Impact of AI on continuous learning and skill development in the workplace: A comparative study with traditional methods

This study explores the impact of AI-based learning versus traditional methods on continuous learning and skill development in the workplace. It aims to understand how these approaches affect employee training and development, considering both their strengths and weaknesses. AI-based learning, characterized by its personalized and scalable nature, provides on-demand access to tailored educational content, which enhances engagement and allows for continuous learning. However, it also faces challenges related to content quality, and limited focus on soft skills development. In contrast, traditional methods offer valuable benefits such as structured learning paths, hands-on training, and social interaction, which are crucial for developing practical and interpersonal skills. Despite their advantages, traditional methods struggle with flexibility, personalization, and scalability. The findings suggest a hybrid approach that integrates AI’s personalization and accessibility with the interactive and practical aspects of traditional methods. This blended strategy can address the diverse learning needs of employees and ensure comprehensive skill development. Recommendations include implementing hybrid learning models, ensuring content quality, providing continuous feedback, and maintaining flexibility in training delivery. The study provides insights into optimizing learning strategies by combining the strengths of both AI-based and traditional learning approaches to enhance overall effectiveness in employee training and continuous development.