Mobility stands as a crucial sector insofar the transition to sustainability is concerned and AI, powering smart mobility solutions, is a fundamental building block in this transition to a more sustainable and accessible mobility. Indeed, applications such as Mobility-as-a-Service (MaaS) or the deployment of connected and autonomous vehicles can benefit the environment by lowering pollutant emissions, and can benefit citizens by allowing a fairer access to mobility for all and by improving safety in urban environments.

Hence, many policy initiatives target this nexus: for instance, smart mobility solutions represent a core part of the Sustainable and Smart Mobility Strategy and, furthermore, the positive potential of smart mobility was also established in the Strategic Transport Research and Innovation Agenda (STRIA) roadmap, adopted by the European Commission as part of the ‘Europe on the Move’ package.

AI, by feeding on large amounts of data to extract patterns and insights, can undeniably be a force of change for several sectors in a transversal manner.

However, technology adoption does not restrict to the potential held by the technology per se but, rather, it expands to the sectorial context surrounding it. Hence, from this more holistic perspective, each sector displays its own set of peculiarities (and challenges) with respect to AI uptake.

In this task, we outline such sectoral specificities in the adoption of AI both quantitatively, by blending different streams of data, and qualitatively, through expert consultations and literature reviews.