Agentic Artificial Intelligence: Autonomy, Decision-Making, and Responsibility in the Age of Intelligent Systems
Abstract
Agentic Artificial Intelligence marks an important transformation in the trajectory of intelligent systems, extending beyond conventional models that function under narrowly defined instructions and constant human supervision. In contrast to generative or rule-based paradigms, agentic AI embodies autonomy, independent goal formulation, proactive decision-making, and adaptive responses to the uncertainties of dynamic environments. Through these capabilities, such systems are able to design, revise, and execute multi-step processes with minimal intervention, thereby creating new opportunities for efficiency, personalization, and complex problem resolution across a wide range of fields. Nevertheless, this very autonomy introduces pressing concerns regarding responsibility, fairness, bias, privacy, and the alignment of machine behavior with human values. As agentic AI steadily integrates into finance, healthcare, logistics, enterprise systems, and everyday life, its presence necessitates a careful reconsideration of technical architectures, ethical safeguards, and governance mechanisms. This study undertakes a critical analysis of the conceptual foundations of agentic AI, its emerging domains of application, and the societal risks that accompany expanded machine autonomy. It contends that the sustainable future of agentic AI will not be determined solely by scientific and technological advancement but equally by the capacity of researchers, policymakers, and institutions to establish frameworks that secure accountability, transparency, and respect for human dignity.
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