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Agentic AI brings a new level of advancement in artificial intelligence (AI), as it is capable of goal-directed behaviour, dynamic adaptation, and self-improvement. It influences various significant fields, such as robotics, healthcare, autonomous vehicles, and labor automation. This paper explores the defining features of agentic AI, highlights its differences from traditional AI, and discusses how autonomy, memory, goal-directed behavior, and adaptive reasoning contribute to increasingly general capabilities. Rather than proposing a new architecture, we offer a conceptual analysis of the trajectory from current agentic frameworks to future agentic AI systems. Examining applications in significant fields, including precision medicine, industrial robotics, and self-driving technologies, and discussing societal impacts, particularly concerning workforce disruption, augmentation, and ethical issues arising from agentic AI systems. The paper identifies key research directions for ensuring beneficial and controllable agentic AI development. This work serves as a primary source for exploring agentic AI by compiling existing research and identifying open questions.
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Ashis Pati
Siksha O Anusandhan University
IEEE Access
Siksha O Anusandhan University
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Ashis Pati (Wed,) studied this question.
synapsesocial.com/papers/697e5e0b92e14b406a5e0a4f — DOI: https://doi.org/10.1109/access.2025.3585609
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