Agentic AI: Transforming the Future of Artificial Intelligence

Recently in one of the meetings, a term was coined “Agentic AI“. This was my first time hearing about it which made me curious to explore more about it.

Agentic AI is still in a very early stage and yet already adapted by many. We were still trying to adjust and learning to collaborate with Generative AI, the introduction of Agentic AI only stress upon the necessity to keep up with the pace of AI growth.

What is Agentic AI?

Agentic AI represents the evolution of the AI systems to be more autonomous in a way by achieving the goal independently. It enables the systems or we can say agents here in a way that they can analyze data, set goals and take actions to pursue them with minimal human intervention.

The continuous advancement in the field of Artificial Intelligence like Natural Language processing (NLP), Machine learning and Reinforcement Learning helped in shaping the path for Agentic AI.

It is about developing the systems that can learn and adapt simultaneously.

Agentic AI and Generative AI

Both Agentic AI and Generative AI differs in many aspects.

Generative AI and Agentic AI also complements each other in a way that former generates the content and the latter uses it to achieve higher objectives.

Agentic AI Benefits

1. The Agentic AI excels at increasing efficiency and productivity. It can take care of boring, repetitive and yet complex tasks with minimal human intervention

2. Agentic AI can change its behavior based on results or feedback from the environment. This creates smarter systems that get better over time without needing to be reprogrammed constantly.

3. Delegating repetitive or complex decision-making will help to focus on higher-level strategic thinking.

4. Agentic systems can work 24×7 with consistent performance ensuring more availability

5. Agentic AI can split big problems into smaller tasks, find the best solutions, and change its approach. This is especially useful in dynamic or uncertain situations.

6. By constantly interacting with users, agentic AI can tailor recommendations and actions to suit individual preferences.

Usage

1. Agentic AI can be used in Finance sector for fraud detection or automating the loan approval process

2. It can also help in automating the insurance claim sytem from submitting the claim to reimbursment

3. Customer Chat bots can help resolve user problems round the clock without human intervention

4. It can help in autonomous vehicles

5. It can help by learning from the user feedback and then help in making educating decision to drive the sales autonomously

The examples mentioned above are just a few of the potential applications and are not limited to these.

Risk and Challenges

Even though Agentic AI has tons of potential, it's not without its own set of challenges. Here are a few:

1. It can lead to lack of transparency on decision making if not monitored continuously.

2. This could also cause job concerns by automating lot of repetitive tasks.

3. This could also cause security concerns as it can bypass some legal guidelines

Final Thoughts

This development in AI is a paradigm shift that has immense potential with seamless boundaries. Without a doubt it is a future of work which will be employed by every industry due to its effectiveness, productivity and robust availability. Though it will take upon some of the work, but it will also open the doors for new opportunities. It will create the new opportunities for better and efficient developers to build and maintain the new agents.