AI in customer service means using artificial intelligence to improve the quality and efficiency of support. Technologies like chatbots and phone assistants allow customer inquiries to be processed more quickly, frequent issues to be answered automatically, and personalized solutions to be provided in real-time. With rising expectations for availability, response speed, and omnichannel support—customers expect seamless assistance across various channels—AI in customer service is becoming a central driver of innovation for many businesses.

What’s behind AI in customer service?

The high expectations for support services present challenges for many companies. AI-powered customer service— a support solution based on artificial intelligence—provides an efficient way to address the many complexities and tasks associated with handling customer inquiries. For example, inefficient processes and a shortage of resources often result in longer waiting times or customers having to raise their concerns several times, which reduces the quality of service. AI provides the right solutions for this, for example by analyzing requests in real time and forwarding customers to the right support staff.

In customer service, it becomes clear that AI serves not as a replacement, but as a complement to human work. The goal of AI-powered customer service is to make service processes more efficient while ensuring the quality of customer interactions.

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How does AI-supported customer service work?

In customer service, AI is no longer just a buzzword, but an innovation driver that significantly changes communication with stakeholders. Where customer contact exists, artificial intelligence in customer service can be used in two distinct ways – predictive and generative.

Predictive intelligence

Artificial intelligence can analyze the subject and content of an email or voice message to deduce the customer’s issue. This allows messages to be automatically categorized and transferred into the ticketing system. With AI in customer service, more than half of all support tickets can be automated on average. AI tools even check the tone to infer the mood of customers (Sentiment Analysis). If the case is then taken over by an employee, key data such as the name and customer number are already recorded.

Generative AI

Artificial intelligence in customer service not only contributes to a higher degree of automation but also inherently has the ability to respond to inquiries. Therefore, there is also the possibility that the bot creates responses and solves problems independently. The basis for the response is data from past cases that the AI tool deems helpful. This type of AI-driven customer service is especially suitable for low-priority issues. Machine learning enables AI to draw conclusions from previous interactions. As a result, the system becomes more precise over time and can independently solve recurring problems, reducing wait times.

Note

An innovative approach to improving generative AI in customer service is Retrieval-Augmented Generation (RAG). In this approach, the AI system accesses a company-specific knowledge database or external information sources to generate precise, fact-based responses.

Multimodal AI systems

Modern AI applications are increasingly based on multimodal models, which can simultaneously process information from text, speech, and images. This opens up new use cases in customer service, such as:

  • Analyzing screenshots in support inquiries
  • Simultaneously processing speech and text in phone or chat channels
  • Capturing forms with visual elements

Multimodal AI improves the quality of problem analysis and enables more comprehensive, context-based responses in real time.

What are some practical examples of AI in customer service?

AI is usually integrated into customer service in the form of AI chatbots. These can not only record customer data, but also answer customer queries. Chatbots can be integrated into the following applications, among others:

In addition to live chats, AI is also commonly used in phone service in customer support. AI-powered phone assistants have the ability to handle calls, transfer them to employees when necessary, answer simple questions, and perform basic tasks such as scheduling appointments.

Furthermore, artificial intelligence in customer service is also used for automated email classification, self-service through intelligent FAQs, and agent-assist systems that support employees during ongoing customer conversations. Custom GPTs can be specifically trained on company-specific content and tone. This allows for personalized customer engagement based on existing information and enhances the relevance of responses.

Next-generation AI systems will increasingly focus on a personalised customer journey and the automation of customer service processes. In addition, AI in customer service is expected to go beyond handling standard enquiries and support more complex cases by preparing solutions or guiding users towards the next steps.

Note

If AI support is planned across multiple touchpoints, such as email and chat, it’s best to introduce each channel step by step. This makes it easier to apply insights from one implementation to the next.

AI phone assistant in focus

An AI phone assistant is a specialized form of customer service with AI that automates phone support or assists employees in real time. It understands spoken language, identifies issues, and responds with appropriate answers or actions. An AI phone assistant handles simple inquiries, prepares more complex cases, and supports employees with real-time information. This significantly relieves the hotline and ensures shorter wait times.

Typical use cases include answering simple questions, scheduling appointments, or structuring call pre-qualification before they are forwarded to the appropriate support.

AI customer service example using the IONOS AI Receptionist

IONOS offers an AI Receptionist in customer service that automatically handles incoming calls, recognizes inquiries, and processes them systematically. Standard requests are answered directly, while more complex cases are specifically routed to the appropriate support team. AI-powered customer service thus ensures higher availability with consistent service quality.

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Data protection and compliance

Artificial intelligence in customer service must meet the highest standards for data privacy and security. When using an AI phone assistant, it is essential to ensure that all processes are designed to comply with applicable data privacy laws and that personal data is protected. Relevant solutions take data privacy, transparency, and security into account at the system level.

In addition to GDPR (for applicable companies in the EU), other legal frameworks, such as the CCPA and CPRA in California, are becoming increasingly important. Companies using AI in customer service need to assess whether their systems fall under any specific risk categories defined by these laws and meet the corresponding requirements for transparency, control, and documentation.

The 5 most important advantages in AI customer service

Customers benefit in various ways from AI-powered support:

  • 24/7 availability and fast response times: AI systems are available around the clock, leading to shorter wait times and enabling quick responses to inquiries.
  • Relief for employees: Routine inquiries are handled automatically, allowing employees to focus on more complex cases.
  • Increased efficiency and cost savings: By automating standard inquiries, companies can save time and reduce costs.
  • Improved customer satisfaction: Fast, precise answers and personalized solutions lead to higher satisfaction among customers.
  • Data analysis and forecasting: AI identifies patterns and performs sentiment analysis to capture customer sentiment and predict future needs.

Challenges in AI customer service

Despite all the advantages, AI in customer service also presents challenges. These mainly include data privacy and security aspects, as well as acceptance among employees and customers. AI does not replace humans, but serves as a supportive tool.

The human-in-the-loop approach has proven highly effective where artificial intelligence takes care of standardized processes, while human agents remain involved in complex, sensitive, or emotionally charged situations. The real strength of modern customer service AI lies in the combination of human empathy and technological efficiency.

In short: AI can improve support, but it does not replace human empathy. Ensure that sensitive or complex issues continue to be handled by experienced individuals.

What should you pay attention to when integrating AI in customer service?

A successful implementation of AI in customer service requires strategic planning. The first step is to analyze the most common enquiries and service processes. It is advisable to start with clearly defined use cases, such as an AI phone assistant or automated email routing.

Equally important are staff training and transparent communication with customers. When it is clearly communicated when and how AI is used in customer service, acceptance increases in the long term.

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