Agentic AI and Multi-Agent Collaboration: Into the Unknown

Agentic AI and Multi-Agent Collaboration: Into the Unknown

Janpha Thadphoothon

I am sure you would agree with me that the pace of AI's evolution is simply breathtaking. As we know, we're living in a time of radical technological change. Consider ChatGPT; just a few years ago, it was a concept, and now, we're discussing humans and agentic AI agents working side-by-side in virtually every field. AI, I think, is no longer just a laboratory experiment; it's a force reshaping our lives and work.

I am sure you would agree with me that recent scholarly and industry sources converge on the transformative potential of agentic AI and multi-agent collaboration. In my opinion, survey research, such as that presented in Gridach et al. (2025), provides a foundational understanding of agentic AI within the context of scientific discovery, outlining its core concepts, challenges, and future directions. As we know, these kinds of papers are really helpful for getting a birds-eye view of the technical landscape, particularly in specific fields. Simultaneously, the news has it that industry reports, such as those from PwC (2024), highlight the practical applications and business implications of these technologies, emphasizing their role in driving efficiency and innovation across sectors. I think this is where we see the real-world impact. Further, I somehow think that detailed blog posts, like the one from Data-intelligence.hashnode.dev (2024), provide a comprehensive breakdown of AI agents and agentic AI, focusing on core attributes, applications, and ethical considerations.

What we all know and agree upon is that these ethical considerations are crucial. My conviction is that, together, these sources underscore the rapid advancement and increasing relevance of agentic AI and multi-agent systems in shaping the future of technology and society. 

In my opinion, agentic AI and multi-agent collaboration are the next big steps in this revolution. It is my personal belief that understanding these concepts is crucial for anyone wanting to grasp the future of technology and its impact on humanity.

The Future of Collaboration

It is highly likely that humans, AI agents, and perhaps even cybernetically enhanced individuals will collaborate closely in the near future. The news has it that companies are already embracing AI to boost productivity, and I think this trend will only accelerate.

Forms of Collaboration

• AI as Tools: AI systems, as we know, are increasingly used as tools for data analysis, design, and decision-making. For example, AI-powered software can find patterns in vast datasets that humans might miss.
• AI as Collaborators: In my opinion, this is where AI's true potential lies. They say that AI can amplify human capabilities, and I agree wholeheartedly. AI agents can work alongside humans to solve complex problems, providing insights, automating tasks, and learning from human feedback.
• Cybernetic Enhancements: What we all know and agree upon is that humans are already integrating technology into their bodies, from prosthetics to implants. This will, I think, redefine what it means to be human.

This collaboration, I guess it is, will likely bring about increased productivity, innovation, and new opportunities. However, I am not sure but perhaps these changes could either uplift society or exacerbate existing inequalities. My conviction is that we need to approach these changes thoughtfully and responsibly.

The Coming of Agentic AI

Let me introduce you to the notion of agentic AI. In my opinion, the development of agentic AI, which refers to AI systems capable of independent action and goal achievement, is one of the most fascinating aspects of modern technology.

Key Characteristics of Agentic AI

• Autonomy: Agentic AI systems can operate independently.
• Goal-Oriented: They have specific objectives.
• Learning and Adaptation: It is well known that machine learning algorithms form the backbone of this capability.
• Complex Decision-Making: They can make decisions based on incomplete or uncertain information.

Applications of Agentic AI

• Robotics: Autonomous robots for various tasks.
• Virtual Assistants: Intelligent assistants like Siri or Alexa.
• Self-Driving Cars: Autonomous vehicles.
• Game AI: Agents demonstrating strategic thinking.

I think these applications are just the beginning. People say that agentic AI will soon permeate every aspect of our lives.

Multi-Agent Collaboration

AI agents can talk to each other—like humans. In my opinion, multi-agent collaboration, where AI agents work together to achieve a common goal, is a game-changing development.

The Evolution of Multi-Agent Collaboration

Those were the days when everything was simple, but now, AI agents need to work together to tackle complex problems.

Key Challenges of Multi-Agent Collaboration

• Communication: Effective communication is essential.
• Coordination: Agents must coordinate their actions. I think this is similar to how humans need to work together in teams.
• Trust and Reputation: People say that trust is the foundation of any successful collaboration, and this holds true for AI agents as well.

Applications of Multi-Agent Collaboration

• Distributed Systems: Solving complex problems like climate modeling.
• Supply Chain Management: Optimizing the flow of goods.
• Smart Cities: Managing urban systems.
• Military Simulations: Improving strategic planning.

The Intersection of Agentic AI and Multi-Agent Collaboration

The combination of agentic AI and multi-agent collaboration enables highly intelligent systems. For example, in supply chain management, multiple agents could collaborate to optimize logistics. This level of collaboration is truly remarkable.

Ethical and Societal Implications

While the potential is immense, it also raises ethical and societal questions. My conviction is that these questions need to be addressed proactively.

Agentic AI and multi-agent collaboration represent the next frontier. Nevertheless, it is my belief that by understanding these concepts, we can create a future where humans and AI work together for the betterment of society.

I am sure you would agree with me that this is an exciting and pivotal time. But it's the unknown world. We are heading into the unknown.

References:

1. Gridach, M., Nanavati, J., Zine El Abidine, K., & Mendes, L., Mack, C. (2025). Agentic AI for Scientific Discovery: A Survey of Progress, Challenges, and Future Directions. arXiv preprint arXiv:2503.08979.
2. PwC. (2024). Agentic AI – the new frontier in GenAI - An executive playbook. PwC.
3. Data-intelligence.hashnode.dev. (2024). Understanding AI Agents and Agentic AI: A Comprehensive Guide - Pronod Bharatiya's Blog.

Janpha Thadphoothon is an assistant professor of ELT at the International College, Dhurakij Pundit University in Bangkok, Thailand. Janpha Thadphoothon also holds a certificate of Generative AI with Large Language Models issued by DeepLearning.AI.