International Journal of Scientific Research and Engineering Development

Artificial Intelligence has expanded so rapidly that it has reshaped the information environment, which makes it important to understand how librarians view and use these emerging tools. This paper looks at library staff attitudes toward AI and AI-driven systems using the Unified Theory of Acceptance and Use of Technology (UTAUT) as its guiding framework. A structured survey was distributed to 165 library staff working in academic, public, and special libraries throughout India. Using Structural Equation Modeling in AMOS 26.0, the researchers tested how the four UTAUT variables — Performance Expectancy, Effort Expectancy, Social Influence, and Facilitating Conditions — relate to both Behavioral Intention and actual Usage Behavior. Results showed that all four variables meaningfully predict intention to use AI, with Performance Expectancy emerging as the most influential factor (β = 0.421, p < 0.001). The overall model fit the data well (χ²/df = 1.87; CFI = 0.963; RMSEA = 0.047) and accounted for 68.3% of the variation in behavioral intention. Overall, library professionals expressed favorable attitudes toward AI, though issues such as limited skills, weak infrastructure, and privacy worries persisted. The paper closes with practical suggestions aimed at library leaders, policymakers, and AI vendors to encourage stronger AI integration in libraries.

Anjaline R, Dr. Sankar P, "AI-Driven Cataloguing in Libraries: Examining Library Professionals’ Acceptance and Use Through The Utaut Framework" International Journal of Scientific Research and Engineering Development, V9(5): Page(167-177) September - October 2026. ISSN: 2581-7175. www.ijsred.com. Published by Scientific and Academic Research Publishing.