Agentic AI and Autonomous Agents: Transforming Artificial Intelligence

Agentic AI and autonomous agents represent a major shift in artificial intelligence, moving from passive, rule-based systems to autonomous, goal-driven entities capable of independent decision-making, learning, and adaptation with minimal human oversight. This rise is reshaping industries, research, and society.

Defining Features and Technological Foundations

• Agentic AI refers to systems that autonomously set, pursue, and adapt complex goals, demonstrating advanced decision-making, adaptability, and self-sufficiency (Acharya et al., 2025; Murugesan & Murugesan, 2025; Viswanathan, 2025; Erukude et al., 2025).
• Autonomous agents sense their environment, plan and execute actions, learn from experience, and often collaborate with other agents or humans (Negnevitsky, 2025; Dodig-Crnkovic & Burgin, 2024; Sun & Botev, 2021; Wang et al., 2023).
• Recent advances leverage large language models (LLMs), deep reinforcement learning, and multi-modal reasoning, enabling agents to perform diverse, complex tasks in dynamic environments (Barua, 2024; Erukude et al., 2025; Wang et al., 2023; Zhou et al., 2023).

Applications and Impact

Figure 1: Key domains and applications of agentic AI and autonomous agents.

Challenges and Future Directions

• Ethical and Societal Concerns: Ensuring goal alignment, transparency, accountability, and trust are critical as agents gain autonomy (Acharya et al., 2025; Murugesan & Murugesan, 2025; Hughes et al., 2025; Viswanathan, 2025; Deng et al., 2024).
• Technical Hurdles: Robustness, generalization, explainability, and security remain open research areas (Patel et al., 2025; Deng et al., 2024; Zhou et al., 2023).
• Evaluation: Benchmarks like AgentBench and WebArena reveal current agents lag behind human performance in real-world tasks, highlighting the need for further development (Barua, 2024; Zhou et al., 2023; Wang et al., 2023).

Conclusion

Agentic AI and autonomous agents are rapidly advancing, offering transformative potential across sectors. However, realizing their benefits safely and ethically requires continued research into governance, transparency, and robust technical solutions. Their integration marks a new era in AI—one defined by collaboration, adaptability, and intelligent autonomy.

References

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Murugesan, S., & Murugesan, S. (2025). The Rise of Agentic AI: Implications, Concerns, and the Path Forward. IEEE Intelligent Systems, 40, 8-14. https://doi.org/10.1109/mis.2025.3544940

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Negnevitsky, M. (2025). The Rise of Autonomous AI Agents: Automating Complex Tasks. International Journal of Artificial Intelligence for Science (IJAI4S). https://doi.org/10.63619/ijai4s.v1i2.007

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Patel, A., Patel, H., & Patel, C. (2025). A Survey on the Evolution of Autonomous Agents: Trends, Challenges, and Future Directions. SPU- Journal of Science, Technology and Management Research. https://doi.org/10.63766/spujstmr.24.000033

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Sun, N., & Botev, J. (2021). Intelligent autonomous agents and trust in virtual reality. Computers in Human Behavior Reports. https://doi.org/10.1016/j.chbr.2021.100146

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