What Is a Generative AI Agent?

Intro

A Generative AI Agent is an advanced AI system powered by Large Language Models (LLMs). The AI leverages the LLM to analyze vast amounts of data, which it then uses to generate human-like responses to user input. 

Generative AI can produce a wide range of different types of content, from long-form articles to imagery and even video. In a contact center, an AI Agent that uses Generative AI can automatically create contextual responses and information to help meet user needs – whether that’s to find answers to common customer questions or to produce call summaries to save your human agent’s time. 

By combining the generative capabilities of Gen AI with the language understanding of Conversational AI, contact centers can deploy an AI Agent into a customer service role that includes handling routine inquiries, assisting human agents, summarizing interactions, and speeding up processes.

An AI Agent workforce can drive cost-efficient contact center automation in a way that meets the complex demands of modern consumers. 

Let’s take a closer look at the role Generative AI Agents play in enhancing customer service processes…

How Does A Generative AI Agent Work?

Generative AI Agents leverage large language models (LLMs) trained through machine learning on extensive datasets. These models analyze vast amounts of textual data, enabling them to recognize language patterns, understand context, and interpret user intentions. Rather than simply identifying words, Generative AI comprehends linguistic structures, semantics, and industry-specific terminology.

When a user or customer types or says something, the AI agent uses its training to predict and generate the most appropriate and contextually relevant response. By interpreting prompts based on statistical likelihoods from training data (similar to autocomplete), the agent delivers coherent, natural-sounding interactions with customers. Over time, generative AI agents can be fine-tuned with additional data, further enhancing their accuracy and personalization capabilities.

The term Generative AI Agent is slightly misleading because most customer-facing AI Agents combine Generative AI with other types of AI technology such as Conversational AI or Agentic AI to expand the agent’s capacity beyond simply generating content. It’s also not to be confused with pre-AI chatbots – see our guide to AI Agents vs chatbots to learn more. 

Benefits of Generative AI Agents

With its ability to create dynamic content tailored to user needs in the blink of an eye, Generative AI brings many different benefits to your contact center…

Instant Responses

Customers don’t need to wait to interact with an AI Agent. They can be deployed instantly and can be available 24/7 on a range of devices, which allows customers to contact support whenever they need to and get answers quickly. With no hold queues and shorter calls, customers will enjoy faster, more efficient service. 

Powerful Insight

An AI Agent that utilizes Generative AI can perform large-scale analysis of your call logs and data to identify patterns, trends, common problems, and other related insights. It can use all of this data to improve its performance when interacting with customers and also to support human agents by suggesting improvements or changes. 

Cost Savings

With its ability to augment your human workforce and improve customer service efficiency, Generative AI drives cost savings across your business. Not only does it improve overall productivity and reduce average handling time, it also frees up human time from manual tasks such as call summaries so you can focus your valuable assets on more complex tasks. 

Industry Knowledge

If you choose an experienced AI provider, any potential AI Agent will be able to leverage your internal service knowledge via Knowledge AI, through a process known as Retrieval Augmented Generation (RAG). This avoids having to train an LLM and instead allows an AI Agent to turn a standardized answer into a natural, contextual, and relevant one for the customer instead of merely regurgitating standardized responses.

Improves Agent Productivity

AI isn’t designed to replace existing human teams. Instead, it can augment humans by automating repetitive tasks and speeding up labor-intensive processes. In a contact center, the main use cases for Generative AI tend to focus on tasks such as call summaries and FAQ answers – all of which help save human agents’ time and free them up to focus on more complex and rewarding tasks. 

Use Cases of Generative AI Agents

By combining Generative AI with Conversational AI, AI Agents can be deployed to serve many different processes across an organization. Here are just a few potential transformational AI Agent use cases for an enterprise contact center…

FAQ Support Agent

Customers calling a contact center to ask basic questions that can be better answered via FAQs are a drain on your time and efficiency. Rather than simply trying to ask these callers to navigate to an FAQ page on your website, you can instead create a Generative AI Agent that takes a customer’s call and provides personalized, accurate responses. This way, your customer gets to feel valued and have their question answered without wasting your human agents' time. 

Self-Service 

AI is not tied to a specific channel; instead, it is a type of interface. Customers can interact with an AI Virtual Agent via voice, text or social media channels wherever they are in the world. Thanks to integration with your backend systems, the AI Agent can take action to help accomplish a customer’s task – whether that be to update personal details or find a missing order. 

Some AI Agents can also be styled as virtual assistants for users, guiding them through personalized recommendations or providing in-store assistance. See our guide to AI Agents vs AI assistants to learn more, or read how a Cognigy client built a stain-solving AI assistant that helped users tackle the most stubborn messes. 

Call Wrap-Up

In almost every customer service case, a call wrap-up must be created at the end of any interaction. Without AI, this means a human agent has to spend a few minutes manually describing the call and adding any additional notes to fit your pre-determined format/template. AI Agents are the ideal choice for automating this task, able to create detailed logs in a matter of seconds that a human can briefly review and approve or make quick edits to.

Agent Assist

Generative AI isn’t only for the benefit of your customers – it also provides ongoing assistance to your human agents to make them more effective. Before a human intervenes on any calls, the AI Agent has already communicated with the customer to extract verification details, gather context, and identify the problem. From there, it can pass a contextual handover to your human team so they’re better equipped to immediately solve the problem. 

During calls, the AI Agent ‘listens’ in and creates transcriptions. It can analyze sentiment and identify any particular patterns or queries – then fetch answers or provide support to your human agent’s screen. 

Once the call is finished, the AI Agent can create a wrap-up, as described above, to save your human team time and make your organization more cost-efficient. 

Analysis & Reporting

Contact center managers rely on data from important metrics to improve service quality and manage costs. Generative AI allows you to supercharge this process, automating many of your most labor-intensive reporting requirements and delivering new insights based on large-scale analysis that a human simply could not perform. Maximize the value of your data to grow your contact center by harnessing an AI Agent.

Best Practices for Implementing Generative AI Agents

Whenever you consider implementing an AI Agent into your organization, there are important considerations to bear in mind. Like any technology, you must plan the process carefully and work with a trusted vendor. Here are some important best practices to keep in mind…

Avoid Common Errors

Public-facing models of Generative AI Agents (such as ChatGPT) are known for errors called hallucinations, where the AI presents false information as factual. In an enterprise contact center that often deals in customer data and sensitive information, you cannot afford to take that risk.

A platform like Cognigy.AI helps eliminate the problem by preventing any customer data from passing to LLMs and using careful prompt engineering behind the scenes to ensure the AI Agent has clear instructions and has gone through extensive simulation testing beforehand.

Start With Narrow Use Cases

The most effective way to get started with AI and automation is to start with a narrow use case that is low-complexity but time-intensive. Don’t try to apply an AI Agent to every process immediately – start small with something highly achievable, such as the ID&V process, monitor the results, tweak performance, and then consider other applications. 

Because AI is capable of self-learning, starting with a narrow scope enables it to evolve on the job and also helps your team become familiar with AI technology before you begin rolling it out to other applications. 

Consult Your Team Early

AI is an amazing tool for business automation – but it’s also a topic that has caused lots of uncertainty for workers. Generative AI, in particular, frequently appears in headline news. When considering AI Agents, you should involve your team early and make them part of the process. Ask them about repetitive tasks that slow them down, common gripes during tasks, and any processes they think could be improved.

Bring this information to your AI provider to show your team you’re addressing their concerns. With insider insight into tricky tasks and common issues, your AI provider can build an AI Agent workforce that directly supports your team in the areas they need it most. 

Provide Human Oversight

Though AI Agents are capable of self-learning and can utilize long and short-term memory, they still require human oversight to function optimally. Human oversight helps keep the AI Agent team on the right track and helps quickly resolve or prevent any potential errors or issues that can occur over time. 

Use Different Types Of AI Agents

Not every type of AI Agent functions in the same way. From Cognigy’s perspective, there are a few core AI Agent types to be aware of: 

• NLU-Driven Conversational AI Agents: This type of AI is process-driven and can follow a tightly defined dialogue flow to allow for precise control of every interaction. 
• Agentic AI Agents: These AI Agents use Large Language Models and dynamic reasoning to plot and pursue goals. 
• Composite AI Agents: This is a combination of the types above, allowing you to blend process-driven behavior with autonomous action. This type of AI Agent learns, adapts, and takes action in a human-like way – making it ideal for customer service applications. 

Within your organization, any regulated processes, such as insurance claims, will be better served with an NLU-driven Conversational AI Agent that can follow the most appropriate flow. 

On the other hand, when dealing with dynamic customer conversations that can take unpredictable twists and turns, a more autonomous AI Agent leveraging Agentic AI will be more capable of improvisation. 

The Future of Generative AI Agents in Contact Centers

Though it is the most ‘popular’ form of AI in terms of media coverage and public awareness, Generative AI is only the first step in an organization’s automation journey. In just a few short years, AI technology has improved dramatically and now offers complex, human-like interactions that can revolutionize customer service processes. 

As AI continues to improve, the speed, flexibility, and utility it offers will ensure customers enjoy better, faster service experiences. Contact centers that want to remain competitive must therefore explore AI Agents as soon as possible or risk falling behind.

Become An AI Leader With Cognigy

Cognigy helps enterprise organizations unlock massive cost savings by deploying industry-leading AI Agents tailored directly to customer service applications. Book a demo today to see what an AI workforce can do for you and your team.

Frequently Asked Questions

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

In most cases, organizations can integrate AI Agents fairly seamlessly into their contact center. The AI Agent is not tied to a single system and can instead be viewed as a separate interactive layer that can access systems such as your CRM to serve a customer’s request. 

If your organization has lots of bespoke tools or legacy systems, integration becomes more complex. In those cases, you’ll need to work carefully with your development team AND your AI provider to ensure the AI Agent can be deployed effectively without causing issues. But as long as it has an API, it generally works.  

How Do Generative AI Agents Improve Customer Service?

Generative AI Agents improve customer service by offering instant, personalized support to customers. They eliminate long wait times, speed up the successful completion of calls, support human agents, and improve overall customer satisfaction. 

How Do I Know if My Call Center Needs a Generative AI Agent?

The easiest way to spot whether automation is going to be beneficial to your contact center is to assess current customer demand versus service quality and costs. Most modern contact centers are overburdened by incoming calls and queries, with no way to address them efficiently other than to increase waiting times or to hire more human teams. 

AI Agents provide a cost-efficient way to meet this increasing demand in a controllable, scalable fashion.