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<p>This study explores how small and medium-sized enterprises (SMEs) in the European Earth Observation (EO) sector leverage Artificial Intelligence (AI) to develop innovative business models. Amid the rapid diffusion of AI technologies and increasing availability of open satellite data, SMEs are emerging as key players in the evolving EO landscape. Drawing on a multiple case study of ten AI-enabled SMEs across the EO value chain, the research identifies two distinct business model archetypes: Specialized AI Services for Space Missions and Data &amp; Knowledge as a Service. Each archetype is characterized by unique configurations of AI capabilities across four domains: data capability, technology/algorithm development capability, foundation capability, and AI democratization capability. The findings reveal how upstream firms prioritize onboard automation, embedded AI systems, and institutional collaboration, while downstream firms emphasize scalable platforms, predictive analytics, and accessible, user-centric services. This study contributes to the literature on AI-driven business model innovation by extending capability frameworks to the space sector, challenging assumptions about SME limitations, and offering practical insights for founders, policymakers, and ecosystem stakeholders.</p>

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Configuring Artificial Intelligence capabilities for business model innovation in earth observation SMEs: insights from the European Space Industry

  • 期刊论文

  • 发表日期：

    2026年7月20日

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  • Lara Agostini,
  • Davide Aloini,
  • Anna Nosella,
  • Luisa Pellegrini,
  • Patrick Spieth,
  • Loretta Latronico

摘要

This study explores how small and medium-sized enterprises (SMEs) in the European Earth Observation (EO) sector leverage Artificial Intelligence (AI) to develop innovative business models. Amid the rapid diffusion of AI technologies and increasing availability of open satellite data, SMEs are emerging as key players in the evolving EO landscape. Drawing on a multiple case study of ten AI-enabled SMEs across the EO value chain, the research identifies two distinct business model archetypes: Specialized AI Services for Space Missions and Data & Knowledge as a Service. Each archetype is characterized by unique configurations of AI capabilities across four domains: data capability, technology/algorithm development capability, foundation capability, and AI democratization capability. The findings reveal how upstream firms prioritize onboard automation, embedded AI systems, and institutional collaboration, while downstream firms emphasize scalable platforms, predictive analytics, and accessible, user-centric services. This study contributes to the literature on AI-driven business model innovation by extending capability frameworks to the space sector, challenging assumptions about SME limitations, and offering practical insights for founders, policymakers, and ecosystem stakeholders.