# AI Agents and Agentic AI-Navigating a Plethora of Concepts for Future Manufacturing

**Authors:** Yinwang Ren, Yangyang Liu, Tang Ji, Xun Xu  
**arXiv:** [2507.01376](https://arxiv.org/abs/2507.01376)  
**Date:** 2025-07-02  
**Summary page:** https://www.summarizepaper.com/en/paper/2507.01376v1/

## Key points

- Authors Yinwang Ren, Yangyang Liu, Tang Ji, and Xun Xu explore AI agents and agentic AI in future manufacturing.
- Significant advancements in AI technologies, particularly in semantic comprehension, complex reasoning, and autonomous decision-making are highlighted.
- The emergence of LLM-Agents, MLLM-Agents, and Agentic AI emphasizes adaptability and goal-directed autonomy in intricate settings.
- These advancements expand the scope of AI in information processing, environmental perception, and autonomous decision-making.
- Opportunities for smart manufacturing are opened up by enabling more efficient processes and innovative solutions.
- Uncertainties remain regarding the definitions, boundaries of capabilities, and practical applications of evolving AI paradigms in smart manufacturing.
- The study systematically reviews the evolution of AI technologies such as LLM-Agents, MLLM-Agents,and Agentic AI to explore their core concepts and technological advancements.
- Potential applications of these technologies in manufacturing contexts are examined along with the challenges they may face.
- The research sheds light on integrating cutting-edge technologies into real-world scenarios to enhance productivity, efficiency, and decision-making processes within manufacturing industries.

## Summary

In their paper titled "AI Agents and Agentic AI-Navigating a Plethora of Concepts for Future Manufacturing," authors Yinwang Ren, Yangyang Liu, Tang Ji, and Xun Xu delve into the realm of  and  within dynamic environments. They highlight the significant advancements in , particularly in  and , which have greatly enhanced  in semantic comprehension, complex reasoning, and autonomous decision-making. The emergence of  further emphasizes adaptability and goal-directed autonomy in intricate settings. The authors discuss how  collectively contribute to expanding the scope of  in information processing, environmental perception, and autonomous decision-making. These advancements pave the way for new opportunities in smart manufacturing by enabling more efficient processes and innovative solutions. Despite these promising developments, uncertainties persist regarding the definitions, boundaries of capabilities, and practical applications of these evolving <kd>AI paradigms</ kd >in smart manufacturing. To address this gap, the study systematically reviews the evolution of < kd >AI technologies</ kd >and explores the core concepts and technological advancements associated with LLM-Agents, MLLM-Agents,and Agentic AI.By examining their potential applications in manufacturing contexts and considering the challenges they may encounter along the way,this research sheds light on how these cutting-edge technologies can be integrated into real-world scenarios to enhance productivity, efficiency, and decision-making processes within manufacturing industries. Ultimately, this comprehensive analysis offers valuable insights into leveraging advanced AI systems for future manufacturing endeavors.