked 14 Oct 2026), Claru (first tracked 14 Oct 2026), Weekday (first tracked 18 Oct 2026), Innodata (first tracked 18 Oct 2026), Rise Data Labs (first tracked 18 Oct 2026), Volga Partners (first tracked 18 Oct 2026), Lifted (Upwork) (first tracked 18 Oct 2026), TELUS Digital AI (first tracked 22 Oct 2026), DATAmundi (first tracked 22 Oct 2026), Shaip (Collaborate by Shaip) (first tracked 22 Oct 2026), Sama (first tracked 22 Oct 2026), RWS TrainAI Community (first tracked 22 Oct 2026) and Cohere (first tracked 25 Oct 2026) list this work but were added to the dataset later, so they are left out of the panel and counted only in the last column: a platform's arrival never reads as growth.
Every week is marked: the kind's change differs no more than chance from the rest of AI training work's, so its weeks do not read on their own.
Source. AITraining.jobs Research, The Market for Data Annotation & Labeling Work, October 2026 edition.
Figure 2
Listings added and removed
How fast do roles in Data Annotation & Labeling turn over, and is the stock growing on the same platforms?
| Work | Open on 1 Oct 2026 | Open on 31 Oct 2026, same platforms | Change | New listings |
|---|---|---|---|---|
| Data Annotation & LabelingSmall sample | 120 | 104 | -13.6% | 69 |
| All AI training work | 2,665 | 2,554 | -4.2% | 1,638 |
Sample. Roles listed from 1 Oct 2026 to 31 Oct 2026: 356 in Data Annotation & Labeling, 7,396 across all AI training work.
Change compares the roles open on the first and the last day of the window on the platforms tracked when it opened, so a platform added during the window does not read as growth.
The kind's change is marked: it differs no more than chance from the rest of AI training work's.
A new listing first appeared in the window on a platform already tracked before that week; a platform's first week (its back catalogue) is not counted.
Median days listed runs from a removed role's listing date to its last sighting, for removed roles with a known listing date (at least 3; 77 here).
Source. AITraining.jobs Research, The Market for Data Annotation & Labeling Work, October 2026 edition.
Figure 3
Who lists it
Which platforms list roles in Data Annotation & Labeling, and what does each advertise?
| Platform | Open roles | Share of open roles | Median per hour |
|---|---|---|---|
| RWS TrainAI Community | 49 | 20.6% | n/a |
| Welo Data | 36 | 15.1% | $30 |
| Alignerr | 20 | 8.4% | $40 |
| Innodata | 15 | 6.3% | $15 |
| micro1 | 15 | 6.3% | $30 |
| Turing | 15 | 6.3% | n/a |
| Claru | 10 | 4.2% | $30 |
| TELUS Digital AI | 10 | 4.2% | $35 |
| Rise Data Labs | 8 | 3.4% | $30 |
| SuperAnnotate (SME) | 8 | 3.4% | n/a |
| OpenTrain AI | 6 | 2.5% | $10 |
| OneForma | 5 | 2.1% | n/a |
| Braintrust | 4 | 1.7% | $25 |
| Mercor | 4 | 1.7% | $55 |
| TransPerfect DataForce | 4 | 1.7% | n/a |
| DATAmundi | 3 | 1.3% | n/a |
| Handshake AI | 3 | 1.3% | n/a |
| Invisible | 3 | 1.3% | n/a |
| RemoExperts | 3 | 1.3% | n/a |
| Appen | 2 | 0.8% | n/a |
| Lifted (Upwork) | 2 | 0.8% | n/a |
| Terac | 2 | 0.8% | n/a |
| AfterQuery | 1 | 0.4% | n/a |
| Cohere | 1 | 0.4% | n/a |
| Outlier (Scale AI) | 1 | 0.4% | n/a |
| Perle Labs | 1 | 0.4% | n/a |
| Prolific | 1 | 0.4% | n/a |
| Remotasks | 1 | 0.4% | n/a |
| Sama | 1 | 0.4% | n/a |
| Shaip (Collaborate by Shaip) | 1 | 0.4% | n/a |
| Vetto | 1 | 0.4% | n/a |
| Volga Partners | 1 | 0.4% | n/a |
| Weekday | 1 | 0.4% | n/a |
Sample. 238 roles in Data Annotation & Labeling open at the end of 31 Oct 2026, by the platform that lists them: HHI 930 (unconcentrated), against 522 for all AI training work.
HHI: the sum of every platform's squared percentage share of the open roles, 0 to 10,000; under 1,500 is unconcentrated, 1,500 to 2,500 moderately and above 2,500 highly concentrated (US merger-guideline thresholds).
Shares are of listings, not of people hired or money paid: a platform posting one role per language or country weighs more here than its hiring may.
A median needs at least 3 roles stating an hourly rate.
Source. AITraining.jobs Research, The Market for Data Annotation & Labeling Work, October 2026 edition.
Figure 4
What it pays
What do roles in Data Annotation & Labeling advertise per hour, against AI training work as a whole?
| Work | Median per hour | Typical pay from | Typical pay to | Stating an hourly rate |
|---|---|---|---|---|
| Data Annotation & Labeling | $30 | $15 | $100 | 72.3% |
| All AI training work | $40 | $30 | $125 | 81.4% |
Sample. Roles open on 31 Oct 2026: 238 in Data Annotation & Labeling, 172 of them stating an hourly rate; 4,381 across all AI training work.
Pay is the hourly figure a posting advertises (the middle of a stated range), counted once per distinct rate as the job board counts it. The median and typical pay are the board's: typical pay runs from the 25th percentile of what roles pay (the middle of each advertised range) to the 90th-percentile advertised ceiling, stated from 3 distinct rates.
Roles paid per task or per project, or that state no figure, do not state an hourly rate.
Source. AITraining.jobs Research, The Market for Data Annotation & Labeling Work, October 2026 edition.
Figure 5
How its rates are distributed
What share of roles in Data Annotation & Labeling pay $50 an hour or more?
| Advertised rate | Open roles | Share of priced roles | All AI training work |
|---|---|---|---|
| Under $15/hr | 46 | 26.7% | 6.9% |
| $15 to $25/hr | 52 | 30.2% | 10.6% |
| $25 to $35/hr | 31 | 18.0% | 11.9% |
| $35 to $50/hr | 21 | 12.2% | 26.0% |
| $50 to $75/hr | 11 | 6.4% | 14.7% |
| $75 to $100/hr | 10 | 5.8% | 15.3% |
| $100 to $150/hr | 1 | 0.6% | 9.4% |
| $150/hr or more | 0 | 0.0% | 5.1% |
Sample. 172 roles in Data Annotation & Labeling open on 31 Oct 2026 that state an hourly rate, against 3,565 across all AI training work.
Each role counts once, at the middle of its advertised range. The bands are those of the pay-transparency report.
Source. AITraining.jobs Research, The Market for Data Annotation & Labeling Work, October 2026 edition.
Figure 6
Applicant demand per open role
Do roles in Data Annotation & Labeling draw more or fewer applicants per opening than the average AI training role?
| Roles | Clicks per role a week | Index |
|---|---|---|
| Data Annotation & Labeling | 12.61 | 3.70x |
| All AI training work | 3.41 | 1.00x |
| Its roles stating an hourly rate | 8.21 | 2.41x |
| Its roles stating no hourly rate | 22.92 | 6.72x |
| Its roles open worldwide | 17.73 | 5.20x |
| Its roles limited by country | 11.46 | 3.36x |
Sample. Apply clicks on a specific role on AITraining.jobs, from 1 Oct 2026 to 31 Oct 2026: 9,513 on roles in Data Annotation & Labeling, against the days those roles were open.
Clicks per role a week = apply clicks / (open role-days / 7). Index 1.00 is the rate of every role on the site.
Data Annotation & Labeling against every kind of work: Rows with fewer than 3.6 open role-days (0.5 role-weeks) are marked as a small sample and not ranked: below that the pooled rate of the kinds of work weighs more than a row's own clicks (the weight fitted on their own clicks).
Its roles by stated pay, against each other: Rows with fewer than 1.9 open role-days (0.3 role-weeks) are marked as a small sample and not ranked: below that the pooled rate of the two sides weighs more than a row's own clicks (the weight fitted on their own clicks). Its roles by reach, against each other: Rows with fewer than 8.2 open role-days (1.2 role-weeks) are marked as a small sample and not ranked: below that the pooled rate of the two sides weighs more than a row's own clicks (the weight fitted on their own clicks). All AI training work is one set, read from its first open role-day.
Apply clicks measure interest among visitors to AITraining.jobs, who see roles open in their country and recent, priced roles first. Clicks are never split by platform.
Source. AITraining.jobs Research, The Market for Data Annotation & Labeling Work, October 2026 edition.
Figure 7
Applicant demand by listing age
Do newer roles in Data Annotation & Labeling draw more applicants than older ones?
| Listing age | Clicks per role a week | Index (this work = 1) |
|---|---|---|
| Listed during the window | 5.42 | 0.43x |
| Listed up to 4 weeks before it | 28.33 | 2.25x |
| Listed 4 to 12 weeks before it | 0.70 | 0.06x |
| Listed more than 12 weeks before it | 17.28 | 1.37x |
| Listing date unknown | 0.49 | 0.04x |
Sample. Apply clicks on roles in Data Annotation & Labeling, from 1 Oct 2026 to 31 Oct 2026, by when each role was listed relative to the window's first day (1 Oct 2026).
Listing date: the date the job board gives for the posting, or else the first day the role appeared in the feed. A role that arrived with a platform's back catalogue and gives no date has none.
The index divides each row's rate by the rate of all roles in this kind of work, so it reads within the kind.
No row with any open time is a small sample: the rates of the listing ages differ so much that each reads on its own from its first open role-day.
Source. AITraining.jobs Research, The Market for Data Annotation & Labeling Work, October 2026 edition.
Figure 8
Who may apply: location rules
Can people apply to roles in Data Annotation & Labeling from anywhere?
| Location rule | Open roles | Share of its open roles | All AI training work |
|---|---|---|---|
| Open worldwide | 44 | 18.5% | 18.5% |
| Worldwide except listed countries | 28 | 11.8% | 18.1% |
| Only listed countries | 165 | 69.3% | 63.0% |
| No rule stated | 1 | 0.4% | 0.4% |
Sample. 238 roles in Data Annotation & Labeling open at the end of 31 Oct 2026, against 4,381 across all AI training work.
The rule is read from each posting's location text, then, where that names no country, from what the posting's own description states, and where both are silent from what the platform states about where it hires.
Source. AITraining.jobs Research, The Market for Data Annotation & Labeling Work, October 2026 edition.
Figure 9
Who may apply: roles open to each country
How many roles in Data Annotation & Labeling can a resident of each country apply to?
| Country | Open roles | Share of its open roles |
|---|---|---|
| Any country (worldwide roles only) | 45 | 18.9% |
| United States | 154 | 64.7% |
| India | 93 | 39.1% |
| United Kingdom | 81 | 34.0% |
| Indonesia | 80 | 33.6% |
| Brazil | 79 | 33.2% |
| Philippines | 79 | 33.2% |
| Bangladesh | 77 | 32.4% |
| Japan | 77 | 32.4% |
| South Korea | 76 | 31.9% |
| Argentina | 75 | 31.5% |
| Chile | 75 | 31.5% |
| Colombia | 75 | 31.5% |
| Germany | 75 | 31.5% |
| Saudi Arabia | 74 | 31.1% |
| Egypt | 73 | 30.7% |
| Nigeria | 73 | 30.7% |
| Ghana | 72 | 30.3% |
| Pakistan | 72 | 30.3% |
| Cambodia | 69 | 29.0% |
| Palestine | 64 | 26.9% |
Sample. 238 roles in Data Annotation & Labeling open at the end of 31 Oct 2026, for residents of a fixed set of 20 countries.
A country's count is the roles open worldwide (including roles that state no rule, as on the job board), plus roles whose list names it, plus roles whose exclusion list does not.
The 20 countries are the same in every report of this series: those named most often by the location rules of open AI training roles on 9 Oct 2026, either as the only countries accepted or as excluded.
Median pay is over the roles open to that country that state an hourly rate (at least 3).
Source. AITraining.jobs Research, The Market for Data Annotation & Labeling Work, October 2026 edition.
Figure 10
What the roles are called
What are roles in Data Annotation & Labeling called: annotator, evaluator, expert or trainer?
| Title word | Open roles | Share of its open roles |
|---|---|---|
| Evaluator or reviewer | 68 | 28.6% |
| Annotator or labeler | 63 | 26.5% |
| Specialist | 45 | 18.9% |
| Analyst or researcher | 31 | 13.0% |
| Quality assurance | 30 | 12.6% |
| Voice actor or speaker | 15 | 6.3% |
| Expert or SME | 11 | 4.6% |
| Contributor or participant | 8 | 3.4% |
| Rater | 7 | 2.9% |
| Trainer | 7 | 2.9% |
| Lead or manager | 2 | 0.8% |
| Writer or editor | 2 | 0.8% |
| Engineer or developer | 1 | 0.4% |
| Red teamer or tester | 1 | 0.4% |
Sample. 210 of the 238 roles in Data Annotation & Labeling open on 31 Oct 2026 name one of these words in their title (88.2%); 14 title words are named.
A title can use several of these words ('Expert AI Trainer') and counts for each. The vocabularies are those of the job-titles, languages and expert-fields reports.
Median pay needs at least 3 roles stating an hourly rate.
Source. AITraining.jobs Research, The Market for Data Annotation & Labeling Work, October 2026 edition.
Figure 11
What the descriptions ask for
Do roles in Data Annotation & Labeling ask for degrees, credentials, experience or tests?
| Requirement | Roles | Share of described roles |
|---|---|---|
| Mentions a PhD | 15 | 6.9% |
| Mentions a PhD or master's | 21 | 9.7% |
| Mentions any degree | 57 | 26.3% |
| Mentions a professional credential | 45 | 20.7% |
| States years of experience | 36 | 16.6% |
| Asks for 5 years or more | 4 | 1.8% |
| States weekly hours | 90 | 41.5% |
| Mentions an assessment or test | 30 | 13.8% |
| Mentions an AI-led or video interview | 1 | 0.5% |
| Mentions a background check | 0 | 0.0% |
Sample. 217 roles in Data Annotation & Labeling open on 31 Oct 2026 whose job board publishes a full description (AfterQuery, Appen, Braintrust, Claru, Cohere, DATAmundi, Handshake AI, Innodata, Invisible, Lifted (Upwork), Mercor, micro1, OneForma, OpenTrain AI, Outlier (Scale AI), Perle Labs, Prolific, RemoExperts, Remotasks, Rise Data Labs, RWS TrainAI Community, Sama, Shaip (Collaborate by Shaip), SuperAnnotate (SME), TELUS Digital AI, Terac, TransPerfect DataForce, Turing, Vetto, Volga Partners, Weekday and Welo Data), 91.2% of its open roles; 4,000 described roles across all AI training work.
A mention can be a requirement or a preference ('a PhD is a plus'): the figure counts both. The patterns are those of the requirements report.
Only some platforms publish full descriptions, so this figure describes their roles, not every platform's.
A kind of work's figure is shown when its described roles outweigh the average of the kinds (5.8 described roles: the weight of every kind's shares around the shares of all described roles, fitted on their own counts).
Source. AITraining.jobs Research, The Market for Data Annotation & Labeling Work, October 2026 edition.
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Method and definitions
The public job boards of the AI training platforms this site tracks, read every hour. Apply clicks are made on AITraining.jobs; full descriptions come from the platforms whose boards publish them. Every figure is computed by one database query over the window shown, the same query for the live report and for every edition. Each figure states its sample beneath it.
- Kind of work
- Each role is classified from its title and description into one of the twelve kinds of AI training work this site tracks; this report counts the roles classified as Data Annotation & Labeling.
- Fixed panel
- The platforms already tracked when the weekly series opens. The index follows their open roles, so a platform added later (such as OpenTrain AI and Welo Data in September 2026) never reads as growth.
- Index
- The panel's average open roles in a week, divided by the same in the base week, times 100; shown beside the same index for all AI training work on the same platforms.
- Open role
- A role listed by a given day and still in its platform's feed that day.
- New listing
- A role that first appeared during the window on a platform already tracked before that week. A platform's first week in this dataset is its back catalogue and is not counted as new. When this site changes how it reads a platform's board (a cap lifted, a page kind or department read too, a relevance rule changed), the roles that came into view or left it from that change to the end of its week are this site's reading, not the platform's hiring: they are not new listings or removals, and changes in open roles are measured like for like across it. Each platform's report says what changed.
- Removed listing
- A role that left its platform's feed during the window.
- Days listed
- From a removed role's listing date to the last day it was seen in its feed. A median needs at least 3 removed roles.
- HHI
- Herfindahl-Hirschman Index: the sum of every platform's squared percentage share of open roles, 0 to 10,000. Under 1,500 unconcentrated, 1,500 to 2,500 moderately, above 2,500 highly concentrated.
- Advertised pay
- The hourly figure a posting states (the middle of a stated range), counted once per distinct rate as the job board counts it. The median and typical pay are the board's: typical pay runs from the 25th percentile of what roles pay (the middle of each advertised range) to the 90th-percentile advertised ceiling, stated from 3 distinct rates.
- Clicks per open role a week
- Apply clicks on AITraining.jobs on a specific role, divided by the days the roles were open, times 7.
- Demand index
- Clicks per open role a week divided by the same rate across every role on the site. Above 1, the roles draw more applicants than the average role.
- Listing age
- When a role was listed relative to the window's first day: during the window, up to 4 weeks before it, 4 to 12 weeks before or longer. The listing date is the job board's posting date, or else the first day the role appeared in the feed.
- Location rule
- Read from each posting's location text and, where that names no country, from what the posting's own description states: open worldwide, worldwide except listed countries, only listed countries, or no rule stated.
- Open to a country
- A role is open to residents of a country if it is open worldwide, its list names the country, or its exclusion list does not. The 20 countries compared are the same in every report of the series.
- Window
- Live: the last 28 complete days, in UTC, and the last twelve complete ISO weeks (from the week of 3 Aug 2026 at the earliest) for the weekly series. Edition: one calendar month, in UTC, and its weeks.
What this data cannot tell you
- Platforms that recruit without a public job board are not counted. Several large ones invite workers to projects directly.
- A listing is not a hire. Some platforms keep evergreen roles open for months, and some post one listing per language or country.
- Apply clicks measure interest among the people who use AITraining.jobs, and what is shown first gets clicked more. Clicks are never published by platform.
- Full descriptions are published by a few platforms only, so the requirements figure describes their roles and appears only when this kind's described roles read on their own against the other kinds' (the weight of every kind's shares around the shares of all described roles, fitted on their own counts).
- A kind of work with few open roles gives figures that move with a handful of postings: rows on too little data are marked as a small sample.
How the job feeds are read and roles are classified: site methodology. How fresh, complete and consistent the data is, checked every day: data quality and coverage.
Editions
The live report covers the last 28 complete days and changes every day. Each complete month is also published as an edition, frozen two days after the month ends, so a figure you cite from an edition never moves.
- Live dataLast 28 complete days, recomputed daily
- October 2026 edition (this page)Freezes on first reading
- September 2026 editionFrozen 10 Oct 2026
- August 2026 editionFrozen 10 Oct 2026
Cite and reuse
Free to quote, chart and republish under CC BY 4.0 with a link to this page. This edition is frozen, so its figures will read the same later.
Citation
AITraining.jobs (2026). The Market for Data Annotation & Labeling Work, October 2026 edition. https://aitraining.jobs/research/data-annotation-market/2026-10
BibTeX
@misc{aitrainingjobs_data_annotation_market_2026_10,
author = {{AITraining.jobs}},
title = {The Market for Data Annotation & Labeling Work, October 2026 edition},
year = {2026},
howpublished = {\url{https://aitraining.jobs/research/data-annotation-market/2026-10}},
}More research
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