Why is Customer Service so important?
By 2026, customer expectations regarding the performance and speed of customer service will be extremely high and could determine whether customers stay with a company or switch to a competitor. A wide range of AI tools supports service teams and helps to reduce the costs of service and support within the company. Customer service is a strategic growth driver for companies, and customer requirements must be identified and met throughout the entire customer lifecycle.
Customer service is generally understood to mean all interactions and services that a company offers its customers before, during, and after a purchase.
Companies face a challenge in identifying customers' wishes and needs to reflect their interests and avoid communication gaps. This is where AI comes in: it is used wherever routine enquiries are answered, for example, but also to forward them to human employees in the event of service escalations.
Customer service aims to create satisfaction and build long-term customer relationships in order to ensure customer loyalty, brand loyalty and corporate success. The following trends are essential for 2026 in order to achieve this goal:
The following trends are essential for 2026 in order to achieve the goal:
1. Agentic AI
The trend in 2026 is clearly moving towards AI as a personal assistant or agent that enables fast and personalised interactions. Autonomous AI agents, or ‘agentic AI’, perform tasks independently while increasing precision and efficiency.
Agents are used for tasks such as greeting customers, conducting dialogues and sentiment analysis, i.e. emotional analysis during conversations. They act proactively and offer customers suggestions for suitable solutions. With the help of agentic AI, service processes can be customised, the consistency of responses increased and processing times reduced. The connection to internal systems (e.g. CRM or ERP) is particularly important here. Intelligent ticket routing ensures that every problem is immediately assigned to the appropriate AI agent or, in the case of more complex issues, to the most suitable employee.
2. AI and Automation
In addition to agent-based AI, predictive and generic AI are particularly important developments in customer service. These technologies are transforming the interaction between humans and automation in a decisive way.
AI is essential in the automation of business processes and provides relief by taking on repetitive, low-value-added tasks and executing them automatically. This includes, for example:
- Password resets: Immediate, secure self-service around the clock
- Shipping updates: Proactive notifications without customer enquiries
- Basic troubleshooting: Automated diagnosis and suggested solutions
- Ticket categorisation: Intelligent prioritisation and routing
Service employees are relieved of routine tasks and can apply their expertise where it has the greatest impact – in complex problem solving, emotional escalations and strategic customer consulting. The result: faster solution times and higher employee and customer satisfaction. Other trends that will become more important in 2026:
- Voice AI as the primary automation solution for enterprise CX strategies: This involves recognising the customer's tone of voice and routing, processing and resolving multi-intent queries in real time with empathy and context.
- Sentiment analysis enables emotional states to be recognised and responded to before frustration and possible escalation occur.
- AI-supported knowledge databases with self-learning: The AI analyses thousands of support tickets, identifies knowledge gaps and automatically generates FAQ articles.
3. Hyper-Personalization
In 2026, customers expect tailored, real-time, one-to-one interactions. Companies will use AI algorithms and customer data to make each touchpoint personalised. Relevant factors include purchase history, location, preferences, mood and general digital behaviour of customers. The service experience can then be personalised using generative AI, machine learning (ML) and real-time data analysis, benefiting both customers and companies:
- Individualised interactions
- High level of customer understanding
- More efficient service interactions
- Increased customer loyalty.
Personalised marketing at the beginning of the customer interaction can reduce acquisition costs by up to 50% and increase marketing ROI by 10–30%. (Gartner, 2026) Hyper-personalisation as a further development of customer retention strategies is an important trend in 2026, requires the implementation of a robust data infrastructure and entails high data protection requirements.
4. Omnichannel
To remain competitive, companies must use technologies such as AI and automation to ensure seamless communication across different platforms, whether email, chat, telephone or social media. Customers usually choose the channel that suits them best and meets their immediate needs. For example, a customer starts by searching the web shop, then has a query and asks the chatbot directly on the page. In the chat, they receive product help via a link to the knowledge database and can then order the appropriate solutions from anywhere and stay informed by email.
Omnichannel solutions integrate all relevant channels into a uniform system without losing context, so that customer data is directly available. Important performance factors are therefore the maturity of the channels and their adaptation to market requirements. Particularly important: multimodality must be supported so that customers can not only submit enquiries in text form, but also transmit and read images, videos and audio. This is helpful in the case of complaints, for example. Omnichannel support combines seamless channel integration, real-time data synchronisation, personalised interactions based on customer history, self-service options and comprehensive analytics for continuous optimisation of the customer experience:
5. Memory-rich Artificial Intelligence
Memory-rich AI refers to the ability of AI systems to store and actively use context, preferences and information across sessions and channels. In concrete terms, this means that customers do not have to repeat themselves when they follow up on a topic the next morning that they had already described to the AI the night before. As a result, they receive seamless, intelligent support, avoiding additional effort and saving support costs. It should be noted that, by definition, memory-rich AI processes personal data permanently and across sessions, which means that the core principles of the GDPR automatically apply. The principle of data minimisation (Art. 5(1)(c) GDPR) is particularly critical. Not everything can simply be stored ‘for later use’; companies must clearly define which data is actually to be saved. Users have the right to view, correct or have stored memories completely deleted at any time (Art. 17 GDPR). Data protection should be built into the architecture from the outset as a privacy-by-design principle in accordance with Art. 25 GDPR so that memory-rich AI can be used to its full extent.
6. Proactive Service
In a service context, proactive can also be interpreted as ‘no service necessary’: customers no longer have to contact support or search for help themselves; instead, the problem is automatically resolved or the relevant information is proactively provided. Instead of reporting a fault, the customer is notified directly, e.g. by email or WhatsApp. Companies should communicate problems before customers report them, suggest solutions immediately and thus create added value. Proactive service has been proven to reduce the volume of incoming tickets, while at the same time increasing the perceived quality of service. If customers do not actively perceive this, a competitor may be preferred.
7. Self-service Offerings
When service is required, customers can now often resolve simple issues themselves via self-service portals. Classic actions offered as self-service are related to products or services, e.g. returns processing or address changes, or downloading documents such as invoices. Websites are the most commonly offered self-service solutions due to their simplicity and accessibility, followed by customer portals and chatbots.
To make it as easy as possible for customers, it is important to design user-friendly, accessible interfaces. Clear language should be used, and voice assistants or chatbots should be directly accessible as a means of assistance. A holistic omnichannel approach to data synchronisation and problem solving optimises the customer experience and human expertise in complex cases, rounding off the service. Self-service is particularly effective when combined with customer insights, i.e. findings from customer feedback.
8. Transparency and Explainable AI
Explainable AI (XAI) refers to artificial intelligence systems in which decisions and actions are comprehensible and understandable to humans. Customers are shown HOW the result was achieved, not just the result itself. Users increasingly want AI solutions with transparent data flows and comprehensible solution logic.
Unlike ‘black box AI,’ explainable AI makes processes and results transparent. This builds trust among users and enables compliance with data protection laws (GDPR, EU AI Act). In an annual CX study by Forbes, 83% of consumers said that a positive customer experience strengthens their trust in a company or brand (Forbes, 2025). The higher the trust in an AI solution, the higher the chances that customers will be satisfied and use the services and products again. Without trust, even the best technologies remain ineffective: our article on ethical AI shows how companies implement it in practice and communicate responsibly with customers.
Conclusion
Customers are accustomed to receiving quick, personalised responses thanks to the many applications, AI chatbots and on-demand platforms available. This increases the demands placed on AI in customer service. In 2026, companies will secure a competitive edge by establishing genuine collaboration between humans and AI agents across all their digital channels. Companies should invest early in AI and omnichannel experiences to position customer service as a competitive advantage. The key to good customer service is to pursue a consistent data strategy and present processes transparently. Chatbots will continue to grow, especially Agentic AI-powered chat, as it enables efficient self-service solutions and is an ideal entry point for the use of AI in the company.
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