Skip to main content
Datamata Studios

Popular destinations

Skill trends, comparisons, salary context, resume help and long-form guides — jump straight to what brings people back.

FreeCC BY 4.0

AI Requirements Index — Open Dataset

How fast AI skills are becoming a job requirement: the daily share of active tech job listings mentioning AI skills, tracked over time and split by skill tier (generative AI vs classic machine learning), job category and seniority. A listing counts once per tier no matter how many AI skills it lists. Free to download, analyse and republish — just credit the source.

9.7%
Data jobs mentioning AI skills
1,305
Rows in the series
Jul 10, 2026
Last updated

The latest snapshot at a glance

Share of active listings mentioning at least one AI skill on Jul 10, 2026, per category. The generative AI tier covers LLM-era skills like RAG, fine-tuning and LangChain; classic ML covers PyTorch, scikit-learn and friends; any AI is either.

CategoryAny AIGenerative AIClassic MLActive listings
AI / ML45.6%23.3%34.4%2,068
Product12.3%9.3%5.3%1,424
Engineering10.3%6.9%5.3%7,376
Data9.7%2.7%8.3%4,883
DevOps3.7%1.6%2.4%2,585
Security3.2%2.5%1.3%1,278

Are entry-level roles expected to know generative AI?

Generative-AI skill share by seniority for Data roles on the latest snapshot. The full seniority split for every category and tier is in the download.

3.6%
senior
2.4%
mid
0.4%
entry

What's inside

Unlike a latest-snapshot dataset, this one carries the full time series — one row per snapshot date, category, seniority and AI tier — so the trend itself is the data. The CSV is plain tabular data; the JSON wraps the same rows with metadata (version, licence, generation timestamp). Columns:

ColumnTypeDescription
snapshot_datedateUTC date the snapshot was computed (YYYY-MM-DD).
categorystringJob category: data, engineering, product, devops, security or ai.
senioritystringSeniority split: all, entry, mid, senior, lead or unknown.
tierstringAI skill tier: genai (LLM-era skills), ml (classic ML) or any_ai (either).
listings_with_aiintegerActive listings mentioning at least one skill in the tier.
total_listingsintegerAll active listings in the category/seniority group on that date.
pctnumberlistings_with_ai / total_listings × 100, rounded to 0.1.
required_countintegerListings where a tier skill is a hard requirement rather than nice-to-have. Blank for legacy rows.

How often it updates

The pipeline snapshots every active job listing daily, extracts skills from listing text with a curated taxonomy and records the share of listings mentioning at least one skill per AI tier. Shares are listing-level, so a listing naming five AI skills counts once. For the full collection method, sources and known limitations, read the data methodology. To explore AI skill demand interactively, see the live AI skills intelligence page.

Query it with the API

The same series is available as a read-only JSON endpoint with open CORS, so you can fetch it from the browser or a script. Filter by category, tier and seniority.

# The whole series
curl https://www.datamatastudios.com/api/datasets/ai-requirements-index

# Headline: any AI skill in data jobs, over time
curl "https://www.datamatastudios.com/api/datasets/ai-requirements-index?category=data&tier=any_ai&seniority=all"

# CSV instead of JSON
curl "https://www.datamatastudios.com/api/datasets/ai-requirements-index?format=csv"

Responses carry the same columns as the download, plus the licence, attribution and the bulk download URLs. Please keep the attribution link when you republish.

Licence & attribution

The AI Requirements Index is released under the Creative Commons Attribution 4.0 (CC BY 4.0) licence. You can share and adapt it for any purpose, including commercially, as long as you credit Datamata Studios and link back to this page. It is also published on Hugging Face and Kaggle.

Suggested citation

Datamata Studios. "Datamata AI Requirements Index." Jul 10, 2026. https://www.datamatastudios.com/datasets/ai-requirements-index. Licensed under CC BY 4.0.

More open datasets

Building something with this data? We'd love to see it — get in touch.