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AI in Customer Service: Enhancing Efficiency, Personalization, and Cost Reduction

Discover how AI in customer service is revolutionizing support by increasing efficiency, offering 24/7 service, and delivering personalized experiences—all while reducing operational costs.
Oct 23, 2024  · 11 min read

The customer is always right. That’s the mantra that drives the whole field of customer service. It’s certainly rewarding to be in a job where your job is mainly to make customers happy. But it can also become a heavy burden when the priorities and expectations of your customers change dramatically without notice, out of the blue. AI in customer service can help with this. 

We’ve seen a changing landscape since the COVID-19 outbreak. In the US alone, 56% of employers reported a change in customer expectations since the pandemic, according to estimates by Gallup. In particular, they cited two ways that consumer behavior has shifted: customers are more demanding and expect higher levels of service, and customers now have greater expectations for virtual/remote service.

In what ways have customer expectations most changes since the start of the pandemic?

Source: Gallup

Against this context, customer service professionals are working round-the-clock to meet the demanding expectations of a customer who wants better and faster service.

But there is also good news: Generative AI. With the rise of tools like ChatGPT, Google Gemini, and the hundreds of generative AI models that are reaching the market, companies and governments are finding innovative ways to enhance their customer service strategies while reducing their operational costs.

In this article, we will analyze how AI is impacting customer service. We will cover the benefits of using AI in customer service, compelling use cases illustrating how AI can make a big difference when meeting customer expectations, as well as potential future trends.

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What is AI in Customer Service?

There are many applications of AI in customer service, but they all follow the same underlying goal: providing immediate, 24/7 quality support whenever the customer needs it. 

AI provides an effective and efficient way for businesses to expand their capacity to serve more customers at a significantly reduced cost. By replicating and augmenting human capabilities, AI-powered chatbots can collect and cross-reference information to develop responses and solutions to specific customer problems. 

Even if smart support cannot answer a complex customer's questions, the system can keep track of the problem's history and send the necessary response to a company agent, an action called chatbot-to-human handoff. When the employee reaches this customer, they will already have an understanding of the customer's entire journey and will be able to provide even more personalized and direct service.

To deliver their magic, chatbots rely on a range of key AI technologies and techniques, including machine learning, natural language processing (NLP), and generative AI, the case of the most advanced chatbots.

Benefits of AI in Customer Service

The uses of AI in customer service are nearly endless, and there are several advantages that are emerging. Below, you can find a list of the main benefits of AI in customer service.

Improved efficiency and speed

When it comes to customer service, scale matters. If you are a small company with a limited number of customers, you may be able to meet their demands by yourself. But, as soon as your client pool increases, customer service can rapidly become unmanageable.

Here is where AI comes in useful. It can automatically address many customers' problems in a matter of seconds, and these capabilities can translate into a great relief for companies in terms of efficiency and speed.

Personalization at scale

Every customer is different. Fortunately, modern AI-powered chatbots can learn from current and previous interactions with customers to provide personalized responses. 

For example, when a customer opens a conversation, an AI agent can rapidly query information from the company’s database to get all the relevant information for the case, such as the customer’s name, location, preferred language, and record of previous interactions. With that data, chatbots can provide instant personalized service no matter the customer and the nature of their needs.

24/7 customer support

In contrast with humans, AI doesn’t eat, drink, or sleep. That means that AI-powered chatbots can offer around-the-clock customer support. When your customers have queries outside of working hours, your AI assistant is on hand to deal with routine queries and gather information on more complex ones. This helps take the load of your customer service agents and gives them a headstart when they’re interacting with customers. 

Cost reduction and scalability

Customer service teams are constantly looking for ways to enhance efficiency and refine operations. AI can play a pivotal role in supporting these goals by automating routine tasks, allowing human agents to focus on more complex and meaningful interactions. This approach not only reduces operational costs but also ensures that the quality of service remains high, improving both the team and the customer experience.

Examples of AI in Customer Service

We’ve seen how AI can benefit teams, organizations, and individuals. Let’s look at how you can deploy AI in customer service in your business. 

Chatbots and virtual assistants

Chatbots are probably the most popular and visible customer service applications. A chatbot is a computer program that simulates conversation with human end users. It often uses NLP to parse inputs and generative AI to automate responses.

Companies across sectors, from banking and insurance to marketing and healthcare are deploying chatbots like Zendesk or Intercom in their customer service to automate and streamline customer queries. 

AI-powered customer support platforms

Customers represent one of the most valuable sources of data for companies. However, businesses traditionally have only been able to retrieve and leverage a limited subset of that data, mostly structured data directly provided by them via the web or surveys. 

Fortunately, recent advances in AI, the Internet of Things (IoT), and data retrieval techniques allow companies to tap into customer data's full potential. Whether phone conversations, social media posts, or data collected by smart devices, all this data is then merged and processed in AI-powered customer support platforms, such as LivePerson and Drift, to discover valuable insights and improve customer satisfaction.

Automated ticketing systems

A ticketing system is designed to process, prioritize, and manage customer issues from end to end. When a customer query is submitted, the ticketing system creates a support ticket that can be tracked until the issue is resolved by an agent.

Unlike the traditional ticketing system, modern, AI-powered ticketing systems organize and route support tickets, process customer inquiries, and escalate tickets based on factors like issue type and urgency. 

These novel capabilities also give agents valuable information to ensure personalized support and coordinate their efforts effectively. As a result, companies can reduce resolution and wait times and deliver better customer service.

How to Use AI in Customer Service

There are clear benefits of adopting AI in your customer service processes. However, it’s important to note that every case is different, and what works for one company may not work for another. Also, keep in mind that adopting AI requires a considerable investment in terms of resources, talent, and time. 

Below, you can find a series of steps you should take to ensure a successful AI integration.

Identify key areas for automation

Cutting-edge AI tools can potentially serve a wide range of applications, yet the truth is that most AI applications work best for specific use cases. In this vein, a great starting point is to identify particular inefficiencies and repetitive tasks in your customer service workflows, where the implementation of AI could make a difference.  

Choosing the right AI tools

Once you have spotted areas of improvement, it’s time to invest time and money to try different AI tools. The goal of this experimentation phase is to familiarize your teams with different AI tools, noting their features, strengths, and weaknesses. 

The AI landscape is rapidly evolving, and it’s important to find the right fit for your company. 

Training your teams 

Whatever the AI solution you want to implement in your customer service, you will need your employees to make that happen. That’s why, before starting the process, it’s essential to conduct an honest evaluation of your team's capabilities, needs, and existing processes. 

Understanding your team’s current skill set allows you to customize training programs effectively. By focusing on areas that require improvement, you ensure that your AI training is relevant, targeted, and impactful. 

Collaboration with your data analytics academy partner, such as DataCamp For Business, can facilitate this process. Our expert teams can help you tailor existing learning tracks or create new ones to meet your organization's specific needs and ensure that all employees stay on track with their learning goals. 

Whether it’s for individuals learning the basics of AI or teams looking to implement AI solutions, making sure you have the right data an AI skills training is crucial. Contact us today to request a demo.

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Integrating AI with existing customer service processes

AI offers many opportunities to improve your customer service processes, but you need to think strategically. Implementing these tools into your daily practices will take resources and time. At this stage, you need to strike a balance between your priorities, finances, and human resources. 

Also, it’s important that you have developed a strategy to measure success. In other words, you need to establish some sort of metrics or KPIs to measure the success of your investment.

AI in Customer Service Statistics

AI has arrived in customer service to stay. In a highly competitive economy, with customers rapidly shifting their priorities and needs, AI is a powerful tool to reduce operational costs while ensuring an effective and high-quality service. 

According to HubSpot’s 2024 Annual State of Customer Service Report, 84% of respondents say AI tools will be instrumental in helping them meet customer service expectations, and 86% say AI will transform the experience customers get with their company. Equally, it is estimated that AI chatbots can save up to 3 billion working hours for customer support agents, resulting in considerable operational cost savings.

And all this without sacrificing quality. Rather, the opposite. As Kieran Flanagan, HubSpot’s SVP of Marketing, puts it in simple words:

In an AI world, support is live 24/7. And it probably has, over time, a better experience because an AI bot can have all of the information at once, where it’s really hard for an individual support agent to be able to have all of that information.

Kieran FlanaganSVP of Marketing at HubSpot

With that in mind, it is not surprising that the conversational AI market is expected to reach $33 billion dollars in 2023, based on Tidio estimates.

Future of AI in Customer Service

We’ve already seen that developments in AI are coming rapidly, but what can we expect further down the line? 

Generative AI in customer service

Technological breakthroughs in the field of NLP and deep learning in the 2010s led to the development of modern chatbots. However, despite the impressive conversational capabilities of these assistants, they weren’t able to generate new content.

This is already changing with the rise of generative AI. Powerful tools like ChatGPT and Google Gemini are taking chatbots to the next level, supercharging them to create personalized responses and handle complex queries. We’ve even seen Antrhopic’s computer use function carrying out tasks on a computer with a basic prompt. 

These tools will continue to grow and improve, giving more scope for automation, and freeing up human agents to deliver best-in-class customer service in other areas. 

Predictive analytics and AI

Customer service will keep improving thanks to predictive analytics and AI. For example, thanks to powerful machine learning, a model is now able to forecast customer behavior and preemptively resolve issues. Check out our separate article to learn everything about predictive analytics.

Ethical considerations and challenges

AI is rapidly reshaping the business ecosystem. However, as always occurs with emerging technologies, with power comes responsibility. As Glenn Hopper, Strategic Finance Leader, explains in this interview:

The biggest hurdles right now for the adoption of AI are data privacy and security issues, compliance, and trust in these gen AI-powered systems.

Glenn HopperStrategic Finance Leader

Despite the unique capabilities of AI, it’s important to consider its potential risks and regulatory concerns before implementing them into your customer service workflows:

  • Bias and discrimination. Biased AI models can result in unfair decisions that often exacerbate discrimination, particularly against minority groups.
  • Privacy issues. AI models are trained with vast amounts of data mainly extracted indiscriminately from the Internet. In many cases, such data contains personal data. This can lead to issues and risks related to data privacy and security.
  • Compliance risks. As new data protection and AI regulations enter into force in countries around the world, companies need to undertake compliance efforts to ensure fair and safe use of AI and avoid hefty fines. A great example of how the future of compliance will look like is the recently approved EU AI Act, a comprehensive regulation that requires companies to advance strict regulatory measures. Check out our EU AI Act Fundamentals Skill Track to learn about this innovative and ambitious rule and how to stay compliant.

Conclusion

AI is here to stay, unlocking a wide range of possibilities to improve customer service. The stakes are high, yet companies that successfully implement AI into their workflows will gain a competitive edge that can completely change the business landscape. 

It’s time for innovation; it’s time for AI. DataCamp is here to help you implement AI in your business. Check out our dedicated materials to start adopting the most powerful technology of our times:

AI in Customer Service FAQs

How is AI affecting customer experience?

AI provides an effective and efficient way for businesses to expand their capacity to serve more customers at a reduced cost. By replicating, and even augmenting human capabilities, AI-powered chatbots can collect and cross-reference information to develop responses and solutions to specific customer problems.

What are the benefits of AI in customer experience?

Some of the major benefits of AI in customer service are improved efficiency and operational cost reduction, personalization at scale, and 24/7 support.

What is the role of generative AI in customer services?

Generative AI is powering the new wave of customer service chatbots. Generative AI helps generate accurate responses to common queries, provide summaries of previous complaints and resolutions that agents can use in conversations, and generate product recommendations.

How will AI impact the future of customer services?

As generative AI becomes more ubiquitous in our lives, we can expect an overall improvement in customer services from companies across sectors.

What are the main challenges of implementing AI in customer service?

Some of the main technical challenges to implementing AI are related to integration issues, and lack of skilled personnel. Equally, it’s important to consider the ethical challenges of using AI, including potential bias and discrimination, privacy issues, and compliance risks.


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Author
Javier Canales Luna
LinkedIn

I am a freelance data analyst, collaborating with companies and organisations worldwide in data science projects. I am also a data science instructor with 2+ experience. I regularly write data-science-related articles in English and Spanish, some of which have been published on established websites such as DataCamp, Towards Data Science and Analytics Vidhya As a data scientist with a background in political science and law, my goal is to work at the interplay of public policy, law and technology, leveraging the power of ideas to advance innovative solutions and narratives that can help us address urgent challenges, namely the climate crisis. I consider myself a self-taught person, a constant learner, and a firm supporter of multidisciplinary. It is never too late to learn new things.

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