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Research report ยท October 2026 edition

AI Training Market Concentration

On 31 Oct 2026, AI training listings were unconcentrated overall (HHI 522 across 62 platforms); Robotics & Physical-AI Data was the most concentrated kind of work, led by Claru with 40% of its open roles.

Read the month's story: The AI Training Job Market in October 2026

Provisional figures. This month is complete, but late data can still arrive until 3 Nov 2026, when the edition is frozen for good.

Data window
1 Oct 2026 to 31 Oct 2026
31 days, UTC
Computed
1 Nov 2026, 01:11 UTC
Final once frozen
Source
The public job boards of the AI training platforms this site tracks, read every hour.
Method
Version 2. Definitions
CC BY 4.0, how to cite

Every figure on this page as CSV and JSON, sent to your work email.

Key findings

  1. 1

    Across all AI training work, listings are unconcentrated (HHI 522 across 62 platforms); Invisible holds 12.2% of open roles.

    Figure 1
  2. 2

    Robotics & Physical-AI Data is the most concentrated kind of work (HHI 2,628, Claru with 40%); Law, Medicine & Finance the least (HHI 642, across 46 platforms).

    Figure 1
  3. 3

    1 of 11 kinds of work with enough open roles to read on their own are highly concentrated by listings (HHI above 2,500).

    Figure 1
  4. 4

    On the same platforms, concentration rose from 1 Oct 2026 to 31 Oct 2026 (HHI 1,368 to 1,402) and fell in 4 of 9 kinds of work; the largest move was in Agentic Tasks & RL Environments, from 3,592 to 2,287.

    Figure 3
  5. 5

    Alignerr lists the widest range of work: all 12 kinds of work with open roles.

    Figure 4

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 workHHIReadingIts share
All AI training work
522
Unconcentrated12.2%
Robotics & Physical-AI Data
2,628
Highly concentrated40.0%
Research Studies & SurveysSmall sample
1,667
Moderately concentrated27.8%
Red-Teaming & AI Safety
1,598
Moderately concentrated29.6%
Math & STEM
1,426
Unconcentrated30.2%
Writing & Content
1,295
Unconcentrated24.2%
Agentic Tasks & RL Environments
1,270
Unconcentrated22.6%
Multilingual & Localization
1,246
Unconcentrated27.8%
Coding & Software Evaluation
969
Unconcentrated17.2%
Data Annotation & Labeling
930
Unconcentrated20.6%
AI Evaluation & Rating (RLHF)
904
Unconcentrated21.3%
Transcription, Audio & Speech
806
Unconcentrated17.6%
Law, Medicine & Finance
642
Unconcentrated10.9%

Sample. 4,381 roles open at the end of 31 Oct 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.

Rows with fewer than 32.6 open roles are marked as a small sample and not ranked: below that the average of the rows weighs more than a row's own open roles (the weight fitted on the rows' own counts).

Source. AITraining.jobs Research, AI Training Market Concentration, October 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?

Sample. Kinds of work with roles open on 31 Oct 2026 whose top three's share reads on its own.

A kind with fewer than 12.1 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, October 2026 edition.

Figure 3

Is each kind of work consolidating?

Did concentration rise or fall over the window, on the same platforms?

Kind of workHHI on 1 Oct 2026HHI on 31 Oct 2026Change
All AI training work1,368
1,402
+34
Robotics & Physical-AI Data4,053
4,504
+451
Math & STEM3,254
3,725
+471
Multilingual & Localization2,413
3,089
+676
Research Studies & SurveysSmall sample4,671
2,781
-1,890
Red-Teaming & AI SafetySmall sample6,576
2,778
-3,798
Coding & Software Evaluation2,235
2,511
+276
Data Annotation & Labeling2,546
2,373
-173
Agentic Tasks & RL Environments3,592
2,287
-1,305
Writing & ContentSmall sample2,758
2,143
-615
AI Evaluation & Rating (RLHF)3,099
1,910
-1,189
Law, Medicine & Finance1,758
1,809
+51
Transcription, Audio & Speech1,394
1,227
-167

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: Rows with fewer than 8.6 open roles are marked as a small sample and not ranked: below that the average of the rows weighs more than a row's own open roles (the weight fitted on the rows' own counts).

At the end: Rows with fewer than 15.4 open roles are marked as a small sample and not ranked: below that the average of the rows weighs more than a row's own open roles (the weight fitted on the rows' own counts).

Source. AITraining.jobs Research, AI Training Market Concentration, October 2026 edition.

Figure 4

Specialists and generalists

Which platforms spread across many kinds of work, and which specialise?

PlatformKinds of work listedShare in its main kind
Alignerr
12
31.0%
micro1
12
55.6%
Mercor
11
57.8%
TELUS Digital AI
11
22.4%
AfterQuery
10
53.0%
Handshake AI
10
78.3%
Turing
10
31.3%
Weekday
10
66.7%
Invisible
9
45.8%
OpenTrain AI
9
22.5%
SuperAnnotate (SME)
9
41.4%
Claru
8
66.7%
Lifted (Upwork)
8
55.6%
Terac
8
62.2%
TransPerfect DataForce
8
43.2%
Braintrust
7
49.4%
Innodata
7
48.4%
Rise Data Labs
7
31.5%
Welo Data
7
46.7%
DataAnnotation
6
52.7%
OneForma
6
35.3%
Prolific
6
46.8%
RemoExperts
6
56.3%
Scale AI Human Frontier Collective
6
50.0%
Vetto
6
65.0%
Anyone AI
5
44.4%
Appen
5
66.7%
Perle Labs
5
94.0%
RWS TrainAI Community
5
37.8%
CohereSmall sample
4
25.0%
Pasiflora AI
4
42.9%
Sovrano AI
4
80.6%
Surge AI
4
76.9%
Volga Partners
4
71.2%
xAI (SpaceXAI)
4
70.6%
iMerit
3
77.8%
Mindrift
3
41.1%
Mistral AISmall sample
3
33.3%
Outlier (Scale AI)
3
95.7%
RemotasksSmall sample
3
33.3%
SamaSmall sample
3
33.3%
Aligned Labs
2
86.7%
DATAmundi
2
62.5%
Fleet AISmall sample
2
50.0%
RealTrainAISmall sample
2
75.0%
Shaip (Collaborate by Shaip)
2
88.9%
Sigma AI
2
91.4%
AnthropicSmall sample
1
100.0%
Babel Audio
1
100.0%
Edison ScientificSmall sample
1
100.0%
Elsevier Health
1
100.0%
EvolutionIQSmall sample
1
100.0%
HeadwaySmall sample
1
100.0%
Inworld AISmall sample
1
100.0%
JazzX AISmall sample
1
100.0%
KastleSmall sample
1
100.0%
LimbicSmall sample
1
100.0%
Pila8Small sample
1
100.0%
PointClickCareSmall sample
1
100.0%
Snorkel AI Expert CommunitySmall sample
1
100.0%
TrellisSmall sample
1
100.0%
Vals AISmall sample
1
100.0%

Sample. 4,381 roles open on 31 Oct 2026.

Specialisation uses the same index across a platform's own kinds of work: 10,000 means it lists one kind only.

Rows with fewer than 4.5 open roles are marked as a small sample and not ranked: below that the average of the rows weighs more than a row's own open roles (the weight fitted on the rows' own counts).

Source. AITraining.jobs Research, AI Training Market Concentration, October 2026 edition.

For labs, data vendors and researchers

Buy the data behind this report

The figures above are a summary. Behind them are records we collect ourselves, every day:

  • 11,482 roles tracked, each with its history

    Every role on 62 job boards, read since 13 Jul 2026 (every hour since 18 Oct 2026): its pay and place, and the first and last day it was open.

  • 58,632 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.

  • 39 lab and vendor hiring boards

    The job boards of 25 AI labs and 14 human-data vendors, read every day: who is hiring for human data, and who is hiring to buy it.

What you can buy

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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.

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). AI Training Market Concentration, October 2026 edition. https://aitraining.jobs/research/ai-training-market-concentration/2026-10

BibTeX

@misc{aitrainingjobs_ai_training_market_concentration_2026_10,
  author = {{AITraining.jobs}},
  title = {AI Training Market Concentration, October 2026 edition},
  year = {2026},
  howpublished = {\url{https://aitraining.jobs/research/ai-training-market-concentration/2026-10}},
}
Data: every figure as CSV (one line per value) and JSON, sent to your work email.Pay and open-roles data

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