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How Agentic AI uses data to make decisions and solve problems

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How Agentic AI uses data to make decisions and solve problems

in Artificial Intelligence
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How Agentic AI uses data to make decisions and solve problems
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Athira Sethu

Kochi, 30 May 2025

Artificial Intelligence (AI) has evolved a great deal in the last few years. AI initially was only capable of predicting outcomes through data analysis. Subsequently, generative AI emerged, capable of generating items such as images, music, and text. Currently, we are in yet another phase known as Agentic AI. This advanced AI type does not merely predict or generate — it can think, act, and learn independently.

Agentic AI is unique in that it has the ability to make decisions on its own without needing constant human intervention. It is able to perceive its environment, perform tasks, and improve with time through learning. Consider it as a computer assistant that is able to operate independently and learn from experience. These AI “agents” are able to assist humans to get work done quicker, smarter, and more effectively.

This technology is already helping businesses in many ways. In customer service, for example, AI agents can chat with customers, solve problems, and give support day and night. In sales, they can find potential customers, schedule meetings, and follow up automatically. In marketing, agentic AI can plan campaigns, track results, and even suggest improvements. These tasks usually take a lot of time and people — now, AI can handle much of it on its own.

One of the most significant aspects of agentic AI is how efficiently it learns. When an agent is incorrect, it can apply the feedback to learn better next time. This implies that the more it operates, the smarter it gets. Gradually, agentic AI proves to be increasingly useful, precise, and effective. It also interacts perfectly with large-scale data systems, making organizations utilize all their data in brighter manners.

Agentic AI software is also versatile. It can be applied across numerous industries such as healthcare, retail, finance, and manufacturing. It allows companies to save time, save money, and yield better outcomes. Technologies such as Agentforce are already demonstrating how this plays out in the real world, like a virtual team supporting workers and contributing to companies’ growth.

Experts predict that agentic AI by 2028 can assist in making up to 15% of daily work decisions. Although new, the future seems rosy. As agentic AI continues to develop, it will transform the way we work, problem-solve, and interact with technology on a daily basis.

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