Impact Factor (2025): 6.9
DOI Prefix: 10.47001/IRJIET
Vol 6 No 7 (2022): Volume 6, Issue 7, July 2022 | Pages: 586-572
International Research Journal of Innovations in Engineering and Technology
OPEN ACCESS | Research Article | Published Date: 09-08-2022
This study investigates the application of artificial intelligence (AI) to design hyper-personalized learning journeys within SAP SuccessFactors Learning Management System (LMS), aiming to align individual development with enterprise goals. By integrating SAP BTP services and machine learning models, the proposed framework dynamically recommends content based on employee behavior, skill gaps, and performance trends. Using a mixed-methods approach combining system review, expert interviews, and simulation on synthetic workforce datasets, the research demonstrates how AI improves content relevance, learning engagement, and internal mobility. The findings indicate that AI-driven personalization significantly enhances knowledge retention and accelerates time-to-skill development. Additionally, the study explores the role of embedded analytics, talent intelligence integration, and ethical AI governance in enterprise learning transformation. This paper concludes with scalable strategies for integrating AI across SAP learning ecosystems to foster continuous, personalized development.
SAP SuccessFactors, Learning Management System, Artificial Intelligence in HR, Hyper-Personalized Learning, Workforce Development, Learning Analytics, Machine Learning in Enterprise Learning, Skill Gap Identification, Career Pathing, Intelligent Recommendations, Talent Intelligence Hub, SAP BTP, Employee Engagement, Organizational Learning Agility, AI-Driven Upskilling.
Manoj Parasa, “Creating Hyper-Personalized Learning Journeys Using AI in SAP SuccessFactors LMS for Individual Development and Business Alignment” Published in International Research Journal of Innovations in Engineering and Technology - IRJIET, Volume 6, Issue 7, pp 568-572, July 2022. Article DOI https://doi.org/10.47001/IRJIET/2022.607127
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