Generative AI Meets Knowledge Management: Insights From Software Development Practices

Recent developments in generative artificial intelligence (GenAI) have raised the interest of knowledge management (KM) scholars in artificial intelligence. By harnessing GenAI, KM processes become more efficient, scalable and adaptable to the needs of organisations and users. Taking the theoretical lens of the Technology–Organisation–Environment (TOE) framework for technology adoption, this study investigates the factors influencing the adoption of GenAI among software developers, as a specific group of knowledge workers, in knowledge creation and sharing. Our interviews with 11 developers from 8 countries were analysed by combining an inductive and a deductive approach. We identified five themes alongside the TOE framework, emphasising the adoption factors of GenAI in software development, particularly within KM. Based on our findings, we discuss how GenAI is adopted for KM in software development. In particular, the interviewees liked the GenAI affordances of solving simpler programming tasks efficiently and rapidly. However, GenAI requires expertise to review and modify the code, write suitable prompts and evaluate the reliability of the provided output. Knowledge exchange with fellow programmers is partly, but not entirely, replaced by exchange with GenAI as a new development team member, as it is more efficient. Nevertheless, continuous learning, adaptation and ethical consideration are needed to realise the full benefits of GenAI tools in software development. This study's findings provide broad practical insights into addressing challenges stemming from GenAI integration in KM processes. Additionally, it prompts a critical reflection on the necessity of revising existing KM theoretical models in light of the emergence of AI-generated knowledge.