From Resistance to Readiness: Healthcare Workforce Adaptation in AI- Driven Digital Transformation

Abstract

Artificial Intelligence (AI) has been identified as one of the key change drivers in the evolution of health care facilities across the globe. However, the implementation of AI-based digital technology is not only the advancement of technology but also the workforce’s alignment with it. Though AI- based digital technology is increasingly becoming popular in health care facilities across the globe, workforce resistance to its implementation remains a major issue in its sustainability. This study aims to identify the perceptions of employees in Bengaluru on the prospects and limitations of AI- based digital technology in health care facilities and the major factors contributing to workforce resistance. The study employed a qualitative methodology. Fifteen employees from various departments of a health care facility were interviewed through in-depth interviews, including doctors, nurses, technicians, administrative staff, and IT employees. The findings revealed seven major factors contributing to workforce resistance: dependency on digital technology, reliability of digital technology, data security apprehensions, training perceptions, emotional attachment to traditional methods, alignment of technology with tasks, and uncertainty regarding performance outcomes.
Employees are aware of the operational efficiency of AI technologies, particularly in improving workflow efficiency. However, resistance escalates when technology reliability is low, organizational support is limited, and change is not communicated in a structured manner. Perceived usefulness alone was not adequate to prepare the workforce. The research contributes to the human capital discourse in the broader AI adoption movement by offering a framework on management strategies involved in the transition from resistance to readiness.