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Research report ยท September 2026 edition

The Expert Scarcity Index for AI Training

On 30 Sep 2026, Engineering (non-software) was the hardest expert field to recruit for AI training work (scarcity index 1.88x, 1.00 = the market) and Law, Medicine & Finance the hardest kind of work (1.44x); 4 groups were scarcer than the market on all three measures: applicants per opening, time to close and pay.

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

Data window
1 Sep 2026 to 30 Sep 2026
30 days, UTC
Frozen
11 Oct 2026, 08:09 UTC
These figures will not change
Source
The public job boards of the AI training platforms this site tracks, read every day, and the apply clicks people make on AITraining.jobs. Fields and languages are read from role titles.
Method
Version 1. 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

    Engineering (non-software) is the hardest expert field to staff, with a scarcity index of 1.88x (1.00 is the market): its roles draw 0.24x the market's apply clicks per open role, its listings came down 18% less often than other roles of the same age on the same platforms, and it advertises $75/hr, 30% above the market median of $58/hr.

    Figure 1
  2. 2

    No language with enough data is harder to staff than the average role; Spanish comes closest, with a scarcity index of 0.89x: its roles draw 0.88x the market's apply clicks per open role, its listings came down 7% less often than other roles of the same age on the same platforms, and it advertises $34/hr, 41% below the market median of $58/hr.

    Figure 2
  3. 3

    Law, Medicine & Finance is the hardest kind of work to staff, with a scarcity index of 1.44x (1.00 is the market): its roles draw 0.41x the market's apply clicks per open role, its listings came down 9% more often than other roles of the same age on the same platforms, and it advertises $78/hr, 35% above the market median of $58/hr.

    Figure 3
  4. 4

    4 of the 25 groups with enough data are scarcer than the market on all three measures (fewer applicants per opening, slower to close than their platforms' other roles, and paid above the market): Engineering (non-software) (1.88x), Biology & life sciences (1.59x), Physics & astronomy (1.56x) and Math & STEM (1.22x).

    Figure 5
  5. 5

    At the other end, Data Annotation & Labeling (kind of work) is the easiest to staff, with an index of 0.48x: its roles draw 2.53x the market's apply clicks per open role, its listings came down 76% more often than other roles of the same age on the same platforms, and it advertises $28/hr, 51% below the market median of $58/hr.

    Figure 4
  6. 6

    Against their own platforms, roles in Multilingual & Localization stay up longest: 58 came down where 109 would have at their platforms' pace.

    Figure 4
  7. 7

    Law, the best-paid expert field with enough data ($125/hr, 2.17x the market median), draws 0.60x the market's apply clicks per open role, so its scarcity index is 1.51x.

    Figure 1
  8. 8

    25 of the 69 fields, languages and kinds of work listed have enough data on all three measures to be ranked; the rest are shown and marked as small samples.

    Figure 4

Figure 1

Scarcity by expert field

Which professions and disciplines are hardest to recruit for AI training work?

Expert fieldScarcity indexApplicant shortfallSlow closingPay premium
All roles (the market)
1.00x
1.00x1.00x1.00x
Engineering (non-software)
1.88x
4.19x1.21x1.30x
Biology & life sciences
1.59x
3.42x1.04x1.13x
Physics & astronomy
1.56x
2.29x1.01x1.65x
Law
1.51x
1.67x0.95x2.17x
Medicine & nursing
1.28x
1.87x0.95x1.20x
Business, sales & consulting
1.21x
1.76x0.77x1.30x
Voice acting, music & sound
1.09x
2.60x0.80x0.62x
Finance, accounting & economics
1.06x
0.88x0.97x1.37x
Design & visual arts
1.00x
1.15x0.90x0.96x
Mathematics & statistics
0.99x
0.92x0.94x1.13x
Software & computer science
0.98x
0.75x1.12x1.13x
Writing, editing & journalism
0.67x
0.45x0.86x0.78x
Psychology & mental healthSmall sample
1.43x
1.12x1.00x2.61x
Humanities & social sciencesSmall sample
1.05x
1.56x0.71x1.04x
ChemistrySmall sample
1.01x
0.68x1.34x1.13x
Education & teachingSmall sample
0.76x
0.45x0.92x1.07x
Trust, safety & child protectionSmall sample
n/a
4.40x5.00xn/a

Sample. 17 expert fields named in the titles of roles open at the end of 30 Sep 2026; apply clicks from 1 Sep 2026 to 30 Sep 2026; listing lifetimes of the 2,008 roles listed from 3 Aug 2026 to 30 Sep 2026.

Scarcity index: the geometric mean of the three ratios beside it, each held between 0.20 and 5.00 so one extreme reading cannot decide it alone. 1.00 is the average role; above 1, harder to staff.

Applicant shortfall: the apply clicks the group's roles would have drawn at the market's rate per open role, over the clicks they drew from 1 Sep 2026 to 30 Sep 2026 (one over the demand index). Above 1, fewer applicants per opening than the market.

Slow closing: the removals expected if each of the group's roles listed from 3 Aug 2026 to 30 Sep 2026 had come down at its own platform's pace for a role of the same age (its Kaplan-Meier hazard), over the removals seen by the end of 30 Sep 2026. Above 1, its roles stay up longer than other roles on the same platforms. It is read against the same platforms because how long a listing stays up depends first on how its platform posts.

Pay premium: the median advertised hourly rate of the group's roles open at the end of 30 Sep 2026 over the median of every open role stating one ($58/hr).

A row is ranked only when its roles would have drawn at least 30 clicks at the market's rate, at least 10 removals were expected, at least 8 of its open roles state an hourly rate and at least 10 are open; otherwise it is marked as a small sample. A ratio capped at 5.00 means no click, or no removal, was recorded.

A role counts for an expert field when its title names it (whole words, the vocabulary of the expert fields report), and counts for each one it names. Titles that name none are not counted.

Source. AITraining.jobs Research, The Expert Scarcity Index for AI Training, September 2026 edition.

Figure 2

Scarcity by language

Which languages are hardest to recruit for AI training work?

LanguageScarcity indexApplicant shortfallSlow closingPay premium
All roles (the market)
1.00x
1.00x1.00x1.00x
Spanish
0.89x
1.13x1.08x0.59x
Arabic
0.81x
1.13x0.73x0.63x
English
0.68x
0.52x1.15x0.52x
MarathiSmall sample
2.67x
3.37x5.00x1.13x
SwedishSmall sample
1.68x
5.00x1.43x0.67x
Filipino (Tagalog)Small sample
1.67x
1.47x5.00x0.63x
MalaySmall sample
1.50x
0.97x5.00x0.70x
GujaratiSmall sample
1.49x
1.28x5.00x0.52x
PunjabiSmall sample
1.44x
1.53x5.00x0.39x
CroatianSmall sample
1.38x
4.80x1.09x0.50x
LithuanianSmall sample
1.36x
5.00x0.45x1.13x
DutchSmall sample
1.29x
3.48x0.98x0.63x
KoreanSmall sample
1.25x
3.49x1.05x0.54x
TeluguSmall sample
1.25x
1.66x3.68x0.32x
DanishSmall sample
1.20x
3.42x0.90x0.57x
FinnishSmall sample
1.19x
2.63x1.05x0.61x
FrenchSmall sample
1.16x
2.94x0.88x0.61x
NorwegianSmall sample
1.11x
1.15x1.42x0.83x
TurkishSmall sample
1.10x
4.15x0.58x0.56x
JapaneseSmall sample
1.07x
1.66x1.19x0.63x
GermanSmall sample
1.07x
1.47x1.32x0.63x
IndonesianSmall sample
1.06x
1.55x0.71x1.09x
TamilSmall sample
1.00x
0.85x3.46x0.34x
CzechSmall sample
0.89x
2.16x0.63x0.52x
ItalianSmall sample
0.87x
1.74x0.78x0.49x
ThaiSmall sample
0.87x
1.17x1.09x0.52x
VietnameseSmall sample
0.85x
1.39x0.84x0.52x
BengaliSmall sample
0.83x
1.07x1.61x0.33x
RussianSmall sample
0.81x
0.77x0.90x0.78x
HebrewSmall sample
0.81x
0.45x1.43x0.83x
PortugueseSmall sample
0.79x
0.84x1.11x0.52x
HindiSmall sample
0.75x
0.72x1.01x0.58x
PolishSmall sample
0.69x
0.76x0.62x0.70x
Chinese (Mandarin)Small sample
0.60x
0.47x1.04x0.45x
UkrainianSmall sample
n/a
2.61x0.80xn/a
KannadaSmall sample
n/a
5.00x1.80xn/a
RomanianSmall sample
n/a
5.00x5.00xn/a
BulgarianSmall sample
n/a
5.00x5.00xn/a
HungarianSmall sample
n/a
5.00x1.01xn/a
MalayalamSmall sample
n/a
5.00x2.37xn/a

Sample. 40 languages named in the titles of roles open at the end of 30 Sep 2026 (the 40 with the most open roles); apply clicks from 1 Sep 2026 to 30 Sep 2026; listing lifetimes of the 2,008 roles listed from 3 Aug 2026 to 30 Sep 2026.

Scarcity index: the geometric mean of the three ratios beside it, each held between 0.20 and 5.00 so one extreme reading cannot decide it alone. 1.00 is the average role; above 1, harder to staff.

Applicant shortfall: the apply clicks the group's roles would have drawn at the market's rate per open role, over the clicks they drew from 1 Sep 2026 to 30 Sep 2026 (one over the demand index). Above 1, fewer applicants per opening than the market.

Slow closing: the removals expected if each of the group's roles listed from 3 Aug 2026 to 30 Sep 2026 had come down at its own platform's pace for a role of the same age (its Kaplan-Meier hazard), over the removals seen by the end of 30 Sep 2026. Above 1, its roles stay up longer than other roles on the same platforms. It is read against the same platforms because how long a listing stays up depends first on how its platform posts.

Pay premium: the median advertised hourly rate of the group's roles open at the end of 30 Sep 2026 over the median of every open role stating one ($58/hr).

A row is ranked only when its roles would have drawn at least 30 clicks at the market's rate, at least 10 removals were expected, at least 8 of its open roles state an hourly rate and at least 10 are open; otherwise it is marked as a small sample. A ratio capped at 5.00 means no click, or no removal, was recorded.

A role counts for a language when its title names it (whole words, the vocabulary of the languages report), and counts for each one it names. Titles that name none are not counted.

Visitors are shown the roles open in their country first, which lowers the clicks on roles limited to a few countries, as many language roles are.

Source. AITraining.jobs Research, The Expert Scarcity Index for AI Training, September 2026 edition.

Figure 3

Scarcity by kind of work

Which kinds of AI training work are hardest to staff?

Kind of workScarcity indexApplicant shortfallSlow closingPay premium
All roles (the market)
1.00x
1.00x1.00x1.00x
Law, Medicine & Finance
1.44x
2.42x0.92x1.35x
Math & STEM
1.22x
1.15x1.41x1.13x
Multilingual & Localization
1.22x
1.51x1.88x0.63x
Coding & Software Evaluation
1.11x
0.97x1.24x1.13x
Red-Teaming & AI Safety
0.97x
1.88x0.72x0.67x
Transcription, Audio & Speech
0.79x
0.77x1.24x0.52x
Writing & Content
0.77x
0.50x0.86x1.04x
AI Evaluation & Rating (RLHF)
0.75x
0.52x0.77x1.04x
Agentic Tasks & RL Environments
0.70x
0.30x1.13x1.04x
Data Annotation & Labeling
0.48x
0.40x0.57x0.49x
Robotics & Physical-AI DataSmall sample
0.55x
0.59x1.09x0.25x
Research Studies & SurveysSmall sample
n/a
0.50x0.91xn/a

Sample. 12 kinds of work with roles open at the end of 30 Sep 2026; apply clicks from 1 Sep 2026 to 30 Sep 2026; listing lifetimes of the 2,008 roles listed from 3 Aug 2026 to 30 Sep 2026.

Scarcity index: the geometric mean of the three ratios beside it, each held between 0.20 and 5.00 so one extreme reading cannot decide it alone. 1.00 is the average role; above 1, harder to staff.

Applicant shortfall: the apply clicks the group's roles would have drawn at the market's rate per open role, over the clicks they drew from 1 Sep 2026 to 30 Sep 2026 (one over the demand index). Above 1, fewer applicants per opening than the market.

Slow closing: the removals expected if each of the group's roles listed from 3 Aug 2026 to 30 Sep 2026 had come down at its own platform's pace for a role of the same age (its Kaplan-Meier hazard), over the removals seen by the end of 30 Sep 2026. Above 1, its roles stay up longer than other roles on the same platforms. It is read against the same platforms because how long a listing stays up depends first on how its platform posts.

Pay premium: the median advertised hourly rate of the group's roles open at the end of 30 Sep 2026 over the median of every open role stating one ($58/hr).

A row is ranked only when its roles would have drawn at least 30 clicks at the market's rate, at least 10 removals were expected, at least 8 of its open roles state an hourly rate and at least 10 are open; otherwise it is marked as a small sample. A ratio capped at 5.00 means no click, or no removal, was recorded.

Every role is classified into one kind of work.

Source. AITraining.jobs Research, The Expert Scarcity Index for AI Training, September 2026 edition.

Figure 4

What each scarcity index is made of

What applicant interest, listing lifetime and pay lie behind each group's scarcity index?

GroupOpen on 30 Sep 2026Clicks per open role a weekMedian advertised payMedian days listedScarcity index
All roles2,7260.21$5828.71.00x
Law, Medicine & Finance6280.09$7831.01.44x
Math & STEM2190.18$6540.51.22x
Multilingual & Localization7600.14$37n/a1.22x
Coding & Software Evaluation2510.22$6528.31.11x
Red-Teaming & AI Safety380.11$3917.20.97x
Transcription, Audio & Speech3420.27$30n/a0.79x
Writing & Content410.42$6019.00.77x
AI Evaluation & Rating (RLHF)2240.40$6021.40.75x
Agentic Tasks & RL Environments540.71$608.30.70x
Data Annotation & Labeling1150.53$2812.00.48x
Robotics & Physical-AI DataSmall sample380.36$15n/a0.55x
Research Studies & SurveysSmall sample160.42n/a9.8n/a
Engineering (non-software)900.05$7538.71.88x
Biology & life sciences320.06$6525.31.59x
Physics & astronomy440.09$9532.81.56x
Law960.13$12533.41.51x
Medicine & nursing1050.11$6935.01.28x
Business, sales & consulting840.12$7525.51.21x
Voice acting, music & sound740.08$3620.51.09x
Finance, accounting & economics1330.24$7927.21.06x
Design & visual arts830.18$5518.71.00x
Mathematics & statistics460.23$6530.90.99x
Software & computer science2080.28$6513.80.98x
Writing, editing & journalism940.47$4523.70.67x
Psychology & mental healthSmall sample510.19$150n/a1.43x
Humanities & social sciencesSmall sample380.14$6031.01.05x
ChemistrySmall sample200.31$65n/a1.01x
Education & teachingSmall sample190.47$61n/a0.76x
Trust, safety & child protectionSmall sample160.05n/an/an/a
Spanish870.19$34n/a0.89x
Arabic520.19$3721.00.81x
English1530.41$30n/a0.68x
MarathiSmall sample190.06$65n/a2.67x
SwedishSmall sample190.01$38n/a1.68x
Filipino (Tagalog)Small sample140.14$37n/a1.67x
MalaySmall sample140.22$40n/a1.50x
GujaratiSmall sample160.17$30n/a1.49x
PunjabiSmall sample150.14$23n/a1.44x
CroatianSmall sample110.04$29n/a1.38x
LithuanianSmall sample130.03$65n/a1.36x
DutchSmall sample340.06$3725.51.29x
KoreanSmall sample480.06$3126.51.25x
TeluguSmall sample190.13$18n/a1.25x
DanishSmall sample160.06$33n/a1.20x
FinnishSmall sample150.08$35n/a1.19x
FrenchSmall sample760.07$3528.41.16x
NorwegianSmall sample140.18$48n/a1.11x
TurkishSmall sample160.05$32n/a1.10x
JapaneseSmall sample490.13$3625.51.07x
GermanSmall sample540.14$3624.91.07x
IndonesianSmall sample250.14$63n/a1.06x
TamilSmall sample160.25$20n/a1.00x
CzechSmall sample120.10$30n/a0.89x
ItalianSmall sample390.12$2821.30.87x
ThaiSmall sample180.18$30n/a0.87x
VietnameseSmall sample230.15$30n/a0.85x
BengaliSmall sample180.20$19n/a0.83x
RussianSmall sample210.27$45n/a0.81x
HebrewSmall sample150.47$48n/a0.81x
PortugueseSmall sample510.25$30n/a0.79x
HindiSmall sample320.29$33n/a0.75x
PolishSmall sample160.28$40n/a0.69x
Chinese (Mandarin)Small sample580.45$2626.80.60x
UkrainianSmall sample110.08n/an/an/a
KannadaSmall sample100.00n/an/an/a
RomanianSmall sample100.03n/an/an/a
BulgarianSmall sample90.03n/an/an/a
HungarianSmall sample90.02n/an/an/a
MalayalamSmall sample90.00n/an/an/a

Sample. Every group in the three scarcity tables. Open roles and pay at the end of 30 Sep 2026; new listings and apply clicks from 1 Sep 2026 to 30 Sep 2026; lifetimes and removals over the 2,008 roles listed from 3 Aug 2026 to 30 Sep 2026, back catalogues left out.

Clicks per open role a week: apply clicks on AITraining.jobs over the days the group's roles were open, times 7. Demand index: that rate over the market's (0.21).

Median days listed: the Kaplan-Meier median from the listing date to the last sighting, as in the listing-lifetime report (n/a when more than half of the group's roles are still listed at the oldest age it can be read at, or fewer than 10 were listed that long ago). It mixes how each platform posts with how fast roles fill, so the index uses the removals against the same platforms' pace instead.

Removed: roles of the cohort that came down. Expected: the removals the same roles would have had at their platforms' hazard for each age; over all roles the two are equal.

Median advertised pay: the hourly figure postings state (the middle of a stated range), shown with at least 8 roles stating one.

Source. AITraining.jobs Research, The Expert Scarcity Index for AI Training, September 2026 edition.

Figure 5

Hardest to staff: scarcer than the market on every measure

Which expertise is short of applicants, slow to close and paid above the market, all at once?

GroupScarcity indexApplicant shortfallSlow closingPay premium
Engineering (non-software)
1.88x
4.19x1.21x1.30x
Biology & life sciences
1.59x
3.42x1.04x1.13x
Physics & astronomy
1.56x
2.29x1.01x1.65x
Math & STEM
1.22x
1.15x1.41x1.13x

Sample. 4 of the 25 fields, languages and kinds of work with enough data on every measure, at the end of 30 Sep 2026.

Listed when all three ratios are above 1.00: fewer applicants per opening than the market, roles staying up longer than other roles on the same platforms, and a median advertised rate above the market's.

A role can count for a field, a language and a kind of work at once, so one set of roles can appear on several rows.

Source. AITraining.jobs Research, The Expert Scarcity Index for AI Training, September 2026 edition.

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Method and definitions

The public job boards of the AI training platforms this site tracks, read every day, and the apply clicks people make on AITraining.jobs. Fields and languages are read from role titles. 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.

Scarcity index
The geometric mean of the applicant shortfall, the slow-closing ratio and the pay premium, each held between 0.2 and 5 so one extreme reading cannot decide it alone. 1.00 is the average AI training role; above 1, the group is harder to staff.
Applicant shortfall
The apply clicks a group's roles would have drawn at the market's rate per open role, divided by the clicks they drew in the window: one over the demand index. Above 1, fewer applicants per opening than the market.
Slow closing
For every role listed in the last 26 weeks (from 3 Aug 2026 at the earliest; back catalogues left out), the chance it comes down at each age is read from its own platform's Kaplan-Meier curve; summed over the group's roles, that gives the removals expected at its platforms' pace. Slow closing is expected removals over removals seen. Above 1, the group's roles stay listed longer than other roles of the same age on the same platforms.
Pay premium
The median advertised hourly rate of the group's open roles over the median of every open role stating one. Needs at least 8 roles stating a rate.
Median days listed
The Kaplan-Meier median from the listing date to the last sighting, as in the listing-lifetime report. Published beside the index; not part of it, because it depends first on how each platform posts.
Ranked
A group is ranked when its roles would have drawn at least 30 clicks at the market's rate, at least 10 removals were expected, at least 8 of its open roles state an hourly rate and at least 10 are open. Other groups are shown and marked as small samples.
Expert field and language
Named in a role's title, matched as whole words with the vocabularies of the expert fields and languages reports. A role naming two counts for both.
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. Every kind links to its own page.
Window
Live: the last 28 complete days, in UTC, with listing lifetimes over every role listed in the 26 weeks to the same end (from 3 Aug 2026 at the earliest). Edition: one calendar month, with lifetimes over every role listed in the 26 weeks to its end, followed to its end.

What this data cannot tell you

  • Applicant interest is measured among the people who use AITraining.jobs, not across the market, and what is shown first gets clicked more: each visitor sees the roles open in their country first, which lowers the clicks on roles limited to a few countries, as many language roles are.
  • A listing coming down is not a hire: a role can close because it filled, because the project ended or because the platform re-posts it. Reading it against the same platforms removes each platform's posting habits, not the reasons a particular role closed.
  • Pay is what postings advertise, not what workers earn, and part of a gap between groups is where they hire: many platforms set lower rates in lower-cost countries.
  • Generic titles hide the field or language of many roles, so a group's counts are a floor; a role can count for a field, a language and a kind of work at once.
  • Platforms that recruit without a public job board are not counted.

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). The Expert Scarcity Index for AI Training, September 2026 edition. https://www.aitraining.run/research/expert-scarcity-index/2026-09

BibTeX

@misc{aitrainingjobs_expert_scarcity_index_2026_09,
  author = {{AITraining.jobs}},
  title = {The Expert Scarcity Index for AI Training, September 2026 edition},
  year = {2026},
  howpublished = {\url{https://www.aitraining.run/research/expert-scarcity-index/2026-09}},
}
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