Simon Janssen
Simon Janssen· CTO at HappyNurse · FR AI Exposure Map 2026
Elementary

Éboueurs and AI

Low exposureAI score 2/10 · Elementary
2out of 10
JPE Score
Median net salary (DARES)
€22K
net per year, employees only
Forecast 2030
-5% to +5%
Employment 2024
121K
DARES, incl. self-employed
Employment growth 2021-2024 (DARES)
+24%
Forecast trend 2025-2030
stable
Part-time
9%
Female share
6%
Sector
Elementary

Exposure scores

JPE (Practical Exposure)2/10 · Low exposure
Employment growth 2021-2024 (DARES)+24%

AI exposure explained

What does an AI score of 2/10 mean?

Interpretation

Low exposure: AI is unlikely to significantly change this occupation in the near term.

Éboueurs has low AI exposure and grew in recent years. This occupation relies on human-centred demand that AI cannot easily replicate.


Forecast 2030

What changes for Éboueurs?

Expected employment change, 2025 to 2030
-5% to +5%
Midpoint +1% · Stable: invest in AI skills
BaseMétiers 2030 projection, without AI+1%
Base + AIJPE 2/10: 0%+1%
Base + AI + roboticsautomation already part of the Métiers 2030 projection trend, no extra effect+1%
Rows add up: the bottom row is the forecast.

The forecast starts from the national projection per occupational family and adds AI and robotics as separate layers. The band of -5% to +5% matters more than the midpoint. Robotics: Side-loaders with a robotic arm (one driver, no loaders) have been introduced in some municipalities and are in the trend; autonomous refuse trucks are trials. (Expert estimate 3/10, already part of the trend in the Métiers 2030 projection, so no extra effect is counted.)

Note: Proxy: all urban maintenance workers (refuse collection, street cleaning, road maintenance).

Sources: base France Stratégie / DARES, Les métiers en 2030 (reference scenario) · jobs, growth 2021-2024, part-time and female share: DARES Portraits statistiques des métiers (FAP 2021), 2024 (incl. self-employed and civil servants) · salary: DARES net median 2023-2025, employees only. Les métiers en 2030 was made on a 2019 base, before generative AI, and differentiates growth per FAP 87 family (FAP 2009); several occupations share a family or are broad proxies. The AI and robotics layers refine per occupation. Salaries are net, not gross.

Read the methodology →


Sector context

Elementary and AI

Éboueurs belongs to the Elementary sector. Occupations in Elementary with high AI exposure tend to remain relatively stable as the work relies primarily on physical, interpersonal, or contextual skills.


AI tools

Which AI tools are already making an impact?

ChatGPT

Career outlook

AI as an asset

This occupation is not directly threatened by AI. The smartest move is to learn the AI tools that strengthen your work: not because you have to, but because it makes you more productive and valuable.


Personal development

Personal development plan

Based on your sector (Elementary) and AI exposure level, here are three concrete steps to future-proof your career.

Start using AI assistants for daily tasks

Familiarity with AI tools is becoming a baseline expectation

→ ChatGPT, Google Assistant
Take a free AI literacy course

Understanding AI capabilities prevents both fear and hype

→ France Travail digital courses, Coursera
Identify repetitive tasks to automate

The first step is knowing where AI adds value in your workflow

→ ChatGPT, Zapier AI

Related occupations

Similar occupations on the map

Agents d'entretien
AI 2/10·0% 2030
Elementary
Gardiens d'immeubles
AI 2/10·-1% 2030
Elementary
Sages-femmes
AI 3.5/10·+8% 2030
Healthcare
Kinésithérapeutes
AI 3.5/10·+4% 2030
Healthcare

About this analysis

AI scores are LLM-estimated using the same methodology as the Dutch AI Exposure Map, making scores directly comparable across countries. Employment 2024, growth 2021-2024, part-time and female share from DARES, Portraits statistiques des métiers (FAP 2021, all workers including self-employed and civil servants); salaries are the DARES net median 2023-2025 for employees, not gross. Occupations are mapped to one or more FAP 2021 families; some are broad proxies or share a family. The 2030 forecast (JPE-prognose v3) starts from Les métiers en 2030 (France Stratégie and DARES, 2019 base) and adds separate AI and robotics layers. These are modelled scenarios, not predictions. A high AI score does not automatically mean job loss. DARES data under Licence Ouverte 2.0; our dataset CC BY 4.0.

Full methodology, sources and download →


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