2026 ALISE Annual Conference

Existing studies focus on the application of generative AI for different purposes (Ng et al., 2025; Wibowo, 2025), but studies on the specific use of GenAI for library-related content are limited. There are still gaps in how different GenAI performs regarding library-related content, especially the ones that can be posted on the library’s social media pages. To address this gap, our ongoing research answer these questions: What are the capabilities of generative AI in creating content for library social media posts? How are library social media influencers leveraging generative AI to create library-related content? We prompt-engineer different generative AI using three prompt engineering frameworks to create content relating to specific use cases that align with the ACRL’s (2018) standards for libraries in higher education and school libraries (AASL 2018, 2019). Inferences and analyses of each GenAI’s capabilities are guided using the ISO 9241-11 usability framework (ISO, 1998). By implication, in line with the ISO framework, each generative AI’s capability will be ranked by effectiveness, efficiency, and satisfaction. The categories are also narrowed down to determine their relevance, accuracy, fluency, reproducibility, originality, creativity, coherence, and potential hallucination. We are also using Floridi’s (2023) Unified Framework of Ethical Principles for AI to frame the ethical implication of using generative AI in creating content for library social media posts by both librarians and library social media influencers. This ongoing study will have implications for theory and practice in the use of generative AI by libraries, information professionals, and library social media influencers.