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This empirical study serves as a primer for interested service providers todetermine if and how Large Language Models (LLMs) technology will be integratedfor their practitioners and the broader community. We investigate the mutuallearning journey of non-AI experts and AI through CoAGent, a serviceco-creation tool with LLM-based agents. Engaging in a three-stage participatorydesign processes, we work with with 23 domain experts from public librariesacross the U.S., uncovering their fundamental challenges of integrating AI intohuman workflows. Our findings provide 23 actionable "heuristics for serviceco-creation with AI", highlighting the nuanced shared responsibilities betweenhumans and AI. We further exemplar 9 foundational agency aspects for AI,emphasizing essentials like ownership, fair treatment, and freedom ofexpression. Our innovative approach enriches the participatory design model byincorporating AI as crucial stakeholders and utilizing AI-AI interaction toidentify blind spots. Collectively, these insights pave the way for synergisticand ethical human-AI co-creation in service contexts, preparing for workforceecosystems where AI coexists.

Synergizing Human-AI Agency: A Guide of 23 Heuristics for Service Co-Creation with LLM-Based Agents