AI Evolution Explained: GenAI vs LLMs vs AI Agents vs Agentic AI vs Intelligent AI

Posted by Suthahar Jegatheesan on Tuesday, September 16, 2025 No comments

Artificial Intelligence (AI) is one of the most exciting technologies in our world today. But the terms that come with it like GenAI, LLMs, AI Agents, Agentic AI, and Intelligent AI can often feel confusing.

If you are just starting to learn about AI or thinking about how to apply it to your business, these words might make things even harder to understand. That’s why, in this article, I’m going to break it all down in a simple way and explain what each term really means, and where you can use them in real life.

In the old days, our grandparents didn’t have calculators or computers. If you asked them to solve a math problem, they would use their brains and remember everything from memory.

Then came the calculator a small device that changed everything. Suddenly, people didn’t need to calculate in their heads anymore. That was the first big step in intelligent tools.

After that, we got computers. Computers were like calculators on steroids not only solving math but also storing data, running software, and creating websites. This was a revolution for business, science, and daily life.

Then the world changed again with mobile phones. At first, they were just for calling, but soon they became smartphones, and developers started creating mobile apps with responsive UIs. The internet was now in everyone’s pocket.

And today, we are in the AI generation. Just like calculators made math easy and mobiles made connection easy, AI is here to make thinking, creating, and problem-solving easy. This is where Generative AI, LLMs, and AI Agents come in the next steps of evolution.

AI Evolution Explained: GenAI vs LLMs vs AI Agents vs Agentic AI vs Intelligent AI

Generative AI

Generative AI means machines can create new things like text, images, music, even video. the old days where computers only did what we told them, GenAI can imagine and generate content

Before GenAI, Computer were smart calculators, they followed instructions but couldn’t create something new by themselves. If you want to draw a picture, you had to learn Photoshop and draw yourself or you need hire Photoshop developer.

Once Generative AI, a new kind of AI that can create. It doesn’t just show old information, it makes brand new things. GenAI saves time and effort. Instead of learning many skills, you just describe what you want, and AI creates it.

Large Language Models (LLM)

Before LLMs, computers were very limited in how they understood language. A search engine could show you links, but it couldn’t explain ideas clearly. Translators often felt robotic and inaccurate. Writing tools could fix spelling, but they couldn’t actually help you think or write. If you wanted an essay, a translation, or even a simple explanation, you had to do most of the work yourself. Computers saw words only as raw data they didn’t really understand meaning.

LLMs completely changed this. Trained on massive amounts of text, they can now understand and generate human like language. They don’t just repeat facts, they can answer complex questions, summarize long documents, translate with context, and even write essays or code.

Imagine asking, “How I can travel to India from Malaysia?” Instead of sending you to five websites, an LLM gives you a clear explanation in natural sentences, just like a your tourist guide .

This power is what makes Generative AI so useful. GenAI tools like ChatGPT are built on LLMs. Without LLMs, GenAI wouldn’t know how to talk, explain, or create text.

It’s the LLM that gives GenAI its “voice” and its ability to interact with people naturally. In simple words: LLMs are the brains, while GenAI is the creative hand. Together, they make it possible for anyone student, developer, or business owner to generate content, learn new things, and communicate faster than ever before.

AI Agents

Before AI Agents, even with GenAI and LLMs, AI could only talk. It could explain things, answer questions, and generate content, but it couldn’t actually do tasks for you.

For example, if you wanted to book a flight or How I can travel to India from Malaysia?, ChatGPT could tell you the steps, but you had to go and click through the website yourself. If you wanted to reset a server, the AI could write a guide, but you still had to execute the command. AI was powerful, but it was like a teacher or advisor, not an assistant who takes action.

AI Agents changed that. They can not only understand language and generate answers but also take real actions in the world. Think of them as the “hands” of AI.

n AI agent can book a ticket, order a pizza, send an email, or run a script on your computer. For example, on the Trip.com website, the team has implemented TripGenie, which provides detailed assistance related to travel planning.

Agentic AI

Before Agentic AI, even AI Agents needed clear instructions. They could do tasks, but usually one at a time, and they followed a set path. If you told an Agent to book a flight, it could book the flight. But if you asked it to plan an entire trip flights, hotels, activities, budgeting it would struggle, because that requires planning multiple steps, making choices, and adapting along the way.

Agentic AI is the next level. It doesn’t just follow commands it can set goals, make plans, and adapt as it works. lot of company

Intelligent AI

When we look back, every step of AI feels like a new chapter. First, we had computers that could only follow strict rules. Then came Generative AI, which surprised us with creativity. LLMs gave those systems brains. AI Agents gave them hands. Agentic AI gave them planning skills.

But here’s the big question: Can AI ever become truly intelligent?

Right now, even the smartest AI sometimes feels like a clever parrot. It can give amazing answers, but if you push it outside of what it knows, it gets confused. It doesn’t fully “understand” the world the way humans do.

That is why Intelligent AI going to come next . That’s still a research goal. Intelligent AI also called Artificial General Intelligence (AGI). Be Ready with next AGI

Conclusion

AI has grown from simple rule-based systems to today Generative AI (GenAI) and Large Language Models (LLMs), which can create and understand human-like content.

On top of this, AI Agents bring action, and Agentic AI adds planning and autonomy.

The next frontier is Intelligent AI systems that can reason, adapt, and learn continuously, becoming true partners in business, education, and daily life. This article walks through each stage, real-world use cases, to start building toward this future.

Tags AI Azure AI MicrosoftAI

Suthahar Jegatheesan

Suthahar Jegatheesan is Mobile and Cloud Specialist/Architect and he has 15+ years of IT experience as a Technology Consultant /Programmer/Developer in IT industry. Suthahar is an industry luminary focused on AI, Computer Vision, Bot, Machine Learning, UWP, Azure, Xamarin and Web Emerging User Experiences as subject matter expert (SME) in implementation, architecture, development and administration.

About Suthahar →