AI-Driven Decision Support Systems for Transforming Employee Engagement and Training in Business

Abstract As organizations navigate increasing digital complexity, engaging, training, and retaining employees has become critical for competitive advantage. Traditional training and decision-making tools often fall short in providing personalized, data-informed support for modern workforces. In response, artificial intelligence-driven decision support systems (AI-DSS) have emerged as strategic tools, leverage predictive analytics, automation, and real-time feedback to enhance employee engagement and skill outcomes. This chapter explores AI-DSS applications that personalize learning paths, automate performance diagnostics, and enhance adaptive training. Examples explored include Amazon’s predictive AI, utilized for onboarding, Microsoft’s AI-driven skilling initiative, UPS’s AI-integrated logistics training, and Harbinger Group’s agentic AI for executive coaching. Beyond operational benefits, AI-DSS tools are increasingly assessed for their capacity to foster trust, ethical governance, and cognitive balance. Research emphasizes the importance of transparency, feedback loops, and human-AI collaboration in maintaining long-term learning retention and critical thinking integrations. By integrating agentic AI, RAG, and behavioral analytics, organizations can reframe employee engagement beyond a static HR function; rather it can be viewed as a dynamic, decision-informed business strategy. The chapter highlights AI-DSS’s role in enhancing workforce satisfaction, skill retention, and organizational agility, establishing adaptive learning as a central artery to enterprise resilience in the AI era.