Abstract
Like the service industry, academia provides intangible outputs (education, knowledge dissemination, research) that directly benefit students, researchers, industries, and society. With the increasing importance of digital technologies, the sector experiences challenges. Generative AI holds promise for creating content, automating tasks, and enhancing organizational efficiency, but implementing it effectively has its challenges. This study investigates the key resources and barriers to the implementation of Generative AI in service-driven organizations. Through a systematic review of recent research, key resources are identified, such as organizational understanding, financial strength, strong technology skills, and positive expectation of results as enablers of successful GenAI implementation. At the same time, barriers like data privacy issues, lack of knowledge, regulatory concerns, and data quality appeared. Our framework shows the most important resources for each phase of GenAI implementation, from early adoption planning to the actual use of GenAI. This study offers practical guidance to help organizations prepare for GenAI, manage critical resources, and overcome common challenges for a smoother, more effective implementation.
Recommended Citation
Essers, Tom; Gülbey, Baran; Hofman, Jelmer; Seinstra, Valerie; Wildenberg, Stephan; and Weritz, Pauline, "Key Resources and Barriers for Generative AI Implementations: Insights from Service-Driven Organizations" (2025). UK Academy for Information Systems Conference Proceedings 2025. 8.
https://aisel.aisnet.org/ukais2025/8