Cloud-Based And AI-Enabled Career Path: A Meeting Point For Students, Parents, Higher Institution And Industries

Abstract

Abstract Today, technology is progressing rapidly and the new profession appears almost every year, the role of the career counseling is becoming even more important. The suggested concept for developing a cloud-based AI solution for the process of career choice can be considered as the theoretical contribution of this study as it is aimed at creating an extensive platform for cooperation between students and parents, academic and industrial institutions. Basing on quantitative approaches, this model aggregates different types of information and utilizes such high-level AI techniques as machine learning to provide individualized career suggestions matched with the specific preferences, abilities, and gaps in one’s professions. Categorically, the paper identifies the factors of the proposed model as well as assesses the effectiveness of applying the model in improving career decision making based on the extant literature and statistical analysis. Consequently, the study stresses on the role of cloud-based, AI- supported solutions in transforming the landscape of career counseling services and collaboration between all the links within the education-employment chain. Majority of the participants gave their satisfaction on the possibility of the model to be used as a collaborative tool for students, parents, higher institutions, and industries so that a right career decision can be made and for education and employment to be anointed. Therefore, the study recommended the following: Here, it is imperative to assess how well the model is performing and what the users of the flow have to say about it from time to time. Engage all the stakeholders such as the students, parents, the institutions of higher learning, and industries in the current process of developing and enhancing the model. It will be necessary to consider the model’s ability to be as available to different user groups and demographics as possible. Provide the users with educational and training materials that would enable them to fully understand how to use different aspects of the model. Enhance relationships with industry associations to leverage expertise in expanding the model’s data inputs, and education institutions for immersion training opportunities and knowledge of developing trends and skills shortage.