Artificial Intelligence and Knowledge Management in Business Classification in Latin America

Small and medium-sized enterprises play a crucial role in the industrial sector, contributing significantly to regional economic development. Classification and cooperation among these companies are considered key aspects for the efficient management of value creation processes. In some countries of the region, business classifications show varying combinations, reflecting the diversity of geographical approaches, influenced by factors such as economic structure, government policies and local market characteristics. Diversity presents significant challenges to the consistency of business information and can lead to misdiagnosis and inaccuracies when classifying and comparing business levels across countries. However, the digitization of end-to-end processes, adopting data as the primary source of value, has rendered traditional classification models obsolete. This chapter proposes an alternative for classification and collaboration between competing companies, emerging as critical factors in the advancement of the industrial sector. Addressing this challenge effectively requires an adequate re-presentation based on solid structures based on the theory of resources and capabilities. These structures, enriched with relevant variables derived from data, information, and knowledge from various sources, are subjected to the application of variable engineering. This process, supported by knowledge management and artificial intelligence, culminates in the consolidation of relevant models. From these models, specific indexes and metrics are defined that allow an objective evaluation and a meaningful comparison between companies. This contribution provides substantial value to the scientific and business landscape, highlighting the importance of adapting to the digital era to improve efficiency in management and collaboration in the industrial sector.