A Multilingual Ai Talent Demand Analysis and Forecasting Using Semantic Analysis and Multivariant Deep Learning

As artificial intelligence (AI) continues to revolutionize various industries, there is an increasing demand for skilled professionals in the field, leading to a significant talent gap and skill shortages. This study aims to understand and forecast the demand for AI professionals across 7 countries in North America, Europe, Australia, and South-East Asia. Using a semantic-based approach to identify relevant job postings, a multilingual analysis was conducted to assess country-specific demand. The US and Canada experienced a significant increase in demand, with a surge in 2020 due to the COVID-19 pandemic. In contrast, the UK and France showed a more gradual increase in demand, while Australia and Singapore demonstrated relatively flat trends. India exhibited a steady and consistent growth in AI demand over the years. Additionally, we analyze the skills that are missing in each country to fulfill AI demand, providing a comprehensive understanding of the talent gap and skill shortages. The US and France showed a shortage of skills in deep learning and artificial intelligence, while Singapore had a shortage in virtual reality skills, and India had a shortage in web-related technologies. Furthermore, we examined the correlation between job demand and factors such as tech industry growth and AI education program availability. The demand for AI jobs is highly correlated between the US and Canada (0.87), and moderately correlated between the US and the UK (0.81) and Canada and the UK (0.82), and low correlation between UK and France (0.30), and France and Singapore (0.08). This suggests a strong link between these countries in terms of …