Teamed holds two things side by side that are rarely seen together: what employers write when they hire, and what practitioners write about themselves. Research is where we count both, show the method, and state the limits.
AI appears in nearly half of L&D job postings. Almost none of them ask you to build anything. We read 9,135 job postings and 36,463 candidate documents to find out what employers are actually asking for, how candidates describe the same skills differently, and which of the shortage…
9,135 job postings · 36,463 candidate documents · 2023 Q4 – 2026 Q3
Read the report →Research holds the evidence, the method and the limits. Interpretation is labeled as interpretation, and the longer arguments live on the blog, which links back here. Every figure states the population it was measured against.
Every number is keyword presence in real job postings and real candidate documents. It measures what people wrote — a floor on what the text says, never a measure of what anyone can do.
A document archive is weighted to older material, so an aggregate measures when something was written. We match the years before comparing the two sides, which is where most shortage headlines go wrong.
Products count only on an unambiguous name, and short acronyms match on word boundaries, never as substrings. A tool sitting near the word "AI" is co-occurrence, not demand.