The Role and Impact of Learning and Development (LD) Programs, with a Focus on AI Integration, as Perceived by Employees, Trainers, and Managers in an Organization

Abstract

Purpose: In today’s competitive banking industry, maintaining employee engagement and fostering skill growth is crucial for organizational success. This study, which focuses on the UAE banking sector, explores how educational technology and artificial intelligence can enhance lifelong learning and development programs. Despite the increasing prevalence of technology in training, many programs still face challenges such as low engagement, a lack of personalization, and a lack of alignment with the organization’s goals.

Methodology: The study employed a qualitative research technique involving interviews. Semi structured interviews were used.15 interviews were conducted, and participants were selected randomly from each of the three staff categories, including employees, trainers and managers. These groups were purposefully chosen to capture the various levels of involvement and engagement in the banks' L &D programmes in UAE. employed a semi-structured interview guide. Together with primary data collection, secondary sources referring to internal documents, L&D plans, open-source data on industry tendencies, and scientific articles on AI in corporate learning were examined. The data was analysed thematically.

Findings: The implementation of Artificial Intelligence (AI) in the Learning and Development (L&D) programs for the employees in the UAE banking sector is a promising endeavor that has been implemented as a challenge. This research looked at the reception of various levels of employees, trainers, and managers about the changes and efficiency of the AI-based L&D solutions. These studies support that AI has brought ideas of personalization, flexibility, and operational er efficiency and effectiveness into training paradigms.

Unique Contribution to Theory, Practice and Policy: Organizations should cultivate scheduled follow-up processes, including coaching, mentorship, and debriefings. Managers should ensure that they pattern themselves as trainers and supervisors to oversee the implementation of these new skills in the organization and correct any faults, if any, noted. Thus, this follow-up process retains the learning loop and increases the chances of behavioral change. AI systems should also have feedback methods, learning methods and real-time analysis that will enable the learners to keep up and or remain motivated.