Identifying opportunities for artificial intelligence in the evolution of training and development practices

Purpose The fast pace of innovation and disruption in business processes and technology today requires employees of organizations to be continuously up-skilled and be able to adapt to changing practices. Training needs are becoming more personalized. Micro-learning and byte-sized training modules, easily accessible to employees, as and when required, are some of the major organizational needs. Training and development programs should be designed keeping in mind factors of employee engagement, involvement and extent of training transfer. The purpose of this paper is to explore whether artificial intelligence (AI) can lead training and development processes in organizations in the years to come. Design/methodology/approach The author has interviewed 27 HR and training professionals, in person, from across eight organizations in the FMCG, oil and natural gas and clothing and apparel industries. All these organizations have an annual turnover of greater than US14. 5m. A formal questionnaire was not followed since this research explores a new field in academia. Open-ended questions were used in the interviews, of which eight were common across all interviews. The mean interview duration was 25 min 33 s. The objective being to capture ideas and identify future trends, the analysis was done on a percentage basis and served as the foundation for a new training and development needs model for organizations. Findings Among the 27 HR/training professionals interviewed, 92. 6 percent respondents believed that their organization/department requires knowledge management practices while 40. 7 percent require the training content delivered to a fixed category of employees, to be updated continuously. Personalized learning was mentioned as a requirement by 63 percent of the respondents. In total, 92. 6 percent HR/training professionals believed training programs should involve high employee engagement. In total, 51. 9 percent would prefer on-the-go learning tools for their employees, while 33. 33 percent respondents believed an intuitive e-learning interface would be useful for their organization/department. The findings also led to the foundation of an SIP model, which shall be useful in providing direction to AI systems in training and development practices. Research limitations/implications The paper opens up avenues for further research to be conducted in identifying the areas of impact of AI in training and development. It paves the way for researchers to quantify training effectiveness and measure it with the help of AI. Practical implications The objective of the paper is to explore the opportunities for AI in training and development practices. Having identified the opportunities, it shall drive the practice of using AI across industries. Originality/value The thoughts in the paper have been ideated by the authors organically. Relevant data points from referred sources have been cited to back up those thoughts.