7 Types Of AI Agents & How To Pick The Right For Your Business

What kind of agent can surprise you? Think!

Absolutely, It’s an Agentic AI or particularly you can call Artificial Intelligence Agents.

The use of chatbots for general conversation has been shifted to more sophisticated AI Agents. This market is predicted to grow rapidly, with a 45.1% annual increase projected from 2024 to 2030.

This growth facilitated more demand for automation, advanced use of NLP, and a push for more personalized customer experiences.

Presently, you may have seen companies integrating AI agents into their workforce to streamline processes.

This may include enhancing interaction with visitors, solving their queries, answers to the questions, and execute tasks without constant human supervision.

Another good example of this can be Zomato that introduced Nugget (an smart Agentic AI for modern-day businesses) for complex queries, boosting efficiency, and streamlining support, to help business scales faster with precision.

AI Agents can be of different kinds which certainly varies based on the functionality of Agentic AI. For example, an AI agent integrated into eCommerce would be different from tracking system AI agent.

As I won’t dig deeper into the subject. Instead, explaining the types of AI Agents that ranging from simple task automation to complex multiple purpose.

Types Of AI Agents

As AI agents are trained on large datasets, they can act on various queries in self-paced learning environment using artificial intelligence. In a nutshell, they gather and process input from their environment, interpreting data and make decisions, taking actions accordingly, and improving knowledge an adaptation.

1. Simple Guided Agents

This is the most straightforward AI agent that sees something and reacts instantly — no memory, no thinking. Just “If this happens, then do that.”

Example: If it’s dark, turn on the light.

2. Model-Based Reflex Agent

It’s a one step ahead of simple reflex agent. Such agents designed to survive in partially observable environment. Uniquely, it remembers things and uses that memory to make better choices.

Example: A robot vacuum that remembers where it already cleaned, so it doesn’t go over the same spot again.

3. Goal-Based Agent

This agent doesn’t just react — it has a goal and tries to figure out the best way to get there. Such agents trained on intelligent models and plan sequences of actions to achieve desired outcomes.

Example: A delivery robot that finds the fastest way to your doorstep.

4. Utility-Based Agent

This type of ai agents are well trained for self-making decision by interpreting real-world objects. This agents are designed to do it in the best way possible. It weighs options and picks the one with the most benefits.

Example: A self driving cars that chooses a route that’s fast, safe, and uses less fuel.

5. Learning Agent

By typo its clear that it learns from input, takes time to think, and deliver results. Alternatively, It learns from its mistakes and gets better over time. Kind of like a student that never stops learning.

Example: Your phone’s keyboard predicting your next word better the more you use it.

6. Autonomous Agent

The most popular AI agent of present where it makes decisions on its own, based on the world around it.

Example: A Mars rover exploring on its own, sending back data without waiting for instructions every second.

7. Multi-Agent System

They might work together, compete, or coordinate — kind of like a group of smart coworkers with different roles.

Example: Multiple AI bots in a game — one is attacking, one is defending, and they’re talking to each other.

Conclusion

Agentic AI is the future of communication! Or beyond it, it can do most of human tasks without even a single command from human.

The demand will rise and more companies will integrate into their business environment based on their suitability. What’s next? Gauge your business with mentioned types of AI Agents and enhance customer interaction and experience at a glance.

Frequently Asked Questions

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Ankita Sharma

Ankita is the Senior SEO Analyst as well as Content Marketing enthusiast at The Next Tech. She uses her experience to guide the team and follow best practices in marketing and advertising space. She received a Bachelor's Degree in Science (Mathematics). She’s taken quite a few online certificate courses in digital marketing and pursuing more.

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