AIRM: a new AI recruiting model for the Saudi Arabia labor market

One of Saudi Arabia's vision 2030 goals is to keep the unemployment rate at the lowest level to empower the economy. Research has shown that a rise in unemployment has a negative effect on any countries gross domestic product. Artificial Intelligence is the fastest developing technology these days. It has served in many specialties. Recently, Artificial Intelligence technology has shined in the field of recruiting. Researchers are working to invest its capabilities with many applications that help speed up the recruiting process. However, having an open labor market without a coherent data center makes it hard to monitor, integrate, analyze, and build an evaluation matrix that helps reach the best match of job candidate to job vacancy. A recruiter’s job is to assess a candidate's data to build metrics that can make them choose a suitable candidate. Job seekers build themselves metrics to compare job offers to choose the best opportunity for their preferred choice. This paper address how Artificial Intelligence techniques can be effectively exploited to improve the current Saudi labor market. It aims to decrease the gap between recruiters and job seekers. This paper analyzes the current Saudi labor market, it then outlines an approach that proposes: 1) a new data storage technology approach, and 2) a new Artificial Intelligence architecture, with three layers to extract relevant information from data of both recruiters and job seekers by exploiting machine learning, in particular clustering algorithms, to group data points, natural language processing to convert text to numerical representations, and recurrent neural networks to produce matching keywords, and equations to generate a similarity score. We have completed the current Saudi labor market analysis, and a proposal for the Artificial Intelligence and data storage components is articulated in this paper. The proposed approach and technology will empower the Saudi government's immediate and strategic decisions by having a comprehensive insight into the labor market.