Autonomous AI Agents: Applications, Challenges, and Future Prospects
Keywords:
Autonomous AI agents, Foundational Models, Generative AI, artificial intelligence, machine learning, Internet of Things (IoT), system optimizationAbstract
Autonomous AI agents are intelligent entities leveraging one or more large language models (LLM’s) to perform complex tasks autonomously to achieve a specific goal. The autonomous learning, decision-making, and action capabilities of AI agents distinguish them from traditional AI systems. Use of these agents can enhance diagnostic accuracy, optimize manufacturing processes to reduce waste and improve efficiency, predict demand to manage inventory more effectively among other applications. Despite their promising applications, deploying AI agents present significant challenges, including ethical implications, explainability issues, and security risks. These challenges often stem from the potential misuse in sensitive areas such as healthcare and autonomous decision-making. This paper reviews the applications and possibilities of Autonomous AI agents in process redesign, decision making and system performance improvements. We further discuss the integration of these agents with advanced technologies such as blockchain, the Internet of Things (IoT), and edge computing to amplify their capabilities. While this integration enhances efficiency and scalability, it also presents challenges that must be addressed to ensure the ethical and responsible deployment of AI agents, to enhance their impact and utility across various fields. Finally, we identify key areas for further research and investigation to optimize the design and secure application of AI agents across diverse applications.
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