Overview

FacultaStudio reads job advertisements and measures what the work actually asks for. Everything on this page counts postings — individual job adverts collected from public job boards, not people, hires or open roles. One advert is one posting, whether nobody applies or a thousand do.

It exists to answer a practical question: if you have an hour, what is it worth learning? The panels below read that off what employers are currently asking for.

Including 455,670 postings from Fortune 500 career sites and 89,801 postings from small-employer job boards and 32,618 postings from US federal jobs, collected since 27 September 2026. Figures on this page are larger than the published ones and are not comparable with them.

Collected 2026-11-08, postings first seen 2023-03-01 to 2026-11-08.

956,671postings (n = 956,671)
232,637AI-related, of n = 956,671
503boards
45,076employers
The four capability quadrants, drawn to sizeTwo overlapping circles, their areas proportional to their counts: engineering depth (54,288 postings) and business depth (153,593). They overlap in 26,280 postings asking for both. 345,650 postings pass neither test. Builder-deep: Computer Science, Computer Engineering. Hybrid: Information Systems. Business-deep: AI in Business, Business Management, Sales, Marketing, Strategic Management, Finance. 31%6,58526%16,0224%39,3814%32,0031%8,9351%11,275Human ResourceManagementGlobal SupplyChainManagementRetail &CustomerServiceHealthcare &ClinicalSkilled Trades& Field ServiceFood Service &Hospitality345,650Business, AI-thin28,008Builder-deepComputer ScienceComputerEngineering26,280HybridInformation Systems127,313Business-deepAI in BusinessBusiness ManagementSalesMarketingStrategyFinance
Builder-deep 28,008
Computer Science, Computer Engineering
Hybrid 26,280
Information Systems
Business-deep 127,313
AI in Business, Business Management, Sales, Marketing, Strategic Management, Finance
The two large circles are the two depth tests a posting can pass; where they cross it passed both, and outside them it passed neither. Their areas are their counts, and the 48% of the engineering circle sitting inside the business circle is why this is a Venn and not four separate things. Each region is labelled with academic programmes, not jobs. Business programmes are placed where most of their postings sit, so the business majors land in business-deep on their own numbers, and Information Systems lands in the overlap because no single region holds most of it: 29% business-deep, 17% hybrid and 21% builder-deep. No business programme lands in builder-deep, so that region names the degrees its jobs — software, machine learning, cloud — draw on. The job families inside the circles are counted in them but not named. The small circles are the fields the four quadrants do not describe. How far a circle reaches in is the share of that field already at that depth, its area is its size, and it is outlined in the colour of whichever circle holds more of it, unless the two are within eight points — those are dashed, because a lead that small is a coin flip. Hybrid counts toward both. The small circles re-cut postings the large ones already count, and a posting that involves two fields is counted in both, so their areas are not meant to add up to anything. Not drawn: Unclassified (1,368). These are job titles the rules could not read, not kinds of work, so drawing them as a category would claim something they are not. Read the provenance before the shapes. Both halves are provisional: the business programmes ride on a classifier awaiting human validation, and the job families outside business are a rule set nobody has yet coded a sample against.
Look inside one programInformation SystemsSalesBusiness ManagementMarketingStrategic ManagementFinanceAccountingHuman Resource ManagementExperience Design and ManagementGlobal Supply Chain ManagementEntrepreneurial Management

Each circle is a program, placed by how many job titles it shares with the others; open one to see its own quadrants, overlaps and skills, or see all programs as a table.

Four quadrants of the same labour market

Bar length is the number of postings in a region. The filled part is the share of that region which is AI-related. Both are the last 90 days, by real posting date.

What the four quadrants are cut on. The capabilities a posting asks for, read from its description. A role naming three or more distinct engineering capabilities has builder depth; three or more business capabilities gives business depth. Both is Hybrid, neither is AI-thin. There are four because two yes-or-no tests cross, which is what makes them quadrants rather than a list. The threshold of three is the one the source analysis used, adopted rather than reinvented so the two stay comparable.

These 527,251 postings are the ones carrying a real posting date from the last 90 days in the United States; the panel above is larger. Geography is a choice here rather than a fixed filter: it was pinned to the United States until 22 September 2026, which set aside about 44% of the scored frame without saying so. The window is deliberate: collection began in September 2026, so anything older is visible only if it stayed open long enough to be caught. Quadrants do not depend on the discipline classifier, so unlike the per-discipline figures they do not wait on human validation.

What each quadrant asks for

Ranked by how far Hybrid AI sits from the other quadrants, not by how often the item appears. The bar is this region; the ticks are the others. An item everybody asks for tells you nothing about where you are.

Domain knowledge

Subject matter the work assumes you already hold. A degree, or a job.

Partly definitional. Quadrants are cut on how many of these terms a posting names, so a quadrant leads on the terms that put it there. The ordering is still informative; the level is not a discovery.

  • Application programming interfaces (APIs)about 43 in 100 postings ask for this
    43%+30.3 points vs the other three
  • Agentic AI and AI agentsabout 26 in 100 postings ask for this
    26%+18.4 points vs the other three
  • Data engineeringabout 15 in 100 postings ask for this
    15%+13.5 points vs the other three
  • Software engineeringabout 24 in 100 postings ask for this
    24%+13.3 points vs the other three
  • Data analysis and analyticsabout 19 in 100 postings ask for this
    19%+13.1 points vs the other three
  • Machine learningabout 20 in 100 postings ask for this
    20%+12.8 points vs the other three
  • Large language models (LLMs)about 19 in 100 postings ask for this
    19%+12.5 points vs the other three
  • Statisticsabout 17 in 100 postings ask for this
    17%+11.1 points vs the other three

Shares are of postings in this region over the last 90 days, by real posting date, in the geography chosen above. These figures were fixed to the United States until 22 September 2026 and could not follow that choice; they can now.