What Is an AI Virtual Agent?

Alexander Christodoulou
Authors name: Alexander Christodoulou
What Is an AI Virtual Agent?
17:15
Table of Content :
  • Intro

  • AI Virtual Agent Explained

  • How Does an AI Virtual Agent Work?

  • Benefits of AI Virtual Agents

  • Use Cases of AI Virtual Agents

  • AI Virtual Agent Examples

  • Best Practices for Implementing AI Virtual Agents

  • The Future of AI Virtual Agents in Contact Centers

  • Frequently Asked Questions

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Intro

AI-driven automation is transforming every industry, but it has the most significant impact on customer service applications. With automated agents that can communicate with customers and perform tasks, enterprise organizations can eliminate wait times, speed up routine tasks, drive down costs, and improve overall customer service satisfaction. 

Compared to earlier automated tools such as chatbots, which were limited to specific, pre-defined responses and logic, AI Virtual Agents are more similar to the capabilities of a human agent. They can communicate with customers, identify their needs, reason their way to a solution, and then take action independently to resolve the problem. Read Chatbots vs AI Agents to learn more about the differences. 

In a contact center environment, where rising customer call volumes are difficult to manage without spending a fortune on hiring additional human teams, AI Virtual Agents represent the most cost-efficient way to assist customers and improve operational efficiency. 

AI Virtual Agent Explained

An AI Virtual Agent, or simply an “AI Agent” from Cognigy’s perspective, is a customer-facing virtual agent that utilizes AI to process language, communicate with customers, and carry out actions. AI Agents are sometimes also referred to as AI Assistants – see our AI Assistants vs AI Agents article to see why. 

AI Agents are trained using a combination of Large Language Models (LLMs), Natural Language Understanding and enterprise knowledge to offer customers expert, personalized self-service options. They are available 24/7, respond to queries instantly, and can communicate in 100+ languages to provide a high standard of customer care. 

An AI Virtual Agent from Cognigy offers: 

  1. Human-like conversation: AI Virtual Agents understand customer intent, context, and sentiment, allowing them to converse in a dynamic, human manner. 
  2. Dynamic reasoning: With Agentic AI, agents can reason their way through tasks to plot and pursue goals independently, without the need for direct human supervision. 
  3. 24/7 omnichannel availability: AI Agents have no ‘downtime’ like human workers; they can be deployed across multiple channels and can respond 24/7, giving customers support exactly when needed.
  4. Personalized, adaptive learning: AI Agents learn and adapt from every customer interaction, utilizing both short and long-term memory to improve service. 

How Does an AI Virtual Agent Work?

AI Virtual Agents are not tied to a single channel. They are integrated with your backend systems, meaning customers can interact with them across many different devices or platforms. They can complete tasks such as updating details in a CRM, tracking down a lost order or even processing a refund or rebooking. 

A combination of different AI technologies powers the AI Virtual Agent: 

  1. Conversational AI: This type of AI gives the agent language capabilities and uses Natural Language Understanding to understand and interpret customer voice or text input. 
  2. Generative AI: This is what allows the AI to generate content in response to user prompts and queries. 
  3. Agentic AI: A new advancement in AI technology that allows a virtual agent to independently plan and plot goals. 

AI Virtual Agents can be trained in two different ways depending on the role they will play within your organization…

You can carefully design conversational flows for process-driven tasks where you need simple, effective automation that doesn’t stray from parameters. You can then deploy an NLU-powered Conversational AI Agent that offers flexible conversational capabilities but closely follows your dialogue flows and process structure. 

For more versatile customer service requirements, you can train an Agentic AI Agent similarly to how you train a human team. You give them upfront ‘training’ via your knowledge base and LLMs, which provides them with contextual understanding. They can then use dynamic reasoning to identify user needs and any additional information, tailor a personalized response, and then carry out actions autonomously.

With Cognigy’s own AI platform, you can also deploy a composite AI Agent that combines these two approaches to offer more flexibility and control over customer processes. This means you can have a dynamic, flexible AI Agent handling the majority of a customer call before switching to a strict, process-driven agent to carry out a specific task.

Benefits of AI Virtual Agents

For enterprise businesses that need to continue to scale amidst rising customer demand without heavily increasing their costs, the benefits of autonomous AI Agents are incredibly compelling: 

Instant Customer Support

Customers value speed and efficiency when contacting your organization. They don’t want to be left on hold or passed between service teams as they try to get an answer. Cognigy’s AI Virtual Agents provide rapid support, answering customer queries nearly immediately and offering 99.5% faster response times than human agents. 

Improved Employee Efficiency

Not only can AI improve customer processes, but AI Agents can also benefit your existing human teams. By automating low-complexity, highly repetitive tasks, an AI Agent removes some of the most tedious tasks for human agents and frees them up to focus on more valuable, rewarding problems. 

Additionally, an AI Agent can provide live assistance during the call, transcribing, translating, and offering personalized answers to your human agent’s screen so they can resolve queries faster. Once the call is completed, an AI Virtual Agent can create an automated call summary and log the case, again saving your human team time. 

Personalized Support

81% of customers prefer companies that offer personalization.1 An AI Virtual Agent can provide personalized support based on both short and long-term memory, tailoring customer communications around existing preferences and their transaction history. This allows organizations to provide a sense of personalized, one-to-one care whilst benefiting from automation. 

Improved Customer Satisfaction

When implemented correctly, an AI Agent workforce addresses many of your customers' key concerns. When interacting with an AI Agent, customers don’t need to wait on hold and can have their queries answered quickly and efficiently. 

With the additional personalization and multilingual capabilities offered by AI Agents, customers enjoy better service experiences and report higher satisfaction scores as a result. Cognigy’s data suggests organizations can achieve at least +37% increase in Net Promoter Scores (NPS). 

Cost Savings & Scalability

The most important benefit of using AI Agents is driving down costs across your entire customer service process. From reducing average handling times to improving customer satisfaction, AI-driven automation helps you scale your organization without the associated costs of having to hire more human teams.

Use Cases of AI Virtual Agents

To understand what AI Virtual Agents are capable of achieving in your business, you need to explore potential applications. Here are some common examples of AI Agent use cases that help demonstrate the impact of AI on common customer service processes… 

Identification & Verification

One of the most obvious use cases for AI Agents comes in the role of automating ID&V processes (also called Know Your Customer/KYC). This process is usually the first stage of every customer service call for the majority of enterprise organizations, though the actual details involved may be slightly different.

Virtually every call begins with ID&V to extract basic customer information, which is then checked against CRM systems or other backend software. Once authenticated, the customer can begin describing their actual issue and start getting the support they need. 

The faster and more efficient you can make such a low-complexity task, the better for your teams and your customers. An AI Virtual Agent can quickly handle the entire ID&V process and then either hand the call back to a human agent or progress to solving the problem itself. 

Order Tracking

For e-commerce retailers, ‘Where is my order? '/WISMO queries are among the most common customer service requests. AI Virtual Agents are the perfect way to handle these queries. They can ask customers to submit any information needed to trace the order, check backend systems, and then either update the customer about the order’s status or take further action, such as expediting a delayed delivery or processing a refund. 

Customer Service Agent

Thanks to the dynamic nature of Agentic AI, you can now deploy AI Virtual Agents to act as frontline customer service agents who take care of every aspect of a customer’s call. These agents can communicate in 100+ languages and offer fast, personalized responses to customer questions. Once they identify a need or problem, they can resolve it or alert a human agent and route the call to them. 

Call Wrap-up

Every second of your human agent’s time is valuable. The faster a human agent can move on from one case to the next, the more cost-efficient they are. Though you need a way to keep summaries of every case, tasking human agents to create them is an inefficient idea that eats time and money. 

An AI Virtual Agent can quickly automate the necessary wrap-up stages at the end of each call, creating a case summary in whatever format you need that your human agent can simply review, edit, and accept before progressing to their next case. 

Analysis & Reporting Agents

AI Agents aren’t solely tasked with resolving customer problems. They can also be applied to internal analysis and reporting tasks to simplify existing processes or even spot new opportunities. For example, an AI Agent can read all of your case histories and analyze patterns and user sentiment to make recommendations for future improvements. 

AI Virtual Agent Examples

Use cases offer potential applications for autonomous assistants, but we have real-world AI Agent examples that show how large organizations are putting them into action…

E.ON Powers Up Customer Support

E.ON is one of the world’s biggest energy companies; as such, it handles enormous monthly customer call volumes. To cope with demand, E.ON Digital Technology (EDT) team sought an AI Agent to provide a scalable solution for tackling customer service phone queries.

With Cognigy.AI, E.ON orchestrates a team of many different AI Agents, all trained to perform specific tasks. With 30+ AI Agents handling over 200,000 conversations per month, E.ON quickly achieved a 70% automation rate with 24/7 service available to customers and employees alike. 

“Our motto is to use Conversational AI to automate repetitive tasks so our live agents are free to use their time to make a more valuable difference.” - Nikolai Berenbrock, Head of Conversational AI, Integration & Sap Development Services at EDT.

Click here to read the full case study. 

Virgin Pulse Uses AI Agents To Tackle User Queries 

Virgin Pulse needed to improve its support for members who asked questions over text, voice, and phone channels. To that end, it integrated Cognigy.AI into its existing Zendesk LiveChat platform. The AI Virtual Agent can identify intent and fetch answers from Zendesk articles. It can also create a support ticket and pass the call to human agents to handle more complex queries. 

Within a single month, the new AI Virtual Agent workforce increased Virgin Pulse’s containment rate from 3% to 40% and doubled user sessions from 12,000 to 30,000. 

This example demonstrates a straightforward solution to a common customer service problem: how to address common queries without hamstringing your existing resources. Click here to see the full case study and discover why Cognigy awarded the team with our Newcomer Champion Award 2024.

Best Practices for Implementing AI Virtual Agents

AI Virtual Agents can revolutionize your organization and drive customer service performance to record levels – but only if you implement them correctly. Here are some best practices to keep in mind when considering contact center automation

Start Narrow

The capabilities of AI Agents are extensive and can feel overwhelming at first. To give yourself the best chance of success, it’s best to define the goals you have for AI automation and identify narrow use cases that enable you to deploy, learn, and then iterate from. 

ID&V is a common ‘first’ use case. It usually represents a significant time sink for your team and isn’t very complex, making it the ideal area to start testing your AI Agent. Once you have it up and running, you can monitor results and tweak performance accordingly before rolling it out to other parts of the customer service process. 

Control Important Processes

AI Virtual Agents are now advanced enough to provide human-like support, making autonomous decisions that are outside of any predefined parameters. Though this contributes to a seamless, more customer-friendly experience, it can sometimes be the wrong approach. 

For some industries that rely on strict processes, such as insurance, you’ll need to build a more controllable AI Agent who adheres to pre-planned dialogue flows and does not stray from the process. Talk to your AI provider about achieving this, or speak to Cognigy to see how our composite approach can address this exact issue. 

Plan For Human Intervention

Customers willing to interact with automated solutions still prefer human support when things get complex. AI Agents can never fully replace human workers, so you need to consider this when designing potential interactions and use cases. Make sure that the AI Agent can always alert a human agent when cases become too complex or when it recognizes negative sentiment patterns during a call. 

Integrate With Existing Systems

For any AI Agent to be effective, it must be integrated with your backend systems and tech stack. You’ll need to work with your IT team to work out how complex any potential AI adoption will be. Any bespoke or legacy systems can cause issues, so it’s important to bring them to the attention of your AI provider so you can work together to get the best implementation possible. 

Monitor & Improve

An AI Agent platform is an evolving thing that continues to learn and grow over time. Once you have AI Agents interacting with customers, you can monitor results and make changes either based on your own observations or on the AI’s own analysis. With short and long-term memory, AI Agents also improve on their own as they build customer-specific knowledge.

The Future of AI Virtual Agents in Contact Centers

Automation is a necessary step for any enterprise contact center that needs to continue growing in a complex, ever-demanding customer environment. However, research suggests that 60% of contact center AI implementations are still at low maturity, offering very little value to customers.2 Investing in AI without achieving meaningful results means wasting time and money. 

Work with Cognigy, and we’ll help you design and deploy an AI Agent workforce that will immediately impact your most time-consuming, costly processes. Our AI Agents have achieved demonstrable results for some of Europe’s biggest brands, driving efficiency in time and cost for contact centers that handle millions of customers annually. 

Speak to our team today or try a demo to see how AI Virtual Agents can benefit your business.

Frequently Asked Questions

How Do AI Virtual Agents Integrate With Our Contact Center Systems?

AI Virtual Agents are not ‘fixed’ to a specific system or channel – they use APIs to integrate with your systems and tools. Make sure you speak to your own IT team as well as any potential AI provider to discuss what access the AI Agent needs and what level of autonomy you can allow it within certain systems. 

How Do AI Virtual Agents Improve Customer Service?

AI Agents improve customer service by addressing the most common sources of customer frustration: wait times and impersonal responses. An AI Agent provides fast, efficient service that cuts out hold queues and allows customers to resolve their queries quickly and at a time that suits them.

How Do I Know If My Call Center Needs an AI Virtual Agent?

The easiest way to know whether you need an AI Agent is to assess call volumes and wait times. If you’re constantly battling to deal with rising customer demand, automation is the only viable route to addressing it. An AI Agent doesn’t just help you deal with the problem – it also allows you to scale into the future. 

1:https://www.forbes.com/sites/shephyken/2024/04/14/the-personalized-customer-experience-customers-want-you-to-know-them/ 

2 https://www.businesswire.com/news/home/20241021840428/en/60-of-Contact-Center-AI-Deployments-Are-Low-Maturity-According-to-New-UJET-Research