Agentic AI is gaining new insights and advancements in the field of Artificial Intelligence, fostering significant potential to enable rapid transformation across various domains. This rapid advancement and the potential to revolutionize various domains advocate the need for a deeper understanding and firm grasp of the technology. Moreover, an investigation into state-of-the-art research directions in agentic AI needs to be conducted to comprehensively assess the potential scope for improvement and application. Therefore, to address these objectives, a comprehensive review can provide researchers and practitioners with valuable insights into the current state and future research scopes of agentic AI. Hence, this work considers the recently published scholarly contributions in agentic AI across various domains and (i) discusses the fundamentals and working principles of Agentic AI, (ii) traces the historical and theoretical evolution of agency in artificial systems, (iii) explores and discusses Agentic AI’s architecture, working principles, and functionalities, (iv) explores real-world applications of Agentic AI across various domains, (v) analyzes the research findings, identifies current challenges, and discuss potential future research directions, and (vi) proposes a comprehensive framework of stakeholders’ intention to use and adopt Agentic AI with the help of proposed system quality dimensions. Therefore, this systematic review provides researchers and practitioners with a comprehensive understanding of Agentic AI, its current developments and applications, highlights key research gaps, and outlines future research directions.
Haque et al. (Thu,) studied this question.
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