Schemes for the Developing Enhancing Skills

This work continued to translates the transition to CCAM into a set of concrete, real-world use cases, examining how impacts differ depending on operational context, deployment environment, and service model. This approach highlights that CCAM is not a single uniform shift, but a diverse landscape of applications, each with its own trajectory, benefits, and challenges.

The analysis focuses on a portfolio of use cases across both freight and passenger mobility, including:

• Automated operations in controlled logistics environments (e.g. ports, terminals, warehouses)
• Hub-to-hub and long-distance freight transport
• Urban and last-mile delivery services
• Shared automated mobility services (e.g. on-demand shuttles, robotaxis)
• Fixed-route automated public transport (e.g. buses and shuttle loops)
• Integrated mobility platforms and service ecosystems (e.g. Mobility-as-a-Service models)

A key finding is that deployment potential varies significantly across these use cases. Applications in controlled or semi-controlled environments—particularly in logistics and fixed-route operations—are more mature and scalable in the near term. These settings allow automation to deliver clear efficiency gains, cost optimisation, and operational predictability. In contrast, use cases operating in complex, mixed-traffic urban environments face slower progress due to greater technical uncertainty, regulatory constraints, and public acceptance challenges.

Across all use cases, the transition is best understood as a reconfiguration of tasks and operational models rather than wholesale replacement. Routine, repetitive activities are increasingly automated, while human roles evolve toward system supervision, remote operation, exception management, and service delivery functions. This results in a hybrid operating model where humans and automated systems are tightly integrated, particularly visible in logistics coordination and shared mobility services.

At the same time, the analysis shows that value creation shifts alongside these operational changes. Data becomes central to how services are delivered and optimised, enabling more integrated, responsive, and platform-based models. New service concepts—such as on-demand mobility and digitally coordinated logistics—emerge, supported by continuous data exchange and system interoperability.

However, several cross-cutting challenges remain consistent across use cases. These include uncertain business models in early deployment phases, fragmented regulatory environments, and varying levels of readiness across stakeholders and regions. These factors influence both the speed of adoption and the ability to scale solutions effectively.

Overall, this phase highlights that CCAM will evolve through a portfolio of use cases progressing at different speeds, requiring targeted, context-specific strategies to unlock their full operational, economic, and societal potential.

Read the full report here D5.1 Report analysing the impact of CCAM on each use case

Occupational profiles for educational instruments

Enhancing CCAM deployment across Europe brings distinct human capital challenges. This report takes a use-case approach to provide a sound basis for developing the educational schemes and actions needed to address them, drawing on the same six use cases developed elsewhere in the project: ground transportation for last-mile delivery, bus depot, port/terminal, public (shared) transportation, private (shared) transportation, and shared transportation targeting specific groups.

Key findings

Evidence from across CCAM-ERAS suggests the risk of unemployment from CCAM deployment is low, given Europe's tight labour market — the real challenge lies in finding the human capital needed to enable deployment in the first place. Human capital needs are broadly similar across use cases, varying more by the development phase of a given CCAM deployment than by the use case itself.

From an inventory of the tasks underpinning these use cases, twelve occupations were identified and clustered into four groups: CCAM operations (customer service agents, fleet orchestrators, remote operations specialists, technicians, safety drivers), preparing and enabling CCAM (infrastructure planning and engineering roles), policy and regulation (policy officers, insurance underwriters, app interface developers), and developing CCAM systems (AV systems engineers, compliance officers, cybersecurity specialists). The longlist spans both technical and non-technical roles, and both mid-level and highly educated professionals.

Co-creation sessions and interviews added depth on professional backgrounds and skills gaps. Technical occupations (mechanics, engineers) have a strong formal education base and mainly need to keep pace with fast-moving technology — best supported through short courses alongside formal education. Non-technical occupations need an added layer of CCAM-specific competence on top of their core skills, which non-formal and informal learning (short courses, on-the-job training, learning-by-doing) is often better placed to deliver than changes to formal curricula.

Recommendations

Because professional backgrounds are so diverse, a variety of learning pathways is needed, built around clearly defined learning outcomes. Two occupations were selected for detailed elaboration into full occupational profiles with learning outcomes: the Remote Operations Specialist (EQF level 3) and the Policy & Regulation Officer (EQF level 6), both seen as pivotal to CCAM development. The report recommends employers, sector organisations, governments and educational providers use these profiles — and the wider longlist — as the basis for developing tailored educational provision.

Read the full report here: Deliverable D5.2_Occupational profiles for educational instruments Final