Horizon Europe: Quantifying how connected, cooperative and automated mobility deployment could affect employment across the EU-27 member states

The analysis focused on alternative uptake scenarios for three use cases: warehousing, road freight and road passenger transport. Using Cambridge Econometrics’ E3ME model, the work assessed direct, indirect and induced labour-market impacts relative to a business-as-usual scenario. The aim was to help policymakers anticipate transition risks, changing skills needs and potential job displacement early in the CCAM deployment.

The findings were published in the April 2026 report, Moving towards the future: Analytical report on employment effects.

The challenge

CCAM deployment has the potential to change employment patterns across transport, logistics and related sectors. However, the scale and nature of these impacts are likely to vary by country, sector, occupation and speed of uptake.

The project translated CCAM deployment assumptions into quantified employment impacts that can support policymaking, skills planning and transition responses across Europe.

Our approach

Cambridge Econometrics combined scenario design, economic modelling and labour-market analysis.

CCAM uptake pathways, investment needs, cost savings and productivity effects were translated into inputs for Cambridge Econometrics’ E3ME model. These were differentiated by use case and country adopter group, allowing the analysis to reflect different deployment pathways across Europe.

The modelling estimated direct, indirect and induced employment effects. Occupational impacts were informed by sectoral employment changes, historical occupational trends and skills-foresight evidence.

The project also included an interactive Power BI dashboard, enabling users to explore socio-economic outcomes across use cases, adoption pathways and time horizons.

Key findings

• The analysis found that employment impacts are highly context-specific, varying by use case, uptake scenario and national context.

• Warehousing showed the largest effects. Faster CCAM uptake was associated with substantial job losses in land transport and warehousing, while slower uptake allowed investment effects to dominate.

• For road freight, the impacts were more modest but concentrated in land transport and driving-related occupations.

• For road passenger transport, high uptake could generate net employment gains, driven by investment, demand and supply-chain effects.

• Overall, the findings highlight the need for forward-looking skills policies, targeted reskilling and differentiated national transition responses.

Outcomes

The analysis provides a quantified evidence base on CCAM-related employment impacts up to 2050. It covers EU-level, Member State, sectoral and occupational results.

Cambridge Econometrics' outputs include:

• D4.1-Supply-chain-mapping-report.pdf
• D4.2-Report-on-scenario-assumptions-and-their-economic-background.pdf
• D4.3-Output-of-the-modelling-process.pdf
• The D4.4 analytical report, Moving towards the future: Analytical report on employment effects
• An interactive Power BI dashboard presenting scenario results for warehousing, freight and passenger transport

Together, these outputs support evidence-based decision-making by helping policymakers, educators, industry and labour-market actors identify where employment risks, new skill needs and transition-support measures are most likely to emerge.