This interactive session equips library professionals with practical strategies for implementing AI chatbots to extend reference services beyond traditional hours. Participants will explore the current landscape of chatbot solutions, from vendor-integrated platforms to custom implementations, and develop evaluation criteria based on institutional needs, technical capacity, and budget. The presentation addresses critical implementation elements including knowledge base development, system integration, privacy safeguards, and accuracy management. Through case studies from various library types, attendees will examine successful deployments and common pitfalls, learning strategies to mitigate AI hallucinations and establish appropriate escalation protocols. Emphasis is placed on change management, including techniques for building staff confidence and setting realistic user expectations. The session explores assessment frameworks using metrics such as query resolution rates, user satisfaction, and impact on traditional reference transactions. Attendees receive practical tools including a platform selection framework, implementation timeline, and staff training templates. Interactive discussion encourages participants to share experiences and collaboratively address common obstacles. This session benefits anyone involved in reference services, technology implementation, or service innovation, regardless of prior AI experience. Participants leave prepared to make informed decisions about chatbot adoption in their own contexts, balancing innovation with the quality and accessibility users expect from library services.
