Abstract
This paper is looking into the metamorphic reverberation of Artificial Intelligence (AI) and Machine Learning (ML) on the ultra-modern employee training and development dynamism. Systematically, a wide-ranging review of literature was conducted to probe the unrolling outlook. Over and above that, factual data were gathered by way of interviews and exploration of experts over manifold sectors to apprehend workable application and consequences.
In the field of workforce development, assimilation of AI and ML has appeared as a progressive force, encouraging radical solutions for employee training and development.
The qualitative methodology utilised in this research paper encompasses a comprehensive and thorough examination and understanding of the circumstances, perceptions, and awareness of key stakeholders, including employees, trainers, and human resource professionals. By way of qualitative methods, the paper intends to gain the affluence and complications of the influence of AI and ML on employee learning.
Semi-structured interviews – conducted with employees and training experts allows for open-ended exploration, allowing participants to demonstrate their opinions on the integration of AI and ML in training programs. The interview questions are outlined to generate elaborate responses with regard to perceived benefits, obstacles and overall interpretations.
Inspecting internal documents, training materials, and policies corresponding to AI and ML applications contribute valuable circumstantial information. This perspective aids in understanding how organisations articulate and accomplish the integration of these technologies into their training structures.
The qualitative data collected is consigned to thematic analysis. This necessitates the recognition and examination of persistent patterns, themes, and codes within the dataset. The goal is to extract relevant insights from the participants’ statements, enabling integrated understanding of the varied consequences of AI and ML on employee training and development.
Results divulged a paradigm shift in training approaches accentuating adaptive learning expedited via AI creed. ML propelled policies vehemently demonstrate content based on individual learner delineation, augmenting engagement and knowledge confinement. Moreover, AI generated simulations and virtual reality are devoted to mesmeric training involvement instrumental in skill acquisition.
Organisations that capitalise on AI in training corroborate considerable gains with subdued training times and profound cost-effectiveness. Continual assessments and feedback loops capacitate employees to respond to skill gaps expeditiously. Additionally, this paper emphasises the increasing significance of virtuous ethical awareness in AI-induced training, guaranteeing fairness, transparency, and unbiased learning experiences.