Enhancing productivity and work engagement: the mediating role of intrinsic motivation toward generative AI knowledge management

Purpose – This study aims to investigate how organizational support – comprising training, work environment and communication – fosters intrinsic motivation toward artificial intelligence (AI)-enabled knowledge management among information technology employees. It further explores how intrinsic motivation influences work engagement and, ultimately, employee productivity. Design/methodology/approach – The study adopts a quantitative research methodology and comprises data from 116 software engineers employed by Fortune 500 companies across the USA, France, Germany, the UK and India. Partial least squares structural equation modeling was used to analyze the data and test the research hypotheses. Findings – Organizational support significantly enhances intrinsic motivation toward AI-enabled knowledge management. While intrinsic motivation does not mediate the link between support and work engagement, work engagement fully mediates the relationship between intrinsic motivation and productivity. This highlights engagement as a key pathway from motivation to performance. Practical implications – The findings provide actionable insights for managers, human resources leaders and digital transformation teams in knowledge-intensive firms. To implement generative AI effectively, organizations should go beyond technical training by fostering a supportive environment and open communication, critical enablers of employee engagement and performance. Originality/value – This study contributes to the literature on AI-enabled knowledge management by applying self-determination theory to explain how support mechanisms shape motivational and behavioral outcomes in generative AI contexts. It deepens understanding of intrinsic motivation in digital work settings and emphasizes the role of engagement in driving productivity.