Insights from a Dynamic KSA Taxonomy Framework: Top 10 Wanted Knowledge, Skills, and Abilities for the INFOCOMM Sector in Mexico

The Industry 4.0 workforce, especially in the INFO-COMM sector, demands flexibility in upskilling and reskilling, in line with the speed of technological change. This study analyzes the implementation of a dynamic knowledge, skills, and abilities (KSA) taxonomy that adapts to the changing needs of the labor market and presents an implementation-using Artificial Intelligence (AI) tools, including natural language processing (NLP) and machine learning - that allows the identification of the 10 KSAs most required by the workforce. The methodology used included collecting and analyzing data from various sources, including job postings and industry reports, to create a flexible and predictive model. The discussions accompanying this study expose what type of information can be obtained and how this dynamic approach ensures that the academic and industrial sectors remain agile and responsive to technological advances and market changes. On the one hand, academia can use it as a robust tool for curriculum development, as by being able to update the taxonomy annually, educational institutions can flexibly align programs with market requirements, improving graduate employability. On the other hand, the industry can leverage it for its targeted training offerings and leverage these insights for strategic workforce planning. Future research will focus on expanding this implementation to diverse regions and sectors, further refining its predictive capabilities and exploring its long-term impacts on education and industry performance.