Strategic Coherence and AI-Enabled Personalization: Drivers of Motivation in Corporate Learning

Abstract

As corporations expand globally, corporate training practices evolve in parallel, raising an urgent question: how can individual development pathways be designed to better align L&D strategy with corporate goals for the benefit of both employees and the organization? Recent bibliometric work on organizational change confirms that the misalignment between strategy and learning remains a critical barrier to sustained innovation readiness. Moreover, L&D managers are not yet able to deal with the lack of time and staff engagement (42% and 41% as the main barriers, respectively). There is a large gap in the study of motivation in corporate learning: most articles consider either learning in schools or universities or the technical aspect of technology implementation in corporate learning. This study investigates four potential drivers of motivation – content personalization, environmental dynamism, AI adoption, and strategic coherence. All these factors affect staff, and some of them relate directly to personalized learning strategies. Artificial-intelligence–enabled tutors and chatbots are already tailoring learning paths in real time, mirroring patterns observed in higher-education AI diffusion. Guided by Self‑Determination Theory, we formulate hypotheses linking each driver to specific dimensions of motivation. We will survey employees of large firms who have recently completed corporate training programmes with the help of an author's questionnaire. Our research closes an important gap in understanding employee motivation within corporate learning and provides a springboard for future investigations into additional motivational antecedents. Based on the findings, we will offer actionable recommendations for embedding these drivers in learning and development strategies. When applied effectively, these insights can help organizations optimize training through higher employee motivation.