Standing in mid-2025, and still looking for resources to explain what agentic AI is and how useful it is for contact centers? Worry not, this write-up is a complete package for you. From what is agentic AI to how it works in customer service, its differences from other AI models, and more, we will cover it all for you. Continue reading, as this blog promises to be both insightful and engaging.
What is Agentic AI?
Imagine a world where no reiteration is required in any customer interaction, and issues are addressed even before they arise. Sounds interesting, right? No customers waiting in the queue, no interaction with incompetent AI bots, and no agents struggling between screens. These are not just exceptional experiences; it’s the real transformation that will convert frustration into friendly interaction. But, how will this happen? The technology hidden behind this transformation is “Agentic AI”.
Now, what is it?
In today’s time, it’s common among customers to interact with the business using multiple platforms, such as chat or phone. Now, without having a proper understanding of conversations on each platform, it becomes difficult for agents to assist customers appropriately. Either they ask them to repeat the issue, or they want them to hold it so that they can check the interaction history.
But thanks to agentic AI. When a customer moves from one channel to another, agentic AI carries context across channels and summarizes the previous conversations. Then briefs the human AI, and the customers don’t have to repeat themselves.
In other words, “Agentic AI” is powered by Agentic Process Automation (APA), which enables AI Agents to develop flexible and responsive workflows that can perform tasks without human intervention. That’s the reason customers highly prefer Agentic AI in today’s customer support environment.
According to a research report by Cisco, “Customers expect 56% of their interactions to be handled by agentic AI within 12 months and 68% within the next three years”.
It is currently the most advanced version of AI that possesses autonomy for solving complex issues in real-time. It is a system that acts independently to accomplish the determined goal without any human intervention. This AI technology utilizes machine learning (ML), large language models (LLM), and reinforcement learning (RL), enabling companies to develop, manage, and deploy various AI agents within a unified platform.
| Also Read: How ChatGPT has Redefined the Role of Conversational AI in Contact Centers? |
Agentic AI is not a tool that requires additional human support to perform its tasks. It is an independent supporting mechanism for customer experience that works autonomously. It is thoughtful, understands reasons, and makes decisions without human intervention.
How Does it Work in Customer Support?
Before understanding the working of agentic AI in customer service, it is crucial to comprehend the multi-agent system (MAS). It is composed of multiple software-based (chatbot) or physical (robots) agents designed to work in a group, accomplish goals, collaborate, and reduce complexities. Each agent in a multi-agent system communicates and collaborates with each other to solve queries, just like a human agent does.
For example, one agent in the contact center is responsible for handling billing, another for taking care of customer queries, and another handles scheduling. All the agents are aligned to accomplish a single goal, which is to offer customer support. These agents are introduced in customer support as agentic AI and can be utilized in various industries, including healthcare, banking, credit unions, and retail.
Now, the question is how multi-agent systems (MAS) and Agentic AI are linked to each other.
Agentic AI is capable of making decisions, taking actions, and acting autonomously. Agentic AI agents are goal-driven and can understand the intent, break complex problems into pieces, plan relevant steps, and act towards achieving the goals without human intervention.
| Also Read: 5 Ways AI-powered Omnichannel Contact Centers can Deliver Better Customer Experience |
Agentic AI is the building block of a multi-agent system. In MAS, each agent can be empowered by agentic AI so that it can make decisions and plan actions like the agentic AI. With the collaboration between these two technologies, it becomes easier to manage complex tasks that a single agent could manage individually.
Furthermore, to understand the functioning of agentic AI in customer support, another aspect to consider is the role of master agents and subagents.
Master Agents, also known as orchestrator agents, act as the manager or central brain of the system. It harmonizes with subagents to ensure all tasks are executed correctly and integrated seamlessly to generate relevant outputs required to achieve desired goals. Master agents are responsible for understanding customer context, breaking queries into subtasks, and assigning those subtasks to appropriate subagents.
Subagents or specialized agents are experts in a specific domain designated to excel in a particular job, such as billing, shipping, inventory management, tech support, etc. It works within a defined space to bring accuracy and speed to the designed roles. Specialized agents are designed to perform deep tasks in a specific area; they use databases, APIs, and internal knowledge bases. Moreover, it can run independently but depends on master agents for assigning tasks.
Now, let’s understand the working of agentic AI through the pictorial representation given below.
How Does an AI-based Agent System Work?
The customer provides instructions to the system, and then the AI agent delegates and executes tasks using resources such as CRMs, inventory databases, or payment platforms. After that, the AI agents review and refine the output, and then share the resolution with the customer.
How Agentic AI is Different From Other AI Models?
Traditional AI is designed to perform specific tasks based on pre-set rules or patterns learnt from data. It operates within a defined framework, based on human programming, and utilizes supervised learning to solve problems within specified parameters.
Whereas agentic AI is an advanced version of an AI model that combines the accuracy of traditional AI with the flexibility and scalability of generative AI. The following are the specialities that make agentic AI different from other forms of artificial intelligence.
⦿ Goal-oriented – Just like human agents, AI agents are also outcome-oriented and work for accomplishing a defined goal to get desired results.
⦿ Enhanced Learning Capabilities – Agentic AI improves the performance of the contact center by learning from interactions and data consumed over time.
⦿ Autonomous – This AI model acts independently, can take required actions without human supervision or instructions.
Benefits of Agentic AI in Customer Service
Incorporating agentic AI in the contact center comes with numerous benefits that help meet customers’ expectations with speed, accuracy, and personalization. Here are some of the standout benefits of agentic AI in customer service.
Improve Customer Engagement
After Agentic AI entered the customer service arena, it has elevated customer engagement to the next level. From offering proactive assistance to focusing on more personalized and contextual interactions, agentic AI offers everything required to engage customers. It is capable of analyzing customer behaviour, detecting their intent, and initiating support interaction even before the problem occurs.
Furthermore, AI agents handle more interactions and close them on a positive note without human intervention. This reduces wait time and also improves the interaction outcome. The data gathered from these interactions is further used to enhance offerings and improve product development.
Enhance Operational Efficiency
Agentic AI automates the entire workflow, not just any specific process or task. It streamlines the process and ensures that all complex operations are performed with accuracy and minimal human intervention.
Agentic AI optimizes operational efficiency by reducing response times and maintaining organizational service standards, even during peak seasons or periods of high pressure. This optimization also saves agents time, sets them free so that they can focus on tasks that require more strategic inputs.
Cost Saving and Scalability
The most important thing that an agentic AI does is reduce cost and increase scalability. Lesser human dependency ensures that AI manages maximum interactions, which automatically reduces operational costs.
Agentic AI promotes scalability by handling 24*7 high-volume calls or interactions without human intervention.
Use Cases of Agentic AI in Contact Center
Agentic AI is designed to evaluate the conversation, understand the context, and respond accurately. This AI model efficiently manages customer queries and addresses challenges by understanding customer sentiment. Using customer data, agentic AI offers personalized responses, suggestions, support, and recommendations that enhance customer experience.
Understand the role of Agentic AI in the contact center through the following use cases.
Quick and Automated Query Resolution
Use Case – Imagine a scenario where a customer contacts a bank and states a transactional issue, wherein the same amount has been deducted twice due to some technical glitch. Here, the master AI actively takes action and assigns the task to subagents. Then one of the subagents checks the transaction history, another one verifies the issues, and the third one suggests a refund based on the company’s policy.
Outcome – With this incident, we can see how the customer gets an accurate resolution instantly with minimal human intervention. Incorporating agentic AI in the contact center reduces average handle time (AHT) and improves First Contact Resolution (FCR).
Active Issue Detection
Use Case – Agentic AI is advanced enough to detect issues before they occur. It consistently monitors customer data, analyses historical patterns, uses predictive models, self-learning capabilities, and automatically initiates outbound communications to let users know about the problem or to assist them before they register a complaint.
For example, if the agentic AI observes a 20% increase in wait times or poor customer sentiments during the interactions, it will automatically predict system slowdown or some issue with the knowledge base and trigger alerts and suggest solutions.
Outcome – This capability of agentic AI transforms the contact center from a reactive to a proactive work model. It reduces agents’ workload, streamlines workflow, and resolves the issue before it arises.
How NovelVox Can Enhance Your Agentic AI Capabilities
Being the advanced version of AI, agentic AI holds many excellent functionalities and enhances the overall performance of the contact center. However, agentic AI cannot utilize all its capabilities to their full potential unless it is integrated with the backend systems and databases. Integrating agentic AI with databases using solutions like CTI Connectors offered by advanced contact center integration platforms (CCIP) enhances the AI’s capabilities and enables it to generate more accurate outcomes. That’s the reason businesses across industries rely on leading contact center integration providers, like NovelVox, to ensure smooth tool integration.
Once the Agentic AI is well-integrated with business applications, CRM, and databases, it effectively resolves each query and gathers data that helps improve future business decisions. Get in touch with experts at NovelVox to boost your AI capabilities and take your business to the next level.
