What is Agentic AI? Explore Examples and Benefits of this Autonomous Technology
- Angela Novelli
- May 27
- 4 min read
Different forms of artificial intelligence have begun to grow in popularity and usage over recent years, such as predictive AI and generative AI. These have made their impact on different industries and operations by increasing productivity and improving efficiency. Another form of AI that is continuing to make its mark on the technological world is agentic AI.
Currently, 29% of organizations are utilizing agentic artificial intelligence, and an additional 44% intend to adopt it within the upcoming year. Doing so will allow companies to save money, improve customer service, and decrease the need for human intervention. Let us explore what exactly agentic AI is, its benefits and uses, and how it differs from generative AI.
What is Agentic AI?
Certain types of AI can act autonomously with minimal human supervision and intervention. This is known as agentic AI, where “agentic” refers to its capacity to act independently. It consists of AI agents, which are machine learning models designed to replicate human decision-making processes for real-time problem-solving.
The AI models that most individuals and organizations are used to are those that are built with the need for human oversight. These are trained on specific guidelines that have restrictions for how much the AI can do. However, this is not the case for agentic AI.
Agentic AI, while different from generative AI, builds upon its techniques. Large language models (LLMs) enable agentic AI to operate effectively within changing environments. It applies generative outputs, that one might see while using generative AI, towards specific set goals by calling on external tools to complete tasks. It operates on its own without the need for manual inputs.
What are the Benefits of Agentic AI?
There are several advantages to using this advanced type of AI which are much less limited than traditional generative AI tools. They also have the capability to continuously improve, adapting to be able to handle more and more complex initiatives. Here are a few of the benefits of agentic AI:
Autonomy: The main advantage of choosing agentic AI systems is that they can act independently without the need for human oversight. This is especially helpful when it comes to long term goals and multi-step tasks, significantly improving efficiency and freeing time for human workers to focus on other things.
Proactivity: Agentic AI systems combine the adaptability of large language models with the structured reliability of traditional programming. This synergy empowers AI agents to exhibit more human-like thought and behavior, which provides better results. This form of AI can find and use external information to make decisions and take actions while also tracking and managing data in real-time.
Complex Problem-Solving: While some AI agents are simple and only perform one task over and over, others are more complex and capable of solving in-depth problems. Agentic AI systems and its agents can draw on memory to figure out how to fix a specific issue, and certain architectures allow for a model that acts as a conductor. This means that one agentic model can supervise multiple simpler agents in order to complete a set task.
How is Agentic AI Used?
Let’s look at several examples of how agentic AI is transforming various operations:
Customer Service: Traditional chatbots rely on pre-programmed responses and keywords and also require human intervention at some times. However, with agentic AI, the model can better figure out a customer’s needs with a more human-like understanding. Customers can receive a smoother interaction and have their problems solved much faster, leading to better customer retention.
Application Development: Agentic AI is set to transform application development and innovate the software lifecycle. It has the ability to generate extensive code segments and offer immediate coding improvement suggestions, and can also automate software testing by creating test scenarios, executing them, and analyzing the results.
Healthcare: Agentic AI proactively aids patients, supports clinicians, and optimizes administrative processes, leading to better patient outcomes and more efficient operations. For instance, agentic AI can monitor chronically ill patients through wearables, alerting them and providers to risks, scheduling follow-ups, and adjusting medication for improved management and fewer hospital stays. Also, by analyzing patient data, AI helps clinicians make faster and more informed diagnoses and treatment decisions.
Government: Agentic AI enables state and local agencies to enhance citizen engagement and internal efficiency by managing inquiries, processing applications, offering personalized service information, and simplifying bureaucratic procedures. This allows for citizens to receive much quicker service and for employees to be able to focus their attention on more complex and strategic tasks.
What is the Difference Between Agentic AI and Generative AI?
While some of the techniques of generative AI and agentic AI are similar, they are two different types of artificial intelligence. Generative AI creates content such as text, images, videos, and more based on manually entered prompts. These models analyze large amounts of data and identify patterns in order to provide results for the user’s request. Agentic AI, on the other hand, does not require prompts from the user. It acts autonomously and proactively with limited oversight in order to achieve a set goal.
Key features of generative AI include its content creation and data analysis abilities, as well as its adaptability and personalization. It refines its results following user inputs and can make personalized recommendations based on those inputs as well. Generative AI is used to produce code, essays, streamline complex workflows, and understand customer preferences, among many more uses.
Agentic AI is known for its ability to learn and operate on its own with minimal human supervision. It assesses situations independently in order to make decisions and determine the best course of action. Self driving vehicles are an example of agentic AI that displays the ability of the technology to interact with its environment to gather data and adapt to its surroundings.
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“AI is going to be the key to understanding and solving many of the world’s most complex problems.”
- Satya Nadella
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