How Does Agentic AI Work?

• Michael Willson
• April 08, 2025

Agentic AI works by letting machines make decisions without needing constant help from people. These systems can look at data, come up with plans, and act on their own. They don’t wait for detailed commands every time. Instead, they figure things out by themselves. To understand it better, let’s go through the full process.

What Does Agentic AI Mean?

To learn agentic AI, you first need to know what makes it different. Regular AI waits for commands. Agentic AI doesn’t. It decides what needs to be done and figures out how to do it. It manages its actions without waiting for each step to be told.

This means agentic AI has some freedom to choose how it completes tasks. It uses tools, checks results, and keeps learning as it works.

How Does Agentic AI Work? 

Let’s walk through the full process and understand how Agentic AI works:

Step 1: Gather information from all sources

The first thing the AI does is collect data. It pulls this from sensors, websites, devices, or user inputs. It may use:

• Cameras to see its environment
• Microphones to hear sounds or speech
• Text and voice tools to understand language
• Cloud systems or apps to get updates

This step gives the AI full awareness of what’s happening around it.

Step 2: Process the data and make sense of it

After collecting information, the AI begins to sort it out. It looks for patterns and important clues. Then it compares the new data with what it already knows. This helps it understand what problem it needs to solve.

Understanding this part is helpful if you want to learn agentic AI from the ground up. It’s one of the core skills the system depends on.

Step 3: Set a goal

Once it understands the situation, the AI picks a clear goal. This can be a task given by a user or a built-in objective. It now knows what result it’s working toward. This step keeps everything on track and focused.

Step 4: Make a plan to meet the goal

Now that the goal is set, the AI looks at its options. It compares different actions and thinks ahead. It guesses what might happen after each one. Then it chooses the most useful path.

For example, if the goal is to design a product faster, the AI might pick tools that cut down wait time or find smarter ways to test ideas.

Step 5: Act without help

Once the plan is ready, the AI puts it into action. It may use apps, hardware, or other systems. It doesn’t need a person to walk it through every step. It handles tasks like sending reports, changing ad settings, or updating records.

If you’re learning how to learn agentic AI, this is a major point to understand ,  the system handles full tasks on its own.

Step 6: Watch the results

As it works, the AI checks if the plan is going well. It compares what’s happening with what it expected. If anything looks off, it changes its actions. This helps it stay aligned with the goal.

Step 7: Learn and adjust over time

Once the task is done, the AI stores what it learned. It remembers what worked and what didn’t. Then it uses that to do better next time. This step makes the system smarter with each task.

So, when someone asks how does agentic AI work, this is the complete set of actions it follows, from seeing the problem to learning after the job is done.

Understanding how Agentic AI operates is crucial for anyone looking to apply it effectively. For those keen to build real-world expertise, pursuing a Certified Agentic AI Expert™ certification offers structured, in-depth training on these systems.

What are Some Examples of Agentic AI?

These systems are already being used in real jobs. Here are a few examples:

Healthcare

In hospitals, agentic AI agents can sign up patients for trials or check on people after they leave the hospital. This takes work off doctors and helps patients get care faster.

Car Design

Companies like Ford use agentic AI to test car designs and speed up the engineering process. The system picks smarter steps and cuts out delays.

Marketing

Adobe’s agentic AI tools help teams build content and send it to the right people. They can change ad settings, test versions, and pick the best message, all without human input.

What are Some Recent Updates in Agentic AI?

The field is growing fast. If you want to learn agentic AI today, here are some tools and platforms making news:

• NVIDIA’s reasoning models help developers build smarter agents that plan better.
• Salesforce’s Agentforce lets companies build their own AI helpers to run business tasks.
• Manus AI is an AI agent that automates your tasks from writing drafts to sending emails without any human intervention.

These systems aren’t just reacting, they’re making decisions and updating as they go.

Core Technologies of Agentic AI Systems

Here’s a look at what’s inside:

• Large Language Models (LLMs) like GPT-4 help the agent understand tasks
• APIs connect the agent with apps like Gmail, Slack, or payment systems
• Memory tools help it keep track of past work
• Guardrails stop it from doing risky things, like spending too much or sending wrong info
• Sensor tools let it work with machines in factories or hospitals

These tools make it possible to build strong systems that can work in many fields.

How are Companies Using Agentic AI?

By 2025, these agents are running many parts of large businesses. Here are some common uses:

• Business operations: Some agents handle scheduling, orders, or reports.
• Cybersecurity: Others spot threats and stop them before humans even notice.
• Education: AI tutors guide students, give feedback, and change teaching styles based on how someone learns
  .

What Problems Does Agentic AI Face?

Agentic systems are powerful but not perfect. Some challenges include:

• Mistakes: The AI can act on wrong or confusing data
• Too much freedom: It might take steps without clear checks unless a system limits it
• Trust: When it makes choices that affect people, like hiring or healthcare, it must be built with care

Companies are now adding strong review steps and backup controls to avoid serious problems.

What’s Next for Agentic AI?

The next big thing is agents working in groups. One agent might order products. Another one tracks delivery. A third one handles customer questions. All these work together without needing a person to run them all.

This shift will help companies do more without adding more staff. It’s changing how work gets done.

How to Learn Agentic AI from Scratch?

If you’re just starting out and want to know how to learn agentic AI, begin by enrolling into the Certified Agentic AI Developer program by the Blockchain Council. This program will help you look at how agents handle tasks in marketing, health, or design. Learn the basics of the tools they use, like APIs, automation apps, and large language models. Then try simple test projects and build from there. The more you see how systems think, the better you’ll understand how to build or use one.

Conclusion

Agentic AI is no longer just a concept, it’s already part of how modern systems work. From planning tasks to making decisions and learning on the go, these agents handle complex jobs without needing step-by-step instructions. They’re faster, smarter, and more adaptable than traditional tools.

For anyone curious about how to learn agentic AI, now is the perfect time to start. The field is growing, and the skills are becoming more valuable every day. Understanding how does agentic AI work isn’t just helpful, it could shape your future work, projects, or business ideas.