Challenges of Integrating AI into SAP Human Capital Management : Understanding Employee Motivation and Leadership Influence from SAP Consultants’ Perspectives - Shah, Munmun (My University, 2026)
This qualitative study examines the Challenges of Integrating Artificial Intelligence (AI) into SAP Human Capital Management (HCM) with particular emphasis on employee motivation and leadership influence in AI-driven transformations. Artificial intelligence tools referred to in this study fall under the category of sandboxed Federated LLM, which means that they are isolated and secure. The study is positioned within the context of growing AI adoption in SAP HCM and SAP Success Factors environments, where AI-enabled tools like SAP Joule and AI Core are increasingly embedded in SAP workflows and applications to improve efficiency, automate routine tasks and support decision making. Although the technological potential of AI in HR systems has been widely studied, less attention has been given to the human and organizational factors that influence whether such integration is successfully accepted and implemented. The study has therefore been undertaken to address this gap by focusing on how employee motivation affects AI integration success and how leadership practices can strengthen motivation during implementation. A qualitative research approach has been adopted. The empirical data have been collected through semi-structured interviews with five SAP consultants with strong professional experience working on AI-related projects in SAP HCM environments. The interviews focused on gathering consultants’ experiences and perceptions related to motivation, technology acceptance and leadership. The interview data have been analysed using thematic analysis to identify themes and sub-themes based on recurring patterns and relationships between them. The theoretical background of the study is formed by the Technological Acceptance Model, Motivation theories like Self-Determination Theory and Transformational Leadership Theory, which together provide an understanding of how technological, psychological and organizational factors interact during AI adoption. The main results of the study indicate that employee motivation is a decisive factor in the success of AI integration, and it influences acceptance, engagement, learning and participation of employees in implementation activities. It has also been found that employee reactions are shaped by how they perceive AI. AI is perceived as beneficial when it is associated with efficiency, support and more meaningful work, but concern is also experienced in relation to uncertainty, role insecurity and the future relevance. Leadership has emerged as a central force in shaping motivation, as employees’ interpretations of AI and their willingness to engage with change are strongly influenced by how leaders communicate, support, involve and guide them. Based on research findings, the study suggests that adoption is strengthened when employees are provided with clear communication, practical training, supportive learning conditions and psychologically safe environments. Overall, the study concludes that AI integration in SAP HCM should be understood not only as a technological change but also as a human- centred and socio-technical transformation. The study contributes to the understanding of AI adoption in enterprise HR systems by showing that successful implementation depends on the interaction between employee motivation, supported leadership and organizational readiness.
Keywords: artificial intelligence; motivation (mental objects); leadership (activity); work motivation; project leadership; Strategic Project Management; Master’s Programme in Industrial Engineering and Management