INSPIROSCOPE: Al-Driven Career Path Optimization Using Machine Learning Algorithms and Data Analytics for Personalized Professional Development

Abstract

Career planning plays a critical role in a person's ultimate success within their profession. Traditional career counselling approaches are usually generalised and therefore may not adequately address the individual's needs - making it difficult to come up with proper career decisions. This can lead to confusion, inefficient skill development, and limited job opportunities.
This paper presents INSPIROSCOPE, a machine learning (ML) and data analytics-based approach to delivering personalized career recommendations through an Artificial Intelligence (AI) framework. INSPIROSCOPE analyses an individual's profile, which includes their skills/experience, level of education, interests, and additional factors such as trends within specific industries, and supply and demand within the labour force. This analysis is performed using predictor models as well as looking for trends across a number of variables.
With INSPIROSCOPE, individuals are able to make an informed career choice based on data, thereby improving their chances of aligning their skills to what specific industries require. Additionally, INSPIROSCOPE provides individuals with a greater likelihood of successfully pursuing their personal and professional development through on-going education and ultimately enhancing their career development through intelligent and customised suggestions.