How To Use AI In Customer Service? 7 Biggest Examples

    In a world where customer engagement is crucial for businesses, customer service has never been more important—or more difficult. Interaction volumes are at an all-time high as companies turn digital, pushing support teams to adapt to a rising demand for fast solutions.

    While AI has been a part of customer support for a while now, the rapid rise of generative AI has seen the advent of faster, more intelligent solutions for customer service agents.

    And, as more businesses experiment and begin to understand how AI works—and how it can drive improvement—there’s no sign of this trend slowing down.

    But how are customer service teams using AI? Are these new tools really any different than the automaton solutions we already had? Let’s dive in and find out.

    What’s the role of AI in customer service? 7 examples of artificial intelligence in customer service

    Content generation and knowledge base updates

    It’s no surprise that one of the key uses of AI for customer support agents is supplementing their workload. Instead of reading, analyzing, and writing information for knowledge bases or spending hours drafting PR statements or internal memos, why not have AI do it for you?

    AI in customer support can analyze conversations and generate humanlike responses. It can even draw from your CRM platform and knowledge base to ensure accuracy and adhere to your own internal guidelines.

    Your team can lean on these AI-generated messages to draft emails to customers, write and update knowledge base articles, and even create new training materials. Plus, they can all be set up to be reviewed by a human before publication to reduce the chance of errors and misinformation.

    Real-time coaching and agent feedback

    AI for customer service agents can monitor live interactions with customers while providing real-time feedback to your agents. Just as it can be used to create and inform your agents, it can also analyze and learn from specific interactions.

    These AI tools can aid agents by drawing on information from your knowledge base, internal documentation, and CRM to offer insights into conversations as they happen, giving agents instant tips and suggestions on what to do or say during customer interactions.

    Automated quality assurance evaluations

    AI in customer support can listen to, analyze, and audit 100% of customer conversations within your contact center. These AI-powered “virtual evaluators” help your existing evaluators dramatically speed up their workflow.

    They offer deeper, more accurate information at a scale that simply isn’t feasible for a human to accomplish. Plus, the outcome of these analyses is free from human bias, letting your evaluators work on the hard facts to deliver a better customer experience.

    AI customer service chatbots and self-service tools

    We know that AI for customer service agents can improve workflows before, during, and after interactions—and it can do the same for your customers too.

    AI-powered self-service tools and chatbots can handle basic inquiries that don’t need human intervention, such as:

    • Tracking orders
    • Renewing or canceling subscriptions
    • Checking account status
    • and more

    Customers can access your call center’s self-service options any time of day and get an immediate response without needing to wait for an agent to be free. Plus, you can easily add multilingual support to broaden your global reach.

    Additionally, self-service tools and chatbots can be trained on your internal data and knowledge base, ensuring that answers are correct and they have all the information they need.

    Intelligent call routing

    It’s almost standard for a contact center to have some sort of call routing technology, such as an interactive voice response (IVR) system. But these can be slow and inefficient, and are unlikely to comprehend nuances in human speech.

    By implementing AI in customer support, call centers can beef up their IVR to interpret and understand human speech with natural language processing (NLP) and natural language understanding (NLU). It can determine positive or negative sentiment, and even nuances in accents and dialects, and help route callers accordingly.

    Once the AI has understood the customer’s needs, it can then redirect them to the appropriate agent, department, or team. On top of that, it can even collect information from the customer before transferring them, passing it to the agent so they’re already informed and ready to assist.

    Automatic sentiment analysis

    In addition to understanding the nuance of language with NLP/NLU, AI can also interpret the customer’s mood and tone within their speech patterns. AI can automatically monitor and analyze interactions and highlight negative (and positive) sentiment for both customers and agents.

    This data can then be used to gauge customer feelings, collect data to see common trends, and understand what’s driving them to reach out in the first place.

    Call centers can also use this data to help train their agents, leveraging sentiment data within coaching sessions to handle complex situations or work to correct behavior.

    Identifying upselling and cross-selling opportunities

    Finally, using AI in customer service can open doors to increase revenue during interactions. Because it's integrated with your CRM and other historical customer data, AI can observe and analyze interactions and offer personalized offers.

    For example, let’s say a customer calls a retail outlet for help with an issue with a recent purchase. As the agent answers the customer's questions, AI can draw from the customer’s purchasing data and recommend a personalized discount for their next purchase.

    How can AI improve customer support? 4 benefits of AI in customer service

    Increased efficiency and scalability leads to cost savings

    AI in customer support can make a significant impact on call center efficiency. These systems can handle much larger interaction volumes without needing to hire or staff additional agents. This means faster, easier scaling without eating into the budget.

    The addition of chatbots, self-service options, and virtual agents make it possible to streamline workflows and automate tedious manual tasks, freeing up agent time. This means your agents can pour their time and effort into more complex interactions. Plus, a reduction in time required for after-call work means they can jump back into the queue to assist more customers.

    Agents can rely on AI in customer service to boost efficiency within their workflows. On top of the benefits of automation, AI tools can offer agents information and recommendations based on previous customer interactions or provide relevant information for the issue at hand.

    Additionally, self-service options can collect information and pass it on to agents before they’re connected to the guest, speeding up the process and keeping agents informed without forcing customers to repeat themselves.

    Expanded support and personalization means happier customers

    It’s not just your contact center agents that benefit from the adoption of AI in call center.

    With the addition of personalization options, customers receive a more bespoke interaction with your business. AI leverages historical data, preferences, behaviors, and more to analyze and tailor customers’ experiences to what they want and value.

    More than just offering personalized discounts and offers, AI can go a step further and inform customers about new services and products. It also ensures those recommendations are tailored to their purchase history and interests, building a unique profile for each customer.

    With the addition of AI, you can even expand your call center to new customers, languages, and locales. It can extend support beyond your normal operating hours to 24/7 and increase availability without needing to hire additional staff. It can even use NLU to determine what language your customers speak and translate accordingly.

    This all leads to a reduced average handle time (AHT) and improved first call rate (FCR) for your contact center. Helping your customer as fast as possible has always been the goal, and integrating AI can dramatically speed up the process without sacrificing accuracy.

    Your customers will notice and appreciate this, too. 52% rank FCR as the most important factor impacting their customer experience.

    AI-powered analytics unlock superior insights

    Effectively using the data you already have—or can collect—makes all the difference when working with your customers. Without it, you won’t know what they want or need, or what drove them to reach out in the first place.

    AI can integrate with your existing customer relationship management (CRM) software, alongside gathering and analyzing historical data and preferences from previous interactions, to build a unique profile for each of your customers. Then, you can use that information to estimate the time it’ll take for your agents to resolve the issue, the chances of an escalation, and more.

    All of these capabilities can significantly impact your customer experience. Not only will your team have better insights into how your call center is performing, but it will also help your agents tailor interactions for each customer.

    AI tools improve agent engagement and morale

    Ultimately, AI just helps make the agent’s job easier and less stressful.

    With the removal of tedious, repetitive tasks, your agents have time to focus on more meaningful work. This means they can tackle tasks that require creativity, problem-solving, emotional intelligence, and critical thinking.

    And when your agents are spending less time on boring, repetitive tasks, they’re going to feel more engaged with their jobs and the customers they interact with.

    Higher engagement also leads to higher morale, meaning your teams will be in better moods, which trickles down to your customers through wholesome, constructive, and positive interactions.

    5 challenges and disadvantages of AI in customer service

    Financial considerations

    While adopting AI for customer service agents can lead to better cost-effectiveness in the long run, it does have upfront costs that you’ll need to consider.

    In addition to the cost of the software and labor to integrate it into your systems, you’ll also need to hire and/or train staff on how to use these new AI tools. You may even need to hire software developers to integrate and maintain them.

    Depending on the type of AI tool that you use, there may be additional requirements, too. The scale at which you need to use these tools, how complex it is to deploy, any additional hardware or features that need to be added before implementation, and even specific business requirements all need to be factored into your decision to use AI in customer support.

    Training requirements (both human and AI)

    Speaking of training staff, you’ll need to ensure your agents are informed and know how to use these new tools. Not only will they need to know how to use it, you’ll also need some employees who know how to maintain your AI platforms and ensure they work as intended. And with the rapid development pace of the AI field, these agents will need to stay up to date on many new features and tools to keep it operational, making upskilling employees a requirement.

    Some agents or teams may need to have customized training as well, to ensure your chosen AI tools work for their specific use cases.

    You’ll also need to make sure your AI is being trained on the correct data for each implementation. While AI platforms are highly configurable, the more configurations you have, the more training your agents (and your AI) will need.

    Time to implementation

    Rome wasn’t built in a day, and integrating a new tool into your call center—whether it’s AI-based or not—requires time for planning, testing, integration, and refinement before full adoption.

    You’ll likely need to start with several small tests or pilot projects to collect data and train agents.

    Starting small gives your teams a better chance to see how your AI tool works within your current processes and systems, so they can spend more time tweaking and modifying it as needed until it’s ready for a full rollout.

    Concerns around privacy & data security

    The data that your call center collects is incredibly important to your business and your customers since their personal information is included, too. The addition of AI in customer service can boost efficiency, but it doesn’t erase a company’s obligation to protect and use that data appropriately (and within regulations).

    When adopting new AI tools, it’s crucial to understand how they handle sensitive data, especially within industries like finance and healthcare. Ensuring they’re compliant with industry and government regulations is vital to data security and privacy.

    With AI still being relatively new and constantly evolving, there are obvious concerns about how it can protect and secure data.

    Resistance from employees

    The most glaring drawback that comes from the adoption of AI for customer support agents is their natural fear about being replaced. A sizable 48% of service professionals are worried they’ll lose their jobs if they don’t learn how to use generative AI tools.

    While it’s fun to joke about our robot overlords, the reality is that agents won’t be replaced by AI anytime soon. Instead of being replaced, agents will need to learn how to use these new tools to improve their performance as their roles evolve.

    What is the future of AI in customer service?

    As AI technology evolves, its applications within customer service teams are set to become more advanced and integral to operations. This presents a unique opportunity to blend AI's strengths with human touch. But how will the future play out?

      • Advanced AI applications within customer service: AI's sophisticated algorithms can now understand and interpret customer queries with empathy and accuracy that haven’t been attainable previously. This means AI can manage more complex tasks, seamlessly transitioning from responding to basic inquiries to handling intricate customer needs, all while ensuring a personalized and engaging experience.
      • Synergy between AI and human agents: Imagine a symbiotic workspace where AI and human agents work together to elevate the customer experience. AI takes on tedious and repetitive tasks, allowing your agents to focus on complex, high-value interactions. This optimizes operational efficiency and significantly enriches the quality of customer service.
    • Upskilling career development with AI: With AI handling mundane tasks, your agents can concentrate on honing skills that require human intellect and emotional intelligence, leading to career advancement. Continuous learning opportunities fostered by AI can help elevate standards, ensuring your team always stays ahead and achieves high customer satisfaction.


    AI isn’t going away anytime soon, and the race for companies to take advantage of AI to gain the upper hand is hotter than ever. The advantages of adopting AI are massive, and the impact it can have on workflows is substantial.

    As businesses show the success that’s stemmed from AI implementation, more and more organizations will continue to follow suit. This means that those who get left behind may never catch up if they’re too slow to take action.

    All of these new AI possibilities can be overwhelming and complex, but they don’t have to be.

    With Scorebuddy, you’ll find targeted AI-plus-QA solutions that can not only save time, but money. Offering virtual evaluators, 100% conversation coverage, and detailed analytics all on one platform, Scorebuddy can take your contact center to a new level.

    Sign up for a free trial today.


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      How can AI be used for customer support?

      AI enhances customer support by automating responses through chatbots, providing real-time coaching to agents, analyzing sentiment, and intelligently routing calls. It streamlines knowledge base updates, monitors quality assurance, and identifies sales opportunities, improving efficiency and personalizing customer interactions.

      AI tools help resolve common queries swiftly, freeing up human agents for more complex issues, boosting both customer satisfaction and operational efficiency.

      What is conversational AI for customer support?

      Modern AI technologies like Large Language Models (LLMs), NLP, and machine learning have transformed contact centers by powering more intelligent chatbots and virtual agents.
      These tools go beyond basic menu navigation and predefined responses, understanding and mimicking human conversation nuances. They facilitate more natural, human-like interactions, analyze data, predict customer preferences, and enhance various tools such as IVR systems, virtual assistants, and analytics tools, significantly improving customer service.

      Does AI replace customer service reps?

      AI does not fully replace customer service reps; instead, it complements their work by handling routine inquiries and tasks. This allows human agents to focus on more complex and sensitive customer issues, enhancing efficiency and customer satisfaction.

      AI supports customer service by providing tools for analysis, automation, and real-time assistance, improving the overall quality and responsiveness of customer support rather than replacing human roles entirely.