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Customer service has never been more challenging.
As customers become more familiar with the speed and accessibility of digital channels and AI solutions like ChatGPT, their expectations for service teams have skyrocketed.
Enterprise organizations are now expected to offer fast, personalized customer service experiences across multiple channels with no hold queues or call delays.
This unprecedented level of demand, coupled with rising customer volumes, places customer service teams under more pressure than ever before. The cost of getting things wrong can be enormous, with 1 in 3 customers leaving a brand after a single negative experience.1
To meet these expectations and cope with demand, customer service teams can leverage the power of Artificial Intelligence (AI) to introduce personalized, responsive automation that helps customers get faster resolutions, improves internal productivity, and drives down costs for your entire organization.
In this guide, we’ll explore the evolving role of AI in customer service to show you exactly how this technology can work for your organization, your contact center teams, and most importantly, your customers…
What Is AI in Customer Service?
AI takes many forms, with the most common example coming from public-facing Generative AI tools such as ChatGPT. These systems leverage Large Language Models (LLMs) to learn from, using that knowledge to generate responses to user prompts in text, imagery, and even video.
Generative AI is only one type of AI, and though it has its uses in customer service, it is far from the only solution. Customer service's dynamic, varied, and human-facing nature means any AI system needs to do more than simply generate responses to user prompts.
Different AI technologies, such as Conversational AI, must also be leveraged in order to create customer-facing AI Agents that can handle tasks autonomously and give customers the instant, personalized and effective service they demand.
AI Agents are built using a combination of different types of AI. They act as autonomous virtual agents that work alongside your existing human teams to engage customers, solve problems, and speed up effective outcomes. AI Agents can support both internally and externally, either by interacting directly with customers to solve problems or by assisting your human teams in freeing up their time and making them more productive.
An AI Agent consists of a combination of different AI technologies, such as:
- Conversational AI: One of the biggest customer service challenges is in handling customer communications without having to place customers in long hold queues. Conversational AI uses Natural Language Understanding (NLU) to allow AI Agents to communicate fluidly with customers, recognizing context, identifying intent, and responding in real-time. By designing conversational workflows for AI Agents to follow, you can ensure all automation follows your processes and carries out defined tasks as efficiently as possible.
- Generative AI: This form of AI is primarily concerned with generating text, imagery and video content as a response to a user’s prompt.. In a customer service context, this can mean generating instant FAQ responses to customer queries based on your existing knowledge base, or supporting human agents by creating instant call summaries during the wrap-up stage.
- Agentic AI: A new evolution that allows AI Agents to leverage the power of LLMs to create more dynamic, goal-oriented decision-making. Unlike NLU-driven Conversational AI that relies on predefined conversational flows, an AI Agent powered by Agentic AI can make independent decisions in response to a customer’s conversation.
With access to short and long-term memory as well as dynamic reasoning, Agentic AI creates truly autonomous AI Agents that plot out goals and take action to resolve them in the most effective way possible.
Due to the incredible evolution in AI technology, the scope for what an AI Agent can achieve has increased rapidly. Early AI Agents that used NLU-driven Conversational AI focused on linear, process-driven tasks such as identification & verification, which are low complexity but high volume.
Now, with Agentic AI, agents are capable of autonomous decision-making and can handle complex, multi-stage processes such as order tracking, rebooking/re-ordering, and even refunds/cancellations.
For customer service teams, both types of AI Agent have compelling use cases. NLU-driven CAI Agents are better when you want to guide a customer through a strict proces,s such as submitting an insurance claim. Agentic AI is more dynamic and better able to solve complex, multi-stage problems.
Rather than choosing one over the other, enterprise organizations can instead deploy a composite AI Agent workforce that consists of multiple agents, all trained to perform specific roles.
This helps explain AI's role in customer service, but how does it help? Why invest in it for your own enterprise? Let’s take a closer look…
What Are the Benefits of AI in Customer Service?
The advantages associated with AI relate directly to the changing needs of modern customers AND your organization’s operational challenges. AI Agents give you a compelling, cost-effective solution that benefits your service teams in all of these different ways:
Cuts Down On Wait Times/Hold Queues
AI Agents are available 24/7 and allow you to instantly answer customer calls and cases, regardless of the time or where they’re calling from. This means your customers don’t have to wait on hold and can instead start seeking resolutions for their queries/problems.
Speeds Up Calls
AI Agents speed up calls by offering fast, personalized solutions to customer problems and by fetching instant answers to common questions. AI Agents can quickly identify user needs and then take the necessary steps to complete their goals.
In most cases, they can complete basic requests without human intervention. If a human agent IS required, the AI Agent will have already gathered context and verified the customer, so when the call is passed over to them, they can quickly focus on resolving the problem rather than re-gathering all of the information.
Provides Deep Insight
AI Agents can collect and analyze vast amounts of data to create insights you may have never considered before. They provide real-time insight into the metrics that matter most for customer-facing teams and can help you stay on track with KPIs.
AI Agents can also forecast and make recommendations based on your existing data. For example, an AI Agent could analyze all of your historic call logs and transcripts to identify common queries, patterns, or friction points and then suggest improvements to optimize future customer interactions.
Enables Effective Self-Service
Effective self-service gives customers the tools to carry out specific tasks and actions themselves, rather than relying on a customer service representative. AI Agents are an intuitive, dependable self-service option that can actively guide customers through their tasks and alleviate many of the barriers associated with less adaptable self-service options.
Supports Omnichannel Engagement
Customers value being able to contact your business in a variety of ways across their favored channels. AI Agents are not tied to a single channel and can act as a layer that bridges social media apps, web chat windows, and SMS messaging to offer an actual omnichannel support experience to customers. If customers become frustrated or feel limited by text-based channels, the AI Agent can direct them to a live voice call instead and carry on the conversation seamlessly.
Improves Customer Experience
Until AI Agents, automation often meant sacrificing some element of customer experience in exchange for efficiency. Pre-AI chatbots, for example, allowed businesses to automate basic customer questions, but they often returned errors if a customer strayed too far from expected parameters, leading to complaints and user frustration.
AI Agents allow you to automate in a way that actually improves customer experience by delivering the speed and contextual understanding customers need without the same rigidity as earlier digital systems.
The personalization offered by AI Agents is also compelling for user experience. AI Agents can use short- and long-term memory and contextual understanding to personalize communications with your customers and offer humanlike support.
Increases Human Agent Productivity
AI Agents also help augment your existing human workforce, enabling them to work more efficiently. With Agent Copilot, AI supports at each stage of the call:
- Early stages: An AI Agent can automatically guide a customer through the ID&V process and ask them to describe their problem or request. It can then summarize this and intelligently route the call to the most appropriate service agent.
- Mid-call: The AI Agent ‘listens in’ on the call, transcribing information and also fetching relevant answers and guidance from your knowledge hub before displaying it on your human agent’s screen so they can answer customer queries far faster.
- Post-call: Summarizing a call after it’s finished can eat up minutes of a human’s time, adding up to hours of wastage each week. AI Agents can create automated summaries and file them in any required format.
Decreases Costs
Without AI, the only way to meet rising call volumes and provide effective customer service is to invest heavily in recruitment and even potentially new facilities. AI Agents allow you to automate key processes to save time and money across your organization, augmenting your existing team’s effectiveness so that you don’t have to invest as heavily in new hires.
What Are the Use Cases of AI in Customer Service?
Now that we’ve explored what AI is, how it impacts customer service, and the benefits it can provide, let’s look at some example use cases to help show how it supports service teams.
ID&V Agent
Almost every customer service case begins with an identification/verification (sometimes referred to as a ‘know your customer’/KYC) process that involves taking customers through a series of questions used to authenticate them. It is mundane and repetitive, but absolutely essential for all sorts of security and privacy reasons.
An AI Agent can be quickly deployed to tackle the entire ID&V process, guiding users through it with intuitive voice or text conversations. By integrating with your CRM systems, an AI Agent can not only authenticate users, but it can also update information and create a ‘warm handover’ for your customer service agent so that they don’t have to ask any repeat questions or re-verify the user.
The ID&V process is the ideal use case for AI Agents. Not only can automation make the entire process more streamlined and efficient, but it also alleviates the burden of this task on your human agents, who likely view it as a dull but necessary part of their job.
24/7 Customer Support Agent
AI Agents can act as 24/7 customer service agents that talk to customers, understand their problems, and then take action to resolve them. These agents are available whenever a customer needs them and can be contacted through a range of channels, and can even translate and communicate across 100+ languages.
AI allows you to offer two distinct ‘types’ of customer service approach – with a flexible and dynamic Agentic AI Agent that offers intuitive customer experiences and can pursue tasks independently to carry out customer goals, or a more process-driven service agent that can direct customers through specific stages and stick to essential legal or regulatory requirements (for example, a support agent handling insurance claims that only uses exact terminology from your knowledge base).
Employee Support
AI can also help your existing customer service team augment capacity and improve productivity. An AI Agent can field the initial stages of a call, gather all the required information, and then create a contextual handover for a human agent. AI Agents can take notes, translate and assist agents during calls by generating responses to queries. They can also identify sentiment and can recommend actions to de-escalate conflict and improve overall customer satisfaction.
In a different context, AI Agents can also be deployed for employee usage rather than supporting them in customer conversations. For example, a company might develop an AI Agent that onboards new customer service agents and trains them in company-specific knowledge or skills.
AI in Customer Service Examples
Use cases provide a broad idea of how AI can be used in customer service. Let’s take this even further by exploring some real-world examples of AI in the customer service industry…
AEGEA’s WhatsApp Agent Makes Customer Service Seamless
AEGEA is a private sanitation company in Brazil dedicated to improving the health and quality of life of over 31 million Brazilians. Faced with huge customer service demand from its large customer base, the company sought to reduce the pressure on service teams and improve customer satisfaction by introducing a digital solution.
AEGEA partnered with GBPA and used AI Agents from Cognigy to create WhatsApp AI Agents that could proactively engage with customers and provide intuitive self-service options. By interaction with the AI Agent, customers could get their questions answered, be routed to the correct teams, and perform self-service tasks without needing to wait for a human response.
This WhatsApp AI Agent has successfully improved operational efficiency and customer satisfaction. During peak months, the AI Agent handled over 1.1 million conversations and achieved an 87% retention rate for WhatsApp queries – which meant far fewer customers were picking up the phone to call service teams, freeing up time and allowing the organization to scale more efficiently.
Click this link to learn more.
E.ON Finds Its Spark With AI Solutions
E.ON is one of the largest energy networks in Europe and provides services to over 50 million customers. Pursuing digital innovation, the E.ON Digital Technology (EDT) team wanted to find a scalable way to introduce AI Agents that could handle phone and chat interactions effortlessly.
Working with Cognigy, E.ON developed a suite of AI Agents across phone, chat and voice. These agents could all be orchestrated and managed within the Cognigy.AI platform, allowing the team to tailor interactions and ensure best-in-class customer service.
E.ON now has over 30 conversational AI solutions with a 70% automation rate, serving customers and employees across the globe. These solutions also collect lots of data that is used to drive performance improvements across all channels, ultimately resulting in better customer experiences and award-winning examples of AI Agent implementation.
Lippert Tackles Complex Customer Requirements
Lippert is a manufacturer for the caravanning, marine, and rail sector. Not only do they manage a complex product inventory, but customer requirements are often highly specific and require specialized knowledge. This meant that service teams were regularly overwhelmed by long conversations that required detailed information-gathering stages.
By introducing AI Agents, Lippert was able to deploy a self-service solution that helped customers get answers to their product-related queries, including part pricing, availability, and order status. This AI Agent has driven an 80% cost reduction from handled queries and achieved a containment rate of 37%.
Get a closer look at this example in the full case study.
Best Practices When Implementing AI in Customer Service
To help you implement AI within a customer service team, we’ve created some best practice tips to help guide you through implementation and ensure your AI-powered contact centers are as efficient as possible.
Consider Integrations
An AI system must be able to integrate with your technology stack to offer optimal capabilities. Talk to your IT team to make sure they understand the role of AI and which APIs or other integrations need to be planned. Cognigy’s own platform is highly versatile and can integrate with almost all leading tools and technologies, allowing our AI Agents to interact with and take action using the systems your business is built on.
Tailor The Technology
Not all AI uses the same background technology. One company’s AI products may be built on an entirely different LLM that isn’t suitable for your business needs. Talk to your potential AI provider to discuss the background systems that power their AI Agents and discuss how they may or may not suit your needs.
Cognigy’s AI Agent platform is fully customizable and allows you to choose from a range of different LLMs or even a combination of them. We can also train AI Agents using your own resources and materials to ensure they understand the context and content of your business.
Start Narrow & Scale
When first deploying an AI Agent, start with a narrow use case that is low complexity but demands significant amounts of time, such as ID&V. This allows you to create a more focused AI Agent that is trained for this specific process. Once deployed, you can monitor and optimize it to improve results and then scale your learnings out across a wider AI Agent workforce with new agents attached to other processes.
The Future of AI in Customer Service
Despite the meteoric impact of AI across all digital sectors, we are still only at the beginning and companies are still getting on board. Venture capital investment in voice AI startups shot from $315 million in 2022 to $2.1 billion in 2024.2
Agentic AI is a relatively new development, but one that totally transforms customer service experiences by creating humanlike conversational journeys. With AI Agents, businesses can finally fulfill customer expectations for fast, efficient service 24/7, all whilst keeping costs down as we scale into an even more demanding future.
Don’t fall behind your competitors. Get started with AI in customer service with Cognigy and experience an efficient, intuitive AI Agent workforce that can revolutionize your customer service processes and send customer satisfaction scores soaring.
Is your organization ready to give AI a try? Book a demo today.
Frequently Asked Questions
Is AI Replacing Customer Service?
No, AI is not ‘replacing’ customer service – it is simply a way to augment existing processes and deliver better customer experiences. Human service agents will still play a valuable role in solving more complex problems, but AI Agents will support them, which can help customers get answers to questions and carry out simple tasks.
How To Use AI In A Helpdesk
Enterprise organizations that have traditionally relied on human agents or pre-AI chatbots to answer helpdesk queries can now deploy AI Agents to handle these interactions. These agents can communicate fluently in multiple languages and quickly assist customers in finding the support they need.
How Can You Keep Customer Data Secure Using AI?
Privacy concerns are a high priority for all technology providers, and AI is no exception. Each provider has a different approach and must be careful about which models their AI is trained on, the level of access the AI has, and even the level of freedom an AI Agent may enjoy in communicating with customers. You must work with an experienced AI provider to address these issues and ensure your AI Agent workforce enhances security rather than risks it.
