This book investigates how academic and public libraries support entrepreneurs by offering diverse business support services in collaboration with other business support actors. The chapters explore opportunities to innovate these services through artificial intelligence (AI) integration and structured experimentation, with a strong emphasis on co-creation between librarians and entrepreneurs. Collaborative AI experimentations are examined as mechanisms to strengthen adoption factors for Generative AI tools and to support informed decisions regarding adoption or switching to the alternative solutions. Two practical experimentation approaches are introduced: Need-Based Experimentation (NBE), addressing service gaps or operational goals; and Curiosity-Based Experimentation (CBE), encouraging exploratory trials of emerging AI tools. Real-world cases from diverse libraries illustrate adaptable, practice-based examples for providing business support services, conducting AI experimentations, and integrating Monitoring & Evaluation (M&E) for both formative and summative assessments. To operationalize these insights, the book includes AI experimentation policies, structured reporting templates, business case formats, and instructional guides for AI tools such as ASReview, Connected Papers, and Citation Gecko. The book advocates that innovation in libraries is achievable for any institution, regardless of size or resources, through experimentation, patrons engagement in AI experimentations, and embedded M&E practices, positioning libraries as active collaborators within their local innovation ecosystems.

In addition, this book:

• Bridges theory and practice via consulting-led experiences from academic and public libraries supporting entrepreneurs
Empowers librarians to conduct ethical AI experimentations by combining co-creation with monitoring and evaluation
• Translates research into practical insights for library managers to innovate business and traditional services

This book investigates how academic and public libraries support entrepreneurs by offering diverse business support services in collaboration with other business support actors. The chapters explore opportunities to innovate these services through artificial intelligence (AI) integration and structured experimentation, with a strong emphasis on co-creation between librarians and entrepreneurs. Collaborative AI experimentations are examined as mechanisms to strengthen adoption factors for Generative AI tools and to support informed decisions regarding adoption or switching to the alternative solutions. Two practical experimentation approaches are introduced: Need-Based Experimentation (NBE), addressing service gaps or operational goals; and Curiosity-Based Experimentation (CBE), encouraging exploratory trials of emerging AI tools. Real-world cases from diverse libraries illustrate adaptable, practice-based examples for providing business support services, conducting AI experimentations, and integrating Monitoring & Evaluation (M&E) for both formative and summative assessments. To operationalize these insights, the book includes AI experimentation policies, structured reporting templates, business case formats, and instructional guides for AI tools such as ASReview, Connected Papers, and Citation Gecko. The book advocates that innovation in libraries is achievable for any institution, regardless of size or resources, through experimentation, patrons engagement in AI experimentations, and embedded M&E practices, positioning libraries as active collaborators within their local innovation ecosystems.