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The Expert Scarcity Index for AI Training

On 18 Oct 2026, Chemistry was the hardest expert field to recruit for AI training work (scarcity index 1.80x, 1.00 = the market), German the hardest language (1.72x) and Math & STEM the hardest kind of work (1.16x); 5 groups were scarcer than the market on all three measures: applicants per opening, time to close and pay.

Data window
21 Sep 2026 to 18 Oct 2026
28 days, UTC
Computed
19 Oct 2026, 03:35 UTC
Recomputed every day
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

    Chemistry is the hardest expert field to staff, with a scarcity index of 1.80x (1.00 is the market): its roles draw 0.09x the market's apply clicks per open role, its listings came down 34% less often than other roles of the same age on the same platforms, and it advertises $50/hr, 23% below the market median of $65/hr.

    Figure 1
  2. 2

    German is the hardest language to staff, with a scarcity index of 1.72x (1.00 is the market): its roles draw 0.33x the market's apply clicks per open role, its listings came down 40% less often than other roles of the same age on the same platforms, and it advertises $65/hr, the market median.

    Figure 2
  3. 3

    Math & STEM is the hardest kind of work to staff, with a scarcity index of 1.16x (1.00 is the market): its roles draw 0.58x the market's apply clicks per open role, its listings came down 11% more often than other roles of the same age on the same platforms, and it advertises $65/hr, the market median.

    Figure 3
  4. 4

    5 of the 48 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): Hebrew (1.70x), Law (1.54x), Engineering (non-software) (1.54x), Arabic (1.27x) and Law, Medicine & Finance (1.16x).

    Figure 5
  5. 5

    At the other end, Data Annotation & Labeling (kind of work) is the easiest to staff, with an index of 0.54x: its roles draw 2.06x the market's apply clicks per open role, its listings came down 41% more often than other roles of the same age on the same platforms, and it advertises $30/hr, 54% below the market median of $65/hr.

    Figure 4
  6. 6

    Against their own platforms, roles in Hebrew stay up longest: 6 came down where 12 would have at their platforms' pace.

    Figure 4
  7. 7

    Law, the best-paid expert field with enough data ($110/hr, 1.69x the market median), draws 0.51x the market's apply clicks per open role, so its scarcity index is 1.54x.

    Figure 1
  8. 8

    48 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
Chemistry
1.80x
5.00x1.50x0.77x
Physics & astronomy
1.79x
4.49x1.32x0.97x
Law
1.54x
1.96x1.11x1.69x
Engineering (non-software)
1.54x
2.81x1.25x1.04x
Mathematics & statistics
1.29x
2.09x1.03x1.00x
Voice acting, music & sound
1.21x
1.61x0.96x1.15x
Biology & life sciences
1.18x
2.07x0.79x1.00x
Finance, accounting & economics
1.12x
1.24x0.92x1.23x
Psychology & mental health
1.09x
1.12x0.74x1.54x
Medicine & nursing
1.07x
1.09x0.97x1.15x
Design & visual arts
1.01x
1.22x0.78x1.08x
Humanities & social sciences
1.00x
1.38x0.72x1.00x
Software & computer science
0.94x
0.75x1.10x1.00x
Business, sales & consulting
0.74x
0.43x0.81x1.15x
Writing, editing & journalism
0.69x
0.47x0.98x0.73x
Education & teaching
0.66x
0.54x0.65x0.83x
Trust, safety & child protectionSmall sample
n/a
2.02x5.00xn/a

Sample. 17 expert fields named in the titles of roles open at the end of 18 Oct 2026; apply clicks from 21 Sep 2026 to 18 Oct 2026; listing lifetimes of the 3,610 roles listed from 3 Aug 2026 to 18 Oct 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 21 Sep 2026 to 18 Oct 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 18 Oct 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 18 Oct 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 18 Oct 2026 over the median of every open role stating one ($65/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, live data.

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
German
1.72x
3.07x1.66x1.00x
Hebrew
1.70x
1.65x1.94x1.54x
Dutch
1.69x
3.08x1.76x0.88x
Polish
1.64x
3.43x0.84x1.54x
Arabic
1.27x
1.33x1.01x1.54x
Italian
1.26x
2.29x1.27x0.69x
Thai
1.20x
3.26x1.43x0.37x
Swedish
1.13x
3.18x0.45x1.00x
Korean
1.06x
2.30x0.84x0.62x
Portuguese
1.06x
1.01x1.17x1.00x
French
0.93x
1.72x0.61x0.77x
Japanese
0.90x
1.08x1.01x0.67x
Spanish
0.88x
1.00x1.11x0.62x
Russian
0.82x
1.15x1.05x0.46x
Chinese (Mandarin)
0.77x
0.98x0.99x0.46x
Turkish
0.72x
0.79x1.01x0.46x
Vietnamese
0.71x
0.75x1.12x0.42x
Bengali
0.71x
0.81x1.32x0.33x
English
0.70x
0.64x1.17x0.46x
Hindi
0.60x
0.53x0.91x0.46x
FinnishSmall sample
2.13x
5.00x1.63x1.19x
DanishSmall sample
1.78x
5.00x0.91x1.23x
CantoneseSmall sample
1.69x
3.92x2.30x0.54x
NorwegianSmall sample
1.61x
4.15x1.39x0.73x
HungarianSmall sample
1.45x
5.00x1.22x0.50x
PunjabiSmall sample
1.33x
2.20x2.89x0.37x
CroatianSmall sample
1.30x
4.39x1.19x0.42x
CatalanSmall sample
1.25x
5.00x0.99x0.39x
CzechSmall sample
1.14x
3.54x0.91x0.46x
GreekSmall sample
1.12x
5.00x0.60x0.46x
KannadaSmall sample
1.02x
1.02x2.95x0.35x
Filipino (Tagalog)Small sample
0.96x
2.70x0.59x0.56x
TeluguSmall sample
0.87x
0.89x2.26x0.33x
GujaratiSmall sample
0.81x
1.89x0.91x0.31x
TamilSmall sample
0.77x
0.68x1.87x0.37x
MarathiSmall sample
0.72x
0.85x0.97x0.46x
UrduSmall sample
0.72x
0.91x0.88x0.46x
IndonesianSmall sample
0.68x
0.95x0.66x0.51x
MalaySmall sample
n/a
3.66x0.53xn/a
RomanianSmall sample
n/a
4.03x1.09xn/a

Sample. 40 languages named in the titles of roles open at the end of 18 Oct 2026 (the 40 with the most open roles); apply clicks from 21 Sep 2026 to 18 Oct 2026; listing lifetimes of the 3,610 roles listed from 3 Aug 2026 to 18 Oct 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 21 Sep 2026 to 18 Oct 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 18 Oct 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 18 Oct 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 18 Oct 2026 over the median of every open role stating one ($65/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, live data.

Figure 3

Scarcity by kind of work

Which kinds of AI training work are hardest to staff?

Sample. 12 kinds of work with roles open at the end of 18 Oct 2026; apply clicks from 21 Sep 2026 to 18 Oct 2026; listing lifetimes of the 3,610 roles listed from 3 Aug 2026 to 18 Oct 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 21 Sep 2026 to 18 Oct 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 18 Oct 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 18 Oct 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 18 Oct 2026 over the median of every open role stating one ($65/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, live data.

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 18 Oct 2026Clicks per open role a weekMedian advertised payMedian days listedScarcity index
All roles4,3580.48$6518.81.00x
Math & STEM2440.28$6519.41.16x
Law, Medicine & Finance1,4560.40$7520.61.16x
Research Studies & Surveys390.51$10011.81.06x
Multilingual & Localization1,1330.29$4026.81.05x
Coding & Software Evaluation3330.57$6517.00.96x
Red-Teaming & AI Safety560.50$7417.20.94x
Transcription, Audio & Speech5740.53$3029.40.82x
Agentic Tasks & RL Environments680.75$508.30.82x
AI Evaluation & Rating (RLHF)1741.02$5818.00.65x
Writing & Content411.27$5511.80.65x
Robotics & Physical-AI Data680.64$109.30.55x
Data Annotation & Labeling1720.98$3012.00.54x
Chemistry870.04$5032.51.80x
Physics & astronomy820.11$6332.11.79x
Law1180.24$11027.11.54x
Engineering (non-software)1830.17$6818.01.54x
Mathematics & statistics940.23$6520.01.29x
Voice acting, music & sound1330.30$7520.51.21x
Biology & life sciences910.23$6514.01.18x
Finance, accounting & economics2750.38$8019.41.12x
Psychology & mental health280.42$10013.01.09x
Medicine & nursing1990.44$7520.01.07x
Design & visual arts900.39$7014.01.01x
Humanities & social sciences470.35$6526.81.00x
Software & computer science3410.63$6513.70.94x
Business, sales & consulting1451.10$7518.00.74x
Writing, editing & journalism1041.02$4820.00.69x
Education & teaching340.88$5427.00.66x
Trust, safety & child protectionSmall sample160.24n/an/an/a
German1210.16$6524.51.72x
Hebrew370.29$100n/a1.70x
Dutch610.16$5825.51.69x
Polish380.14$100n/a1.64x
Arabic1070.36$10023.51.27x
Italian670.21$4521.31.26x
Thai210.15$2425.51.20x
Swedish370.15$65n/a1.13x
Korean770.21$4012.01.06x
Portuguese810.47$6526.21.06x
French950.28$507.20.93x
Japanese800.44$4420.00.90x
Spanish1260.47$4027.00.88x
Russian290.41$3015.20.82x
Chinese (Mandarin)770.48$3019.90.77x
Turkish190.60$308.00.72x
Vietnamese300.64$28n/a0.71x
Bengali260.59$21n/a0.71x
English1670.75$3048.00.70x
Hindi360.90$3025.50.60x
FinnishSmall sample290.08$78n/a2.13x
DanishSmall sample310.04$80n/a1.78x
CantoneseSmall sample110.12$35n/a1.69x
NorwegianSmall sample180.11$4827.51.61x
HungarianSmall sample130.05$33n/a1.45x
PunjabiSmall sample150.22$24n/a1.33x
CroatianSmall sample110.11$27n/a1.30x
CatalanSmall sample120.05$26n/a1.25x
CzechSmall sample150.13$30n/a1.14x
GreekSmall sample130.06$30n/a1.12x
KannadaSmall sample120.47$23n/a1.02x
Filipino (Tagalog)Small sample140.18$37n/a0.96x
TeluguSmall sample230.54$21n/a0.87x
GujaratiSmall sample140.25$20n/a0.81x
TamilSmall sample200.70$24n/a0.77x
MarathiSmall sample200.56$308.00.72x
UrduSmall sample110.52$30n/a0.72x
IndonesianSmall sample260.50$3313.00.68x
MalaySmall sample110.13n/an/an/a
RomanianSmall sample110.12n/an/an/a

Sample. Every group in the three scarcity tables. Open roles and pay at the end of 18 Oct 2026; new listings and apply clicks from 21 Sep 2026 to 18 Oct 2026; lifetimes and removals over the 3,610 roles listed from 3 Aug 2026 to 18 Oct 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 (0.48).

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, live data.

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
Hebrew
1.70x
1.65x1.94x1.54x
Law
1.54x
1.96x1.11x1.69x
Engineering (non-software)
1.54x
2.81x1.25x1.04x
Arabic
1.27x
1.33x1.01x1.54x
Law, Medicine & Finance
1.16x
1.20x1.12x1.15x

Sample. 5 of the 48 fields, languages and kinds of work with enough data on every measure, at the end of 18 Oct 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, live data.

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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. Live figures change daily: cite a monthly edition for numbers that will read the same later, or keep the access date.

Citation

AITraining.jobs (2026). The Expert Scarcity Index for AI Training (live data, 21 Sep 2026 to 18 Oct 2026). https://www.aitraining.run/research/expert-scarcity-index (accessed 19 Oct 2026)

BibTeX

@misc{aitrainingjobs_expert_scarcity_index_live,
  author = {{AITraining.jobs}},
  title = {The Expert Scarcity Index for AI Training (live data, 21 Sep 2026 to 18 Oct 2026)},
  year = {2026},
  howpublished = {\url{https://www.aitraining.run/research/expert-scarcity-index}},
  note = {Accessed 19 Oct 2026},
}
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