Key findings
- 1
Across all AI training work, listings are unconcentrated (HHI 0 across 0 platforms).
Figure 1
How concentrated each kind of work is
For which kinds of AI training work does one platform hold most of the openings?
| Kind of work | HHI | Reading | Its share |
|---|---|---|---|
| All AI training work | 0 | Unconcentrated | n/a |
Sample. 0 roles open at the end of 30 Sep 2026 on the job boards this site reads, by the platform that lists them.
HHI: the sum of every platform's squared percentage share of the open roles, 0 (many small platforms) to 10,000 (one platform). Read with the US merger-guideline thresholds: under 1,500 unconcentrated, 1,500 to 2,500 moderately, above 2,500 highly concentrated.
Shares are of listings, not of people hired or money paid: a platform posting one role per country or language weighs more here than its hiring may.
No row with any open roles is a small sample: the rows differ so much that each reads on its own from its first.
Source. AITraining.jobs Research, AI Training Market Concentration, September 2026 edition.
Figure 2
The three largest platforms in each kind of work
Who leads each kind of AI training work, and how far ahead?
No data in this window.
Sample. Kinds of work with roles open on 30 Sep 2026 whose top three's share reads on its own.
A kind with fewer than 1 open roles is left out: below that the average of the kinds weighs more than its own roles (the weight fitted on the kinds' own counts).
Source. AITraining.jobs Research, AI Training Market Concentration, September 2026 edition.
Figure 3
Is each kind of work consolidating?
Did concentration rise or fall over the window, on the same platforms?
| Kind of work | HHI on 1 Sep 2026 | HHI on 30 Sep 2026 | Change |
|---|---|---|---|
| All AI training work | 0 | 0 | 0 |
Sample. Roles open at the start and the end of the window on the platforms tracked throughout.
Platforms first tracked during the window are left out of both ends, so their arrival does not read as a change in competition.
At the start: No row with any open roles is a small sample: the rows differ so much that each reads on its own from its first.
At the end: No row with any open roles is a small sample: the rows differ so much that each reads on its own from its first.
Source. AITraining.jobs Research, AI Training Market Concentration, September 2026 edition.
Figure 4
Specialists and generalists
Which platforms spread across many kinds of work, and which specialise?
No data in this window.
Sample. 0 roles open on 30 Sep 2026.
Specialisation uses the same index across a platform's own kinds of work: 10,000 means it lists one kind only.
No row with any open roles is a small sample: the rows differ so much that each reads on its own from its first.
Source. AITraining.jobs Research, AI Training Market Concentration, September 2026 edition.
For labs, data vendors and researchers
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The figures above are a summary. Behind them are records we collect ourselves, every day:
0 roles tracked, each with its history
Every role on 0 job boards, read since n/a (every hour since 18 Oct 2026): its pay and place, and the first and last day it was open.
0 apply clicks in 28 days
Which roles people actually apply to, by field, pay and kind of work. It happens on this site, so nobody else can count it.
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Method and definitions
The public job boards of the AI training platforms this site tracks, read every hour. 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.
- HHI
- Herfindahl-Hirschman Index: the sum of every platform's squared percentage share of open roles, from near 0 (many small platforms) to 10,000 (one platform). Read with the US merger-guideline thresholds: under 1,500 unconcentrated, 1,500 to 2,500 moderately concentrated, above 2,500 highly concentrated.
- Share
- A platform's open roles in a kind of work over all open roles in it, on the last day of the window.
- Like for like
- The change figure counts only platforms already tracked when the window opens, so a platform's arrival in this dataset is not read as a change in competition.
- Open role
- A role listed by a given day and still in its platform's feed that day.
- 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, from AI evaluation and coding to multilingual and audio work. Every kind links to its own page.
- Coverage
- The platforms whose public job boards AITraining.jobs reads in full every hour. Each figure states how many were read.
- Window
- Live: the last 28 complete days, in UTC. Edition: one calendar month, in UTC.
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.
- Shares are of public listings, not of workers hired, hours worked or revenue; a platform posting one role per language or country weighs more here than its hiring may.
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 editionFreezes on first reading
- September 2026 edition (this page)Frozen 11 Nov 2026
- August 2026 editionFreezes on first reading
Cite and reuse
Free to quote, chart and republish under CC BY 4.0 (creativecommons.org/licenses/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). AI Training Market Concentration, September 2026 edition. https://cyberjobs.cc/research/ai-training-market-concentration/2026-09
BibTeX
@misc{aitrainingjobs_ai_training_market_concentration_2026_09,
author = {{AITraining.jobs}},
title = {AI Training Market Concentration, September 2026 edition},
year = {2026},
howpublished = {\url{https://cyberjobs.cc/research/ai-training-market-concentration/2026-09}},
}More research
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