From HR to XR: Integrating Artificial Intelligence and Extended Reality for Future Workplace Learning
DOI:
https://doi.org/10.63544/ijss.v4i4.202Keywords:
AI, Engagement, Immersive Learning, Skill Acquisition, Workplace Learning, XRAbstract
This study investigates the transformative relationship between Artificial Intelligence (AI) and Extended Reality (XR) technologies and their multifaceted impact on workplace learning, specifically focusing on employee engagement, skill acquisition, and knowledge retention. The primary aim was to examine how adaptive, immersive learning environments influence cognitive, technical, and crucial soft skill outcomes. Utilizing a quantitative research design, data was gathered through structured observations, detailed surveys, and objective performance metrics from participants engaged in an AI-XR enhanced training program. Subsequent analysis confirmed a statistically significant positive relationship between these integrated training programs and superior learning outcomes. The findings further revealed that the AI-XR program not only streamlined procedural practices and technical proficiency but also profoundly influenced learners' emotional and behavioural engagement by fostering a sense of presence and interactive involvement. This underscores the critical importance of intentional instructional design elements, such as high scenario realism, advanced simulation techniques, and responsive AI-driven personalization, for maximizing training effectiveness. These elements directly enhance employee engagement and satisfaction, which are key drivers of overall organizational performance. The research substantiates the substantial potential of AI-XR integration to elevate employee performance through dynamic, scalable, and adaptable technology-driven learning solutions that simultaneously address hard and soft skill gaps. Practical implications emphasize the necessity for a phased, strategic implementation of such programs, ensuring alignment with core pedagogical principles and incorporating mechanisms for continuous evaluation and iterative improvement. Proposed future research directions identify the need for longitudinal studies to assess skill durability, cross-comparative analyses across diverse industry sectors, and deeper investigation into the integration of AI-XR platforms with advanced learning analytics for predictive insights and optimized learning pathways.
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Copyright (c) 2025 Ishaq Farid, Abdullah Javed , Saquib Yusaf , Muhammad Irfan Syed, Muhammad Amoon Khalid , Dr. Hafizullah

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