AI in Customer Service: 11 Ways to Use it [+ Examples]

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Alana Chinn
Alana Chinn


The market for artificial intelligence (AI) is expected to grow to almost 2 trillion U.S. dollars by 2030, and AI in customer service has become a focus area for many businesses.

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Thanks to modern technology, chatbots are no longer the only way customer service teams can leverage AI to improve the customer experience.

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Keep reading to learn how you can leverage AI for customer service — and why you should.

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45 Customer Service Scripting Templates

45 templates to help you determine your customer service responses.

  • Live Chat Support Script Templates
  • Phone Support Script Templates
  • Social Media Support Script Templates
  • Email Support Script Templates
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    When implemented properly, using AI in customer service can dramatically influence how your team connects with and serves your customers.

    This video outlines a few of the ways that AI is changing the way we think about customer service.

    Let's take a look at some of the benefits.

    benefits of ai in customer service

    Improved Customer Support Workflows

    AI technology can be used to reduce friction at nearly any point of the customer journey.

    Chatbots allow you to quickly answer routine questions from new customers.

    You can also use conversational AI tools like HubSpot's AI content assistant to and HubSpot's AI Email Writer to develop personalized emails and knowledge base articles for your existing customers.

    AI helps you streamline your internal workflows and, in return, maximize your customer service interactions.

    Reduced Response and Handle Times

    With improved workflows, AI can give you better customer response metrics.

    Using chatbots as an example, you can automatically respond to a customer's live chat message within seconds. This will decrease your support team's first response time significantly.

    The result? Your average handle time will go down because you're taking less time to resolve incoming requests.

    Better Predictions of Customer Behavior

    AI uses real-time data to make predictions.

    That means you can use AI to determine how your customers are likely to behave based on their purchase history, buying habits, and personal preferences.

    Predictive AI can help you identify patterns and proactively make improvements to the customer experience.

    Let's review how to put some of these benefits into practice.

    How to Use AI in Customer Service

    Here are ten ways your business can use AI for customer service.

    how to use ai in customer service

    We'll review each in more detail below.

    1. Chatbots

    We've mentioned chatbots a lot throughout this article because they're usually what comes to mind first when we think of AI and customer service.

    That's because they're one of the first AI tools to be used for serving customers.

    Chatbots are programmed to interpret a customer's problem then provide troubleshooting steps to resolve the issue. This saves time for your reps and your customers because responses are instant, automatic, and available 24/7.

    Pro tip: HubSpot's ChatSpot is a conversational CRM bot that service professionals can connect to HubSpot to maximize productivity.

    You can perform tasks (like sending emails) or pull data insights (like creating custom reports) by entering a chat-based command.

    how to use ai in customer service, ChatSpot, HubSpot

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    2. Augmented Messaging

    While chatbots are great at troubleshooting smaller issues, most aren't ready to tackle complex or sensitive cases.

    This is where augmented messaging comes into play. This AI tool identifies opportunities where human agents should step in and help the customer for added personalization.

    Here's an example of how this interaction could play out.

    how to use ai in customer service, augmented messaging

    Image source

    Pro tip: While bots are great at saving time for your team and your users, they'll never produce the same customer delight as a human agent. Augmented messaging tools give you the best of both worlds.

    3. Sentiment Analysis

    Today, many bots have sentiment analysis tools, like natural language processing, that helps them interpret customer responses.

    This tells the bot how to respond when a customer behaves in a certain way, so your bot won't escalate the customer's emotions when it's trying to help them.

    Pro tip: Tools like Grammarly's tone detection in the image below can analyze your text and tell you how your message may be perceived by your audience before you hit send.

    how to use ai in customer service, grammarly tone detector

    4. Request Routing and Prioritization

    In addition to outgoing messages, you can also use AI to identify keywords and analyze the nature of the request before assigning it to one of your reps.

    AI tools allow you to analyze the customer's problem, the perceived urgency, and their associated emotions. You can also program your AI model to tag in the right agent to handle the case.

    This is another time-saving process that makes it easier for your support team to troubleshoot and resolve issues.

    Pro tip: Reserve your most-experienced agents to handle your complex cases, and allow your newer reps to deal with the simple tickets. Also, consider having reps who are solely dedicated to time sensitive requests.

    5. Self-Service Resources

    While building out a robust knowledge base or FAQ page can be time consuming, self-service resources are critical when it comes to good CX.

    The good news is that AI writing assistants like and ChatGPT can help.

    These types of tools use AI to synthesize existing information and output copy based on a desired topic. You can then use this copy to create knowledge base articles or generate answers to common questions about your product.

    Pro tip: AI content assistant natively integrates with your favorite HubSpot features, helping you generate and share high-quality content for blogs, landing pages, and more without toggling between different tools.

    Get early access to HubSpot's AI content assistant

    6. Voice Analysis

    According to a recent HubSpot survey, the majority of consumers (57%) prefer to contact customer service over the phone.

    Voice AI has made it easier to automate call center interactions. These tools can be trained in predictive call routing and interactive voice response to serve as the first line of defense for customer inquiries.

    For example, when you call your favorite company and an automated voice leads you through a series of prompts, that's voice AI in action.

    Pro tip: Use voice AI technology to resolve routine customer service tasks (like hours of operation requests and account access troubleshooting) so your best agents remain available for more complex issues.

    45 Customer Service Scripting Templates

    45 templates to help you determine your customer service responses.

    • Live Chat Support Script Templates
    • Phone Support Script Templates
    • Social Media Support Script Templates
    • Email Support Script Templates
    Learn more

      Download Free

      All fields are required.

      You're all set!

      Click this link to access this resource at any time.

      7. Omni-Channel Service

      AI can support your omni-channel service strategy by helping you direct customers to the right support channels.

      If all of your chat reps are busy taking cases, the AI can tell the customer that they should use live chat for a quicker response.

      Or if a customer is typing a very long question on your email form, it can suggest that they call in for more personalized support.

      Here's an example.

      Pro tip: When reps are unavailable for callbacks or chat, don't give customers the option to select those channels. That way, customers aren't stuck in a party-of-one conversation wondering why your team hasn't responded.

      8. Data Management

      Not all AI features are customer-facing. In fact, some of the most useful tools are the ones that are integrated with your internal software.

      As an example, AI can be paired with your CRM to recall customer data for your service agents. Your customer success team can use this feature to proactively serve customers based on AI-generated information.

      Pro tip: Use AI to track customer engagement data. If a loyal customer hasn't engaged with you in a while, set up systematic AI to proactively flag it and notify your team to reach out.

      9. Multilingual Support

      Many AI chatbots and conversational tools have the capacity to generate content in different languages. This is especially helpful if your business operates globally.

      AI can detect a customer's language and translate the message before it reaches your support team. Or you can use it to automatically trigger a response that matches language in the original inquiry.

      Pro tip: Review your customer profiles or run a survey to gain insight into your customers' preferred languages. Then, incorporate those into your AI strategy.

      10. Machine Learning and Predictive Analytics

      Machine learning is at the heart of predicting customer behavior through AI.

      It's the process of analyzing large quantities of data and pulling out actionable insights that forecast trends, anticipate customer sentiment, and solve future problems.

      Pro tip: Use predictive analytics to inform your predetermined customer communication responses (e.g., via chatbots or over the phone). Machine learning can help improve the intended output based on FAQs and customer history.

      11. Automated Call Transcription

      AI call transcriptions are revolutionizing customer service by enhancing call quality assurance through efficient call reviews, aiding in the targeted training of new representatives, and helping identify key service trends and recurrent issues.

      These transcriptions offer an objective record for effective dispute resolution and pave the way for personalized customer interactions, ensuring a more tailored and responsive service. By leveraging tools like CallRail's conversation intelligence software, customer service teams can operate with heightened efficiency, ensuring improved customer experiences.

      Chipotle's AI Kitchen Management System

      In 2022, Chipotle began piloting a needs-based approach to kitchen management.

      This approach leverages AI and machine learning to forecast ingredient and cooking quantities based on demand.

      examples of ai in customer service, chipotle

      The new kitchen management system monitors ingredient levels across restaurants, and notifies the staff how much to prep and when to start cooking.

      The goal: It's designed to help reduce friction in the kitchen so the crew can focus on providing an exceptional customer experience.

      Duolingo's GPT-4 Educational Experience

      The popular language learning app, Duolingo, recently released a new learning experience powered by GPT-4.

      examples of ai in customer service, duolingo

      Image source

      Duolingo Max has generative AI-powered features that allow users to learn from their mistakes and practice real-world conversation skills.

      The goal: This new offering provides highly-customized language lessons and personalized experiences for each user.

      Netflix's Machine Learning Strategy

      Netflix's use of machine learning to curate personalized recommendations for its viewers is pretty well known.

      examples of ai in customer service, netflix

      Image source

      More recently, the streaming service has also been using machine learning to refine their offerings based on the characteristics that make content successful.

      The goal: Netflix is leveraging AI to optimize the production of original movies and TV shows within their fast growing portfolio.

      The Future of AI in Customer Service

      The future of AI in customer service may still include chatbots, but this technology has a lot more to offer in 2023. It's a great time to take advantage of the flexibility, efficiency, and speed that AI can provide for your support team.

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