AI-driven changes in organizational culture : Insights from organizational change theories

Abstract

Rapid development of artificial intelligence (AI) has led to organizations adopting this new technology. The sudden integration of generative AI has triggered significant transformations in organizations and their culture, necessitating a deeper understanding of these changes. This research explores how AI affects modern organizational culture and assesses whether traditional organizational change theories can help explain these AI-driven changes.

To achieve this, the study employed a qualitative approach, analysing existing empirical data from industry reports and surveys and integrating insights from certain change management frameworks, such as Lewin’s three-step model, McKinsey 7-S framework, and Maurer’s resistance and change model to see, how these traditional frameworks could explain the observed changes.

The findings reveal that AI has significant effects on multiple facets of organizational culture, ranging from workforce dynamics to organizational efficiency and decision-making processes. Effects include also cultural challenges, related to fears of employees, shifts in power dynamics, and concerns about data privacy and ethics. Traditional change management theories were found partially effective in explaining these effects, but they require some adaptations to fully capture all the nuances of AI-driven change.

The research contributes insights into the intersection between AI and organizations, offering guidance for organizations as well as scholars on how to best navigate AI adoption processes and what to consider when trying to align AI usage with organizational goals and minimize the cultural disruptions caused by the change. On top of that, by including the change management models as a framework, this research adds to the theoretical understanding of how these change models can hold up with this new type of change driven by AI.