The influence of cultural lag on integrating artificial intelligence in software development

Abstract

Background: Material culture evolves faster than non-material culture when new technologies emerge, creating a cultural lag that misaligns society, hinders artificial intelligence (AI) integration, and causes resistance, potentially leading to failed integration efforts.
Objectives: The study applies Ogburn’s theory to the modern context of AI, identifying material and non-material cultures that influence its integration and proposing strategies to reduce cultural lag.
Method: The research is grounded in an interpretivist worldview, employing an inductive, qualitative approach rooted in phenomenology. Semi-structured interviews served as the primary data collection method, and thematic analysis supported by ATLAS.ti provided a systematic approach to analysing the data.
Results: The findings revealed that the company’s material culture reflects a multi-tool AI environment. However, non-material cultures (infrastructure limitations, operational constraints, subscription costs, and procurement choices) created a cultural lag. Strategies to reduce this lag were proposed, including leadership communication, structured enablement and operational improvements.
Conclusion: This study established the need to explore material and non-material cultures influencing AI integration and to develop strategies to reduce cultural lag. While AI can transform industries, resistance because of cultural lag often hinders integration, underscoring the need to understand these cultures.
Contribution: The study contributes a strategy model that can assist software development companies and other industries in addressing the gap between technological innovation and cultural adaptation. The findings seek to benefit software developers, IT professionals, business leaders and academics by facilitating smoother technological transitions and improving AI implementation in the industry.