ARTIFICIAL INTELLIGENCE – BASED INVOICE TECHNOLOGIES IN MODERN ORGANIZATIONS
ARTIFICIAL INTELLIGENCE – BASED INVOICE TECHNOLOGIES IN MODERN ORGANIZATIONS

Summary/Abstract: The paper proposes an integrated methodological and technical framework for the evaluation and selection of management and billing technologies in a modern organizational context. The research compares three distinct technological modules: T1-blockchain, smart contracts, and artificial intelligence, T2-classic database and AI, and T3-hybrid solution with database (DB), blockchain, and AI components. The purpose of the research is to develop an integrated technological model for the comparative evaluation and selection of the optimal management and billing technology in a specific organizational context. The main research objectives are: (1) comparative analysis of invoice management technologies, types of billing technologies and invoice formats; (2) Selection of indicators for the comparative evaluation of technological modules; (3) determination of indicator values through software simulations and AI modules; (4) discovery and analysis of correlations between invoice types and technological modules; (5) integration of scores for each combination of invoice type and technological format; (6) analysis of correlations between indicators and billing technologies and invoice formats. The main research tools were: artificial intelligence algorithms, Python and graphs to perform evaluations and correlative and comparative analyses. The research contributions consist of providing a unified framework for comparative evaluation, developing measurement metrics, integrating simulations with artificial intelligence applications, and using modern comparative analysis tools to highlight the correlations and performances of emerging technologies. The results obtained have particular value, being based on an original and relevant interdisciplinary comparative approach contributing to reducing technological risks and optimizing costs in digital billing processes

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