The Influence of AI on Employee Flourishing in Multinational Companies

As artificial intelligence (AI) becomes more deeply embedded in global business operations, its impact on the workforce has shifted from a purely technological concern to a human development issue. In multinational companies (MNCs), where workforce diversity and operational complexity intersect, the influence of AI on employee well-being is especially significant. While AI has the potential to improve performance and streamline processes, it also presents new psychosocial risks and workplace pressures. Current literature lacks a unified understanding of how AI adoption influences employee flourishing, defined as thriving and dignity, especially across different roles within MNCs. This thesis explores how AI adoption affects employee flourishing in MNCs, applying the Job Demands–Resources (JD-R) model to examine AI adoption as a job demand or a job resource. It aims to uncover the differing experiences of managerial and non-managerial employees and how these shape employee flourishing and future roles in MNCs in the AI era, where a conceptual matrix of AI automation and augmentation is being implemented. The study employed a qualitative, interpretivist approach using semi-structured interviews with 14 employees from various country units and functions within MNCs. Data were analysed thematically, developed based on the literature of the JD–R framework. Findings show that AI functions as a dual impact between job demand and job resource: it enhances efficiency, autonomy, and learning opportunities, but also introduces technostress, job insecurity, and cognitive overload. Managers often benefit from automatic assistance to strategic augmentation and expanded influence, but face increasing role stretch and accountability. Non-managerial employees, particularly in routine roles, encounter more basic automation and task reduction, which may erode autonomy unless offset by reskilling and support. The study presents an updated conceptual model linking AI adoption types to employee flourishing outcomes, mediated across diverse institutional and cultural contexts. AI does not inherently improve or harm employee well-being; instead, its effect depends on how it is designed, governed, and integrated into work. To foster flourishing, MNCs must implement inclusive AI strategies that balance automation with augmentation, prioritise human-centric governance, and invest in the future competencies of both managerial and nonmanagerial employee. The thesis contributes to theory by integrating JD-R and the automation-augmentation lens, and calls for future research on longitudinal outcomes, actor-specific interventions, and industry-level comparisons.