AI-FIEM: Un marco conceptual para la gestión financiera y energética integrada en PYMEs mediante inteligencia artificial en tiempo real
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Abstract
Latin American SMEs employ 67% of salaried workers but contribute only 25% to regional GDP. The productivity gap has multiple causes, including what this paper defines as "informational latency": financial and operational decisions made with delayed or dispersed data. The energy dimension is even more critical: SMEs absorb volatile costs managed reactively, without the ability to estimate their financial impact before materialization. This article presents AI-FIEM (Artificial Intelligence Framework for Integrated Energy and Financial Management in SMEs), a purely conceptual framework, without empirical validation at this stage, that integrates financial management and efficient energy use through real-time information processed by artificial intelligence. The architecture has three layers (data capture, AI processing and inference, and decision cycles) and relies on three mechanisms linking the financial and energy dimensions. Three expanded illustrative scenarios demonstrate the framework's operationalization across representative Latin American industrial sectors. The paper concludes with a discussion of cybersecurity challenges, enabling conditions for large-scale adoption, and an empirical research agenda.
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