Say a customer hits a roadblock with their current subscription and could really use a premium product featured at a higher tier. A frontline support agent might not recognize this opportunity or relay it to your sales team. However, an AI system would quickly identify the customer’s needs and alert your sales team of a potential upsell opportunity. Cognitive technologies are redefining how businesses interact with customers and service teams are no longer a peripheral aspect but a vital touchpoint influencing customer perception and loyalty.

Depending on the type of AI that they are able to offer, customer service teams may reach new heights of productivity as they are able to use technologies to automate busywork. You’ll be able to do more work with fewer agents as the AI takes over the tasks that would normally be performed by your team. Many customers now expect a certain level of artificial intelligence when interacting with customer service teams – it’s all about how you deploy it. Machine learning elevates support functions across channels, including social media customer service, effortlessly with intelligent automation.

How leaders fulfill AI’s customer engagement promise

See how this technology improves efficiency in the contact center and increases customer loyalty. Think of it like a virtual buddy who’s not only knowledgeable, but also understands your exact needs and preferences. All you have to do is tell it what you need help with, and it will take care of the rest. No need to find your tracking number, provide your email, or explain the details of your purchase, it already has all that information and knows exactly what to do.

The main reason CS people don’t use AI/automation tools is that consumers prefer to interact with a human over AI, so it can make the process of getting support feel impersonal. The vast majority of consumers, both in the U.S. (82%) and abroad (74%), still prefer to speak to a human. Your customers will remember that connection when it’s time to purchase again, and so will the friends and family they recommended your product to. AI summarize can summarize a complex conversation in seconds, generating an easy-to-understand bullet point summary that allows a new agent or team to get up to speed effortlessly. Although we use the term artificial intelligence when we talk about these tools, it’s important to understand that that’s more of a verbal shorthand than an accurate description of what’s happening under the hood.

‘Hi, Can I Help You?’ — How Chatbots Are Changing Customer Service

You need to align your AI strategy with your customer needs, preferences, and expectations. You need to understand who your customers are, what they want, and how they communicate. You need to provide your customers with options, transparency, and control over how they interact with your AI agents.

AI tools like Sprout analyze tons of social listening data in minutes so you can make data-driven decisions based on the conversations happening around your brand and industry. For example, customer care teams can use social listening to get ahead of product defects or service issues if they see similar complaints across social. Luckily, innovations in artificial intelligence (AI) like generative what is AI customer service pre-trained models (GPT) and text analytics are transforming how customer care teams operate. The AirHelp chatbot acts as the first point of contact for customers, improving the average response time by up to 65%. It also monitors all of the company’s social channels (in 16 different languages) and alerts customer service if it detects crisis-prone terms used on social profiles.

Top 5 Use Cases for ChatGPT/AI in Customer Service

Chatbots can answer common questions with canned responses, or they can crawl existing sources like manuals, webpages, or even previous interactions. Using AI in customer service allows customer service teams to gather consumer insights. With Zendesk, for example, intelligence in the context panel comes equipped with AI-powered insights that gives agents access to customer intent, language, and sentiment so they know how to approach an interaction. All the relevant data gets stored in a unified workspace, so agents don’t have to toggle between apps to get the info they need. Adding artificial intelligence to your customer service interactions offers several benefits. Firstly, it can reduce friction at all points in the customer journey, as chatbots can quickly reply to most routine questions from users.

For example, a travel company can employ a conversational AI platform to create a virtual travel assistant and help customers book flights, hotels, and activities. Be sure to keep this in mind at the beginning of your search for the right automated service program for your organization. A high-level algorithmic hiccup has been observed in AI tools where the output does not follow the input. No matter how well we train machines to identify our use of emotive language, they will have no visceral understanding of what your customer is going through. There are now AI programs that create consistently branded avenues for your customers to access service across all of your channels. If you’re hoping for an all-knowing, all-solving, (dare we say, sentient?) customer communication robot, you’ve still got a long time to wait.

Put AI, automation, and data to work

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. Keep reading to learn how you can leverage AI for customer service — and why you should. Imagine never having to resort to tired stock photos thousands have already used again. Revel in the ability to create jingles, musical introductions or soundtracks inexpensively. Modern businesses don’t have to dream about that because generative AI models that do both already exist.

• Providing an AI-powered 24/7 customer service chat can help handle most queries and transfer customers to live agents when needed.
• This eliminates wait times as customers get intelligently routed to the agent best suited for the task.
• AI has many customer service applications, but that doesn’t mean it will replace human service.
• This process can be time-consuming and is typically used in quality management, business development and sales.
• The most visible way customer service teams use AI is by automating initial communications in order to help customers solve simple issues independently.

By automating mundane tasks, AI could provide a better experience for customers with more self-service options and help fix some of the industry’s biggest problems, especially employee burnout and inefficiency. Working in customer service is notoriously stressful—it was named one of the world’s top 10 most stressful jobs—and companies see turnover rates of up to 45% of agents every year. That has led to a massive talent shortage and is costly for companies to continually recruit and train new employees—all of which affects the customer and employee experience. Providing an AI-powered 24/7 customer service chat can help handle most queries and transfer customers to live agents when needed. Research shows that 80% of customer service companies will use generative AI as of 2025 to improve their productivity and customer experience. Besides, 30% of customer service representatives are expected to use AI to automate their work by 2026.

examples of AI in customer service

For instance, AI can assist customers based on their past behaviors or inquiries. Traditionally, customers are required to leave a voicemail or send an email and wait for a response, which could take several hours, if not days. With AI-powered answer bots, you can assist your customers, no matter the time of day. Annette Chacko is a Content Specialist at Sprout where she merges her expertise in technology with social to create content that helps businesses grow.

Introduced as “Macy’s on Call,” this smartphone-based assistant can provide personalized answers to customer queries. It can tell you where products or brands are located or what services and facilities are available in each store. AI can improve customers’ experiences when implemented effectively by reducing wait times, tailoring experiences, and giving them more resources for solving problems without having to contact an agent.

Sentiment Analysis

Not every piece of technology is right for every organization, but AI will be central to the future of customer service. In customer service, AI is used to improve the customer experience and create more delightful interactions with consumers. Technologies like chatbots and sentiment analysis can help your support team streamline their workflow, address customer requests more quickly, and proactively anticipate customer needs. Nowadays, customers want support immediately, so all customer service teams want a low average handling time.

With AI, your customers can access real-time assistance, regardless of whether your human support agents are available. Miami-based health and fitness company, Sensory Fitness, provides a holistic gym experience that includes intense workouts and restorative stretching and recovery programs. To meet the needs of a fast-growing clientele, they collaborated with AI company, FrontDesk AI, to develop a personalized AI virtual assistant, Sasha, to enhance their customer service capabilities. For example, use this data to enrich your resource center with information covering what’s most important to your audience or update frequently asked questions (FAQs) from customers. This improves transparency for potential customers in the decision-making phase who are browsing products. For example, they can direct customers to live agents in the relevant department or ask for more information to provide a solution—giving you the perfect balance between machine efficiency and human expertise.

Toward engaging, AI-powered customer service

AI customer service is the use of AI technologies like machine learning, natural language processing (NLP) and sentiment analysis to provide enhanced, intuitive support to current and future customers. While customers expect them to respond immediately and know all the answers, siloed teams, opaque workflows and fragmented customer data across channels add to the challenges support teams face on an ongoing basis. They need the right tools to make swift, efficient decisions and provide the kind of personalized customer care needed in today’s competitive environment.