ML/AI Work Research · Demand intelligence
Demand × Supply gap: chased vs overlooked AI roles
Job seekers searching for “prompt engineer” outnumber live postings 438 to 1, while generative ai engineer draws just 3.1 — a 140× less crowded door into the field — the most chased and least crowded corners of the AI job market (ML/AI Work, search demand × live corpus, as of 2026-07-28).
Searches per live postingbar length is log-scaled · label shows the real ratio
red = overheated (seekers ≫ jobs) · green = supply-rich (more postings than searchers — seeker leverage)
Prompt Engineer: 62,690 searches/mo against 143 live postings (438 s/p). At the other end, generative ai engineer shows 3.1 searches per posting — a 140× gap in seeker competition between the two ends of the chart.
Anti-hype: “prompt engineer”, global searches/month
“Prompt engineer” searches peaked in 2023-04 at 168K/month and have fallen 65% since — yet it still tops the gap chart above: interest decays slower than the role's actual market.
Methodology
Demand = average Google searches per month over the last 3 closed months (via DataForSEO), summed across 18 markets. Supply = live postings in the ML/AI Work corpus (active, AI-tier) whose normalized title contains the role phrase on a word boundary. The ratio is a direction-of-imbalance signal, not a vacancy forecast: search interest includes the curious as well as applicants, and title matching undercounts roles advertised under adjacent names. Corpus definitions: methodology.
Cite this
ML/AI Work, "ML/AI Work Demand × Supply gap", dataset v2026.06, n=16, as of 2026-07-28. https://mlai.work/research/demand-supply-gap