Intro

Researching what type of AI technology suits your business is becoming more and more challenging due to all of the varying terminology associated with AI. With different media outlets and AI vendors using their own language, it can be hard to know which technology is right for you. 

If you’re looking into AI Agents to help field customer service queries, you may have encountered the term Agentic AI. Often heralded as the future of AI-driven customer service, Agentic AI should not really be considered as a separate technology and instead viewed as a new evolution in how AI Agents will function. 

Despite this, many media outlets and AI vendors still define AI Agents and Agentic AI as different things. In this guide, we’ll explore why that may be, how each tool can differ, and finally, show you why the AI Agent of the future will use Agentic AI to make better decisions and fuel more autonomy, flexibility, and productivity in your business… 

What Are AI Agents?

AI Agents are customer-facing automated agents that are task-focused and trained for specific roles. They are more reactive than proactive, using a combination of Conversational AI and Generative AI to understand a user’s query, generate responses, and progress tasks towards the conclusion of the AI Agent’s pre-defined journey. 

Pre-Agentic versions of AI Agents are:

1. Primarily reactive: AI Agents respond to customer inputs via voice or text commands and can understand natural language, but they rarely initiate interactions. Outbound interaction is far more dynamic and varied, which can cause issues and errors for AI Agents that do not use Agentic AI.
2. Pre-trained and pre-defined: AI Agents are pre-trained and their processes are rigidly mapped out to ensure they can progress conversations towards an effective solution.  
3. Efficiency-oriented: AI Agents are built to streamline routine tasks and reduce human workload.

The most beneficial application for an AI Agent is for a process that follows a fixed path and has very clear requirements. Examples range from something simple like a password reset request to a more complex but defined process such as an insurance claims AI Agent – where the agent is responsible for very distinct steps such as collecting a customer’s initial personal details, extracting case information, and then creating a case to route to a human agent.

What Is Agentic AI?

In our What is Agentic AI guide, we shared how Agentic AI creates autonomous, decision-making AI systems that can take initiative and employ dynamic reasoning driven by Large Language Models (LLMs). These systems are proactive and can interpret the goals of its users. Agentic then produces actions and follows them in order to achieve those goals without any human intervention efficiently.

Agentic AI’s features include:

1. Proactive: Agentic AI uses dynamic reasoning to interpret user queries, identify goals, and solve problems as they arise. 
2. Action-driven: Agentic prioritizes taking actions and is integrated with your backend systems and tools to autonomously carry them out. 
3. Retentive memory: Agentic AI has both short and long-term memory to help contextualize and personalize interactions with customers. 

Agentic AI is not a standalone technology and is instead used to create more autonomous AI Agents. These agents, unlike their more rigid, specific task-orientated predecessors are instead trained similarly to a human and then deployed to evolve and learn ‘on the job’. 

What Is The Key Difference Between Agentic AI vs AI Agents?

The main difference between traditional AI Agents and Agentic AI is the level of autonomy each provides. Agentic AI operates autonomously within the space and options you give it, often driving conversations or decisions, while AI Agents require defined customer inputs and pre-mapped conversational flows to operate effectively.

In reality, the term ‘AI Agent’ is becoming increasingly associated with Agentic AI. In the future, an AI Agent will be a general term that describes a customer-facing AI system that harnesses Conversational AI, Generative AI, and Agentic AI to offer the most dynamic, human-like automation journey possible. 

Even in this more advanced world, there will still be practical value that justifies the use of non-Agentic AI Agents. Some customer service tasks require that an AI Agent follows strict processes and does not deviate or improvise in any way. Cognigy.AI’s platform allows enterprise organizations to design AI Agents with this type of strict workflow mapping – as well as creating a separate team of Agentic AI Agents for more complex, variable tasks.

Why choose Agentic AI?

Agentic AI helps directly challenge many of the problems customers have with AI Agents – whether that’s frustration with perceived errors or feeling like they’re interacting with a rigid, impersonal robot. 

Agentic AI helps empower AI Agents that can react dynamically to unexpected queries and variations in language or tone. This means they don’t need to rely on predefined scripts or workflows and won’t produce the type of errors associated with earlier AI systems. 

The main benefit, of course, is that Agentic AI helps improve the chances of successful outcomes by automatically carrying out tasks associated with a user’s goals. While it does this, the AI Agent also uses short- and long-term memory to personalize the interaction. 

Not only does Agentic AI help improve the effectiveness of self-service for customers, but it also supports more complex needs. Agentic AI offers multilingual support across a wide array of channels, such as voice calls, text messaging, and platforms like WhatsApp. This omnichannel capability ensures consistent and accessible service that a customer can interact with whenever it suits them and in whatever language they speak. 

Agentic AI also makes onboarding AI Agents simpler than ever. Rather than having to map out processes rigorously, the AI Agent can be trained in a similar way to your human employees by being given training up-front, access to the tools they need and then deployed to learn ‘on the job’.

Remember, however, that Agentic AI is not used in isolation. As we have already discussed in our guide to Agentic AI vs Generative AI, different types of AI offer the best results when combined within a single AI Agent. 

To summarize, Agentic AI is the perfect solution for enterprise businesses that want to implement a customer-facing AI Agent that can offer genuinely valuable self-service support that speeds up cases, improves productivity, and increases customer satisfaction. 

Why choose AI Agents?

Though we expect the term AI Agent to become synonymous with Agentic AI in the near future, there’s still a case for producing more rigidly defined AI Agents that favor Conversational AI and Generative AI. 

Non-Agentic AI Agents can still offer many of the cost and speed benefits of their more advanced counterparts, but they are more configurable and controllable. For simple, repeatable processes that don’t require advanced automation, there’s no need for Agentic AI and a more standard AI Agent is a better solution.  

You don’t need Agentic AI for a password reset bot. Instead, you can design a simple AI Agent that uses Conversational AI to ask a user a security question and understand the response, then direct the customer down your pre-defined pathway to confirm a successful reset.

Non-Agentic AI Agents are also valuable for your human workforce, who can benefit from Agent Copilot features that help improve their productivity. An AI Agent can, for example, listen in on a call and create an automatic summary/case log in the exact format you have outlined for it, saving your human team 2-3 minutes on every single case. This type of AI Agent doesn’t need the advanced features of Agentic and can focus entirely on performing its task within the required confines. 

Agentic AI Is The Future of Contact Center Automation

Customer-facing AI Agents need to be able to offer human-like experiences that meet the expectations of modern customers. As more and more people become accustomed to interacting with automated systems, their needs grow more demanding. 

Considering that all customer service is about taking those complex customer needs and getting from A to B, Agentic AI helps vastly improve the how. Rather than having to map out every process and spend time planning every possible variation in a customer’s route from A to B, Agentic takes action using its own decision-making processes, making every customer-facing interaction far more efficient.

Though some specific tasks will and should still be handled by more linear AI Agents, the vast majority of customer service automation will now benefit from the inclusion of Agentic AI. With Agentic, your automated AI Agents become smarter – meaning they are better able to solve customer problems and drive improved customer experience outcomes. 

Get started with Cognigy AI Agents

Cognigy.AI offers an AI Agent platform tailor-made for enterprise organizations, with support for hundreds of languages and pre-designed integrations with the tools and systems that power your business. 

Our platform offers a composite AI approach that allows you to swap between intent-based workflows for tightly controlled processes and the flexible, responsive nature of Agentic AI. Whatever your customer service scenario, our AI Agents can handle them. 

Click here to learn more about Cognigy.AI and book a demo to see it in action.