Agentic AI is the tech buzzword of the moment, but if you find yourself wondering what all the hype is about, you’re not alone. What is Agentic AI, how far along are we in developing the technology, and why are people so excited about its potential? Let’s talk all things Agentic AI.

To understand what Agentic AI is, it can be helpful to first call out what it is not, GenAI. The defining characteristic of GenAI is to generate content based on large amounts of data in response to prompts. In contrast, the defining feature of Agentic AI is its ability to act independently, making decisions, acting on those decisions, and even learning from experience. Instead of responding to prompts, humans give Agentic AI specific objectives and Agentic AI dynamically acts to achieve those goals.

Agentic AI is different than straight AI chatbots. Chatbots respond to prompts generating content. In contrast, Agentic AI learns and takes action. John Berg offers a great example to illustrate the difference between a chatbot and Agentic AI. Imagine you want to know if a piece of hardware is compatible with your smart home network. You could ask a chatbot, which might “provide a scripted response” confirming the hardware is compatible based on its training data knowledge. In contrast, Agentic AI could “analyze real-time images or video of the device, cross-reference this with historical data, and autonomously guide the user through a complex troubleshooting and resolution process” ensuring the device is compatible in real time based on your personal home setup.

In other words, Agentic AI “doesn’t just talk—it thinks and acts.” Agentic AI’s combination of sophisticated reasoning, independence, and action make it a very exciting technology. Instead of just turning to a chatbot to answer questions or produce content, we can put Agentic AI to work across the enterprise as extra employees available 24/7 to improve processes, problem solve, and support humans.

As Bernard Marr explained, Agentic AI “can take initiative, solve complex problems, and adapt its approach based on changing circumstances. It's like having a tireless, hyper-intelligent intern who not only follows your instructions but also anticipates your needs and comes up with creative solutions you might never have considered.”

Sounds pretty cool, right?

How far along are we in developing this technology?

We can break Agentic AI down into eight key abilities:

1. Autonomy—needs no human intervention

2. Proactive—can anticipate what will happen next

3. Adaptability—experience based flexibility

4. Action—can make independent acts

5. Decision-making—models to make decision

6. Goal oriented—takes actions to achieve specific objective

7. Perception—gathers new information that can change its action

8. Learning—based on new information, can modify behavior

Of these eight abilities, current Agentic AI is pretty capable in carrying out #1-5. It's autonomous meaning it doesn't need human intervention to do something. It's proactive meaning, for example, it can start to look at trends and data and anticipate when something's going to happen. It can adapt by doing things like looking historically at what's happened and changing its output based on the experiences that it has seen. It can take action to achieve goals. And it can look at data and decide which action it is going to take.

Where Agentic AI still needs to develop is being goal oriented, and its perception and learning abilities. One of the defining characteristics is the ability to define a goal or outcome. This technology is still developing the ability for a master agent to not only be able to interpret that goal, but to establish which other agents it can engage to get the information and take the actions to achieve that goal. It is also still developing the ability to gather information from different sources that could perhaps change its course of action and perceive how that information matters. Agentic AI is able to look at data, decide which action it's going to take, execute that action, but it should also be able to learn from the responses of that action.

Where Agentic AI will improve over time is its creativity and ability to achieve outcomes in ways that surpass what humans might have imagined. As Agentic AI improves over time, it will work out better ways to get to a goal, trying out different models to use to achieve the same thing. This means Agentic AI will improve over time, becoming more effective, useful, and innovative.

What are people so excited about Agentic AI’s potential?

Agentic AI is garnering so much hype because it offers a concrete business use case with clear ROI, something other AI capabilities have struggled to deliver. AI agents can:

• provide customer service freeing up human agents to address the most complex cases
• serve as personal assistants helping support employees to do their work better and faster
• improve processes like delivery routes and supply chains
• offer 24/7 monitoring of things like network security or a hospital patient’s health
• optimizing logistics, inventory management, and demand forecasting by analyzing data and making decisions that ensure efficiency

Because agents can act independently, they can be deployed to improve work throughout a business, providing round-the-clock services.

What does this mean for the future of work?

For us humans, Agentic AI is not likely to replace us but instead transform our work. Agents will augment and support our work. Instead of performing tasks, some of our jobs will also become monitoring systems doing those tasks for us. We’ll become managers of entire teams of AI agents, ensuring they are carrying out their objectives effectively.

So, there you have it. A quick rundown of Agentic AI and why it is generating so much buzz.

What do you think? Is Agentic AI worth all the hype?