AI in Information Professions

AI as Library Practice

AI contributes to core library and information tasks, including:

• Linked data for metadata and knowledge organization:
  • linked data work by OCLC (OCLC Linked Data)
• Search and discovery systems:
  • Ex Libris Primo with the Research Assistant feature.
  • Campus-wide example: University of Kentucky InfoKat Discovery with Research Assistant enabled.

Research Assistant at the University of Kentucky’s InfoKat Discovery

Other examples and resources

The following resources provide examples of how AI is being explored and applied in library contexts.

• Institutional guidance and practice:

  • University of Kentucky Libraries resources on generative AI use
  • University of North Carolina Libraries guidance on generative AI and libraries

• Professional perspectives on AI in public libraries:

  • Using AI on the job
  • Teaching AI and digital literacy in public libraries
  • The future of AI and public libraries

• A Survey of AI tools in Library Tech: Accelerating into and Unlocking Streamlined Enhanced Convenient Empowering Game-Changers

AI as Information System Infrastructure

AI functions as core infrastructure within many information systems. In organizational settings, AI is widely used in the following areas:

• AI interface for internal information systems

  • Example: Microsoft 365 Copilot for organizations, used by many institutions, including campus-wide deployment at the University of Kentucky (see UK's AI offerings)
  • Enterprise-level AI assistants often include data protection and privacy safeguards. For example, enterprise data protection in Microsoft Copilot

• Customer support and service automation

  • Overview: Automating call centers with AI
  • Example: Salesforce Agentforce AI agents (Agentforce AI agents)

• AI introduces new challenges for cybersecurity:

  • AI-driven cybersecurity threats
  • Counter-AI approaches in cybersecurity