Beyond Automation: Reimagining Customer Service with AI and Human Connection with Christian Berends, Global Customer Service Leader

Christian Berends is a customer service leader with extensive experience in global customer operations, customer experience, and AI-driven transformation. As Global Customer Service Manager at Hunkemöller, he is focused on enhancing customer service through technology, automation, and operational excellence.

His work centers on leveraging AI to improve efficiency, increase scalability, and deliver better experiences for both customers and customer service teams.

As customer service continues to evolve, Christian Berends shares his experiences and insights on using AI and automation to improve operations while keeping the customer and human connection at the centre.

Q1. What motivated you to pursue a career in customer service operations, and what key experiences shaped your journey into global customer experience leadership?

I have always been motivated by the combination of people, performance and problem-solving. Customer service sits at the intersection of all three: you can improve the customer experience while also making an operation more efficient and scalable. My journey has taken me from operational and commercial roles at companies such as Diesel and Booking.com, into customer service leadership at Netflix, Landal, Talpa Networks, Holland Casino and now Hunkemöller. Each step taught me something different—from building teams and operating models to managing international delivery, transformation and cost-to-serve. Over time, I became particularly interested in how technology and customer insight can fundamentally change the way customer service operates.

Q2. How have you leveraged AI, automation, and emerging technologies to improve customer service efficiency, scalability, and overall service performance?

At Hunkemöller, AI and automation are central to the transformation of customer service. I have been driving the use of conversational AI, automated email handling, digital self-service and Salesforce capabilities to resolve more customer needs without requiring an agent for every interaction. The principle is simple: automate the predictable, give customers better self-service, and allow our people to focus on the cases where judgement and empathy add real value. This is not only about reducing cost; it is about creating a more scalable operation and a better customer journey.

Q3. What are some of the most significant challenges organizations face when implementing AI in customer service, and how can they overcome them?

The biggest challenge is often not the technology—it is the operating model around it. Organizations can implement an AI tool quickly, but creating the right knowledge, processes, data, governance and ownership takes more work. I also see a tendency to automate before understanding the customer journey. My approach is to start with the problem: identify the highest-volume or highest-friction journeys, establish a clear baseline, improve the underlying process and knowledge, and then use AI where it genuinely adds value. Strong human oversight, clear KPIs and continuous improvement are essential.

Q4. What role does customer data and feedback play in determining which customer service processes should be automated or enhanced through AI?

Customer data tells us where the real opportunities are. I look at contact reasons, volume, repeat contacts, customer feedback, CSAT, resolution rates and the effort required from both the customer and the agent. If a large proportion of contacts are predictable and rules-based, that is a strong automation candidate. If customers are repeatedly contacting us because information is unclear or a process is broken, the answer may be better self-service or journey redesign rather than simply adding AI. Data helps us distinguish between a technology opportunity and a process problem.

Q5. What strategies have you found most effective in using AI to manage growing customer service volumes while maintaining consistent service levels?

I focus on three layers. First, prevent unnecessary contacts through better customer journeys, proactive communication and self-service. Second, automate suitable contacts through AI and workflow automation. Third, strengthen the remaining human operation with good workforce management, knowledge and performance management. This creates a scalable model rather than simply adding more agents as volume grows. At Hunkemöller, this approach has contributed to reducing the customer contact rate from 14% to 7%, while CSAT improved from 70% to 86%.

Q6. Can you describe a specific instance where AI or automation significantly improved the efficiency or effectiveness of a customer service operation?

At Hunkemöller, we have been using conversational AI and automation across chat, email and Salesforce-supported customer service journeys. A good example is using AI to handle predictable customer questions and guide customers to the right information before an agent becomes involved. This reduces manual handling and gives customers an immediate response. The important part is that automation is connected to the broader service model—knowledge, case handling, escalation and measurement—rather than being treated as a standalone chatbot project.

Q7. Could you share a success story where the implementation of AI delivered measurable improvements in customer experience, operational performance, or employee productivity?

A strong example is the broader digital transformation at Hunkemöller. By combining AI, self-service, customer journey improvements and stronger operational governance, we reduced the contact rate from 14% to 7% and improved CSAT from 70% to 86%. The value is bigger than the individual automation rate: fewer unnecessary contacts reduce pressure on the operation, while customers who genuinely need help can receive more focused support. It also creates a better environment for agents because they spend less time on repetitive interactions.

Q8. Which methodologies or frameworks do you use to identify customer service processes that are best suited for automation while ensuring the right level of human involvement?

I use a practical combination of volume, complexity, customer value, risk and automation potential. High-volume, repetitive, predictable and low-risk processes are usually the first candidates. Processes involving emotion, exceptions, financial impact, complaints or complex judgement need a stronger human role. I also look at the end-to-end customer journey rather than an individual contact reason. The key question is not ‘Can we automate this?’ but ‘What is the best combination of automation and human involvement for this customer journey?’

Q9. How do you collaborate with technology, operations, and customer service teams to successfully introduce AI while ensuring employees are equipped to work effectively alongside these technologies?

I treat AI as a cross-functional transformation rather than an IT implementation. Customer Service brings the customer and operational perspective; Technology brings the platform and integration expertise; and the business provides the strategic priorities and governance. Agents also need to be involved because they understand the exceptions and pain points that data alone may not reveal. Training, communication and clear ownership are critical. People need to understand what the technology is doing, what remains their responsibility and how their role becomes more valuable—not simply smaller.

Q10. How do you balance automation and efficiency with the human touch, empathy, and personalized support that customers continue to expect?

I don’t see automation and human service as opposites. The goal is to automate the transactions and preserve the human interaction. If a customer simply wants an order update or a piece of product information, an AI-powered self-service experience can be faster and more convenient. If the customer has a complaint, a complex problem or needs reassurance, that is where a human should be available. Good AI should make human service more meaningful by removing the repetitive work, not by removing empathy.

Q11. What best practices have you implemented to help customer service teams transition from handling repetitive tasks toward more complex, valuable, and customer-focused interactions?

First, remove or automate the repetitive work. Second, redesign roles and performance measures so that quality, resolution and customer outcomes matter—not just speed. Third, invest in knowledge, coaching and training so agents are confident handling more complex conversations. My experience at Landal, for example, included building scalable onboarding and training programmes, while at Hunkemöller the focus has been on combining operational governance with digital transformation. The long-term opportunity is to turn customer service into a higher-value problem-solving function rather than a transaction-processing function.

Q12. How do you stay updated with the latest developments in AI, automation, customer service technology, and the evolving role of customer service teams?

I stay close to the technology while keeping the customer and operation at the centre. I follow developments in AI and conversational technology, speak with technology and CX specialists, and learn from what we see in real operations. My current work at Hunkemöller gives me a very practical laboratory for this because I am actively involved in AI, Salesforce, self-service and operating-model transformation. I also believe the best learning comes from testing ideas, measuring outcomes and being prepared to change direction when the data says something different. AI is moving quickly, so curiosity and continuous experimentation are essential.

Conclusion

Christian Berends’ perspective highlights how the future of customer service is not simply about doing more with AI, but about using technology thoughtfully to create better experiences for both customers and employees.

By combining customer data, journey improvements, automation and strong operational foundations, organisations can reduce unnecessary effort while allowing service teams to focus on the interactions where empathy, judgement and problem-solving matter most. His experience at Hunkemöller demonstrates how this balance can translate into measurable improvements in both customer satisfaction and operational performance.

As AI and automation continue to reshape customer service, the opportunity lies in moving beyond transaction processing towards a more valuable, customer-focused function — one where technology handles the predictable and people are empowered to handle what truly requires a human touch.

“Christian will be joining us at the 5th Annual Conversational AI & Customer Experience Summit Europe 2026 in Munich. Here’s a glimpse into his insights and experiences ahead of the event.

Look forward to hearing more from him, along with perspectives from other industry leaders in our next edition”