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BALANCING TECHNOLOGY AND HUMANITY IN HR: HOW AI AND SKILLS-BASED MODELS ARE REDEFINING THE EMPLOYEE EXPERIENCE IN 2026

📘 Volume 13 📄 Issue 6 📅 June 2026

👤 Authors

Dr. PramuKumar Raje Urs, M N 1 , Madhunayaka 2
1. Principal and Professor, Vidya Vikas First Grade College, Mysuru, Karnataka.,
2. Assistant Professor, Department of Management Studies, Vidya Vikas Institute of Engineering and Technology, Mysuru Karnataka,

📄 Abstract

The rapid integration of Artificial Intelligence (AI) and the paradigm shift toward skills-based hiring models are fundamentally reshaping the Human Resource landscape in 2026. This research paper examines the dual dynamics of technological advancement and human-centric workforce management, analyzing how AI-driven recruitment, talent management systems, and skills-first frameworks are redefining the employee experience. Drawing on secondary data from industry reports, surveys, and academic analyses, the study finds that approximately 64.8% of companies now apply skills-based hiring practices, while AI adoption in recruitment has surged from 26% in 2023 to 53% in 2024 and continues to expand. The paper argues that the most successful organizations in 2026 are those that balance AI efficiency with human empathy, ensuring that technology augments rather than replaces human judgment in workforce decisions. The findings contribute to the growing discourse on ethical AI deployment in HR and offer strategic recommendations for practitioners navigating this transformation.

🏷️ Keywords

Artificial Intelligence Skills-Based Hiring Employee Experience Human Resources Talent Management Workforce Transformation UGC-CARE

🔗 DOI

View DOI - (https://doi.org/10.36713/epra28485)

📚 How to Cite:

Dr. PramuKumar Raje Urs, M N, Madhunayaka , BALANCING TECHNOLOGY AND HUMANITY IN HR: HOW AI AND SKILLS-BASED MODELS ARE REDEFINING THE EMPLOYEE EXPERIENCE IN 2026 , Volume 13 , Issue 6, June 2026, EPRA International Journal of Economics, Business and Management Studies (EBMS) , Pages: 176 - 181 , DOI: https://doi.org/10.36713/epra28485

🔗 PDF URL

https://cdn.eprapublishing.org/article/1781986577104-22.EPRA28485.pdf

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