About the AI Labor Market Index
The AI Labor Market Index is a monthly dashboard of how artificial intelligence is affecting the Norwegian labor market, produced by Øystein Hernæs (Frisch Centre) and Andreas R. Kostøl (BI Norwegian Business School). The index tracks employment, new hires and pay in the Norwegian private sector, grouped by occupations' AI exposure and workers' age — a Norwegian parallel to Stanford Digital Economy Lab (DEL)'s Canaries Dashboard. The dashboard itself is at kiindeksen.no/en.
Key findings
As of April 2026 (July 2026 release); up-to-date figures on the front page.
- No job crisis in Norway: total private-sector employment is growing, and the employment rate is stable.
- The AI Labor Market Index is slightly positive (+0.5): since October 2022 (the month before ChatGPT), total employment in the most AI-exposed occupations has fallen by 0.1%, versus a 0.6% decline in the least exposed occupations.
- But there are important differences across age: among the youngest (21–30) in the most AI-exposed occupations, employment has fallen — both relative to young people in other occupations and relative to older workers in the same occupations. The decline has intensified over the past year.
- Two mechanisms pull in opposite directions: in occupations where AI usage is most augmenting (AI assists the worker), employment has grown clearly more than in other occupations since the launch of ChatGPT, while growth has been clearly weaker where usage is most automating (AI performs the task).
Method
The data source is the A-ordningen (employers' monthly reporting) via microdata.no: the entire population of wage earners in the private sector, monthly from January 2021, in the age groups 21–30, 31–40, 41–50 and 51–60. The reference period for each month is the week containing the 16th.
AI exposure. Each occupation (four-digit STYRK-08) is linked to the exposure measure “beta” from Eloundou et al. (2024, Science) via the occupation classifications ISCO-08 and SOC. The quintiles are equally weighted per occupation, the same construction as in the DEL dashboard. The usage groups are based on the Anthropic Economic Index (Handa et al. 2025) and follow the grouping in Brynjolfsson, Chandar and Chen (2025).
Outcomes. Employment is the number of wage earners in the group. New hires is the number of jobs with a registered start date in the window between the previous and current monthly reference date. Pay is the group's average monthly cash pay, scaled up to full-time equivalent (FTE) using each occupation-age cell's average contracted hours — a part-time position counts as its share of a full-time year, so that pay changes are not conflated with changes in working time; the pay series are nominal.
Smoothing and seasonal adjustment. By default the
figures show seasonally adjusted series smoothed with a 6-month
centered moving average; raw (unadjusted) series — the same method as
DEL — can also be chosen. The seasonal adjustment is an X-11 core in
logarithms with factors estimated on 2021–2024 and then frozen. The
downloadable data files additionally contain population-adjusted
variants of each series (the adjustment column).
Population adjustment (per capita). The population
grows differently across age groups, so headcount series mix
labor-market changes with demographics. The per capita variants
divide the number employed by the resident population in the same
age group
(SSB table 07459, quarterly figures interpolated
to month), so that the index measures jobs per person rather than the
number of jobs. All variants are in the downloadable data files (the
adjustment column).
Differences from the DEL dashboard. DEL uses a balanced panel of ~25,000 U.S. firms with ADP payroll data; we use the entire Norwegian population of private-sector wage earners without sample selection. The age groups are decade groups (theirs are finer). The composition is very different: in the ADP panel 66 percent of employment sits in the two most exposed quintiles, in Norway about 40 percent.
Revisability. The A-ordningen can revise recent months. Each monthly data release is therefore archived as its own vintage and is not changed afterwards.
Citation and contact
Data and figures may be used freely with attribution to the AI Labor Market Index (kiindeksen.no) — see citation information with BibTeX. A research paper with a full methodological description and analysis is in progress: Hernæs, Øystein and Andreas R. Kostøl (2026). “Does AI Widen Employment Gaps? Tracking Early-Career Employment by Occupational Exposure in Norway”. Contact: andreas.r.kostol@bi.no.