We invite submissions that advance understanding and practice of agentic AI and generative AI in service contexts. Agentic AI systems represent a paradigm shift in service research: moving beyond AI as a purely data-driven tool to autonomous agents that pursue goals, make decisions, and actively intervene in service processes (Bartelheimer et al., 2025). This evolution—complemented by rapid progress in generative AI—unlocks novel capabilities, from real-time adaptation of service workflows and dynamic multi-agent coordination to seamless collaboration with human workers (Banh & Strobel, 2023; Feuerriegel et al., 2024; Maedche et al., 2016). At the same time, it raises critical questions around control, accountability, and trust: as AI agents gain autonomy, we must understand how to design, monitor, and integrate their decision-making within existing service architectures and hybrid service ecosystems (Bartelheimer et al., 2025).

Exploring agentic AI is therefore not only a technical endeavor but also one of profound societal and economic significance. Autonomous systems can elevate service quality, efficiency, and personalization—reshaping competitive advantage and customer engagement—yet successful adoption depends on organizational readiness and user intention (Weritz et al., 2024). Robust frameworks for ethics, governance, and risk management are essential to guard against misalignment, bias, and unintended consequences in practice (Banh & Strobel, 2023; Feuerriegel et al., 2024), while ecosystem-level perspectives help align human and artificial agency for value co-creation (Bartelheimer et al., 2025). Only through interdisciplinary inquiry—from conceptual modeling and design principles to empirical case studies—can we responsibly harness the transformative promise of agentic AI in service ecosystems.