Data Space and Agentic AI: Orchestrating the next generation of mobility services

To begin with, Zineb Essahli, Chief Strategy & Transformation Officer at G7 Taxis, highlighted the disruption that agentic AI could bring to local mobility services. She raised a central question: how can traditional operators maintain trust and value when AI agents begin recommending and orchestrating transport services on behalf of users? For her, the challenge is not only technological but also economic and regulatory. She emphasized the need for collective rules that ensure fair distribution, algorithmic loyalty, and sovereignty over pricing and services. Rather than being disintermediated, she argued that mobility providers must expose their services to AI ecosystems under conditions that preserve value, transparency, and remuneration. In her view, a European framework for trusted recommendation and data use will be essential to avoid dependency on dominant global platforms.

Next, Nicolas Maynard, SVP Data Science and AI at Accor, explained how agentic AI expands the boundaries of what is possible in the travel and hospitality sector. Unlike traditional systems that operate within isolated booking environments, agentic AI enables a much broader understanding of the traveler’s journey, connecting multiple services into a continuous experience. He described ongoing work on next-generation travel experiences that rely on collaborative data protocols and deeper personalization powered by loyalty ecosystems. However, he also stressed the economic and strategic tension this creates: in a highly concentrated digital market, new value generation often requires redistribution of demand. For Accor, maintaining visibility across its portfolio of brands while integrating into agentic ecosystems is a key challenge. He also underlined the importance of governance, European regulatory alignment, and human validation in decision-making loops.

Moving from industry deployment to technical foundations, Étienne Grass, Global Chief AI Officer at Capgemini Invent, emphasized the scale of the transformation underway. He highlighted the exponential increase in computational requirements associated with agentic AI systems, noting that they consume significantly more processing power than traditional conversational models. For him, the key challenge is not only building intelligent systems but ensuring that they operate on trustworthy, interpretable, and semantically rich data. He stressed the importance of data spaces, contextual data management, and knowledge graphs as the backbone of reliable AI ecosystems. In his view, the future will depend on the ability to manage user context continuously while preserving trust, transparency, and compliance with European principles.

Finally, Yann Hervouët, CEO of Instant System, brought the discussion back to real-world mobility operations. He described agentic AI as a shift from information delivery to autonomous action: systems that can book tickets, discover services, manage disruptions, and dynamically adapt journeys in real time. In complex mobility environments—such as regions with thousands of tariff structures or multimodal transport systems—this capability could dramatically improve user experience. However, he also highlighted regulatory and operational constraints, particularly in the public transport sector, where openness, interoperability, and legal frameworks such as mobility laws require strict compliance. He emphasized that while agentic AI could significantly reshape transport distribution, governance and trust remain essential to ensure fair access and control over public mobility services.

All in all, the panel converged on a shared conclusion: agentic AI will fundamentally reshape mobility and travel, but its success depends on trusted data spaces, clear governance frameworks, and a carefully balanced relationship between autonomy and human oversight. The future will not be defined by AI alone, but by the infrastructures that determine how it acts, what it is allowed to do, and who ultimately benefits from it.

Readers are encouraged to explore these developments further through the EONA-X ecosystem and its work on European data space initiatives.