DOI: https://doi.org/10.36719/2789-6919/57/253-257
Gunash Mammadova
Azerbaijan State University of Economics
Master's student
https://orcid.org/0009-0008-6243-3473
mammadova.gunash.asif.2024@unec.edu.az
The Role of Artificial Intelligence Technologies in Decision-making Processes and Application Models
Abstract
The paper provides an analytical exploration of how artificial intelligence (AI) technologies influence modern decision-making processes, their application models, and methodological foundations. Technologies such as reinforcement learning, deep learning, machine learning and Explainable AI are reshaping various domains of decision-making. Within a comparative sectoral analysis framework, models applied in medicine, finance, public administration, and Industry 4.0 are evaluated in terms of technological readiness level, advantages, and risks.
The findings demonstrate that AI systems significantly enhance the accuracy, speed, and consistency of decision-making. Nevertheless, concerns regarding transparency, potential algorithmic bias, and the need for adequate human oversight continue to create obstacles for the widespread adoption of this technology. The comparative analysis reveals that the financial sector has reached a higher level of AI integration, while public administration advances more slowly due to organizational barriers. Causal AI, multi-agent systems, and regulatory mechanisms emerging within the European Union AI Act framework are identified as key directions for future development. In conclusion, properly establishing the human–machine balance emerges as a fundamental condition for effective and reliable decision-making across various sectors.
Keywords: decision-making, decision support systems, machine learning, artificial intelligence, explainable AI, algorithmic bias, governance, deep learning