Human Touch : The Key Ingredient in AI Customer Service Strategies

Businesses in various sectors are using these tools to manage everything from basic questions to intricate claims processing, promising quicker response times and round-the-clock availability.

But here's what you need to know: the human element remains crucial to AI customer service strategies, and that won't change anytime soon.

Despite predictions that customer service jobs would be completely eliminated with AI adoption, the reality is quite different. Leading organizations like Allianz, Expedia, and easyJet are finding out that the most effective strategy isn't replacing humans with machines—it's forming a strong partnership between the two.

In this article, you'll learn why fully automated customer service is both unlikely and undesirable. I'll guide you through real-world examples of companies successfully implementing hybrid models that combine AI efficiency with human empathy.

You'll discover the limitations AI faces when dealing with complex situations, examine case studies from industry leaders, and understand the ethical considerations that should shape your AI customer service strategies.

The future isn't about choosing between technology and people. It's about using both to create outstanding customer experiences that neither could provide on their own.

The Evolution of AI in Customer Service

The journey of automation in customer support stretches back decades, beginning with simple interactive voice response (IVR) systems that directed callers through menu options. These early implementations laid the groundwork for today's sophisticated AI-powered applications, which can understand natural language, process complex requests, and learn from each interaction.

The Role of Machine Learning in Transformation

The transformation accelerated dramatically with machine learning capabilities. What started as basic rule-based chatbots evolved into intelligent systems capable of understanding context, sentiment, and intent. Companies began deploying these tools to handle the repetitive, time-consuming queries that once consumed countless hours of human agent time—password resets, order tracking, basic account information, and frequently asked questions.

Real-World Applications Reshaping Customer Support

Allianz's implementation of AI voice assistant technology demonstrates how far automation in customer support has progressed. Their multilingual assistant, launched in September and operating in more than 20 languages, provides roadside support for breakdowns. The system doesn't just answer calls—it intelligently assesses urgency. When a lone parent with young children calls about a breakdown in the middle of the night, the AI recognizes the critical nature of the situation and immediately escalates to human agents.

The insurer's Australian division pushed innovation further with claims processing with AI apps. Their refrigerator spoilage claims app, introduced in July, streamlines what was once a lengthy process. Homeowners who lost food during power cuts caused by severe weather can now file claims rapidly through an intuitive interface. The app guides users through documentation, validates information, and accelerates processing times that previously stretched across days or weeks.

Josef Teglas, Allianz's group head of data and AI, describes the technology as a "superpower" that improves customer lives by reducing turnaround times and resolving problems faster. The efficiency gains are measurable—routine queries that once required 10-15 minutes of agent time now resolve in seconds through automated systems.

The Impact on Customer Service Economics

These AI-powered applications excel at pattern recognition and data processing. They handle spikes in call volume during peak periods without degradation in response times. They work around the clock without breaks, providing consistent service quality regardless of time zones or holidays. The technology has fundamentally shifted the economics of customer service, allowing companies to scale support operations without proportionally scaling headcount.

Limitations of Fully Automated Customer Service

The idea of having customer service completely run by machines without any human agents faces major challenges that go beyond just what technology can do right now. According to research by Gartner, organizations that are hoping to use AI to completely get rid of their service workforce should think again. Their study predicts that by 2027, half of the organizations that planned to significantly reduce their service workforce because of AI will abandon these plans. This isn't just a temporary setback—it shows the basic limitations of how AI deals with complicated customer situations.

The Reality Check on Agentless Customer Service

Gartner's report, titled "Agentless Customer Service Should Not Be Your Goal," challenges the overly optimistic predictions made by tech leaders like Sam Altman. While OpenAI's chief executive suggested customer service roles would be "totally, totally gone," the evidence points in a different direction.

AI struggles when faced with situations that require:

• Nuanced judgment
• Emotional intelligence
• Contextual understanding beyond pattern recognition

When AI Works: Simple Queries

Consider the difference between a customer asking about their account balance versus someone dealing with a sensitive billing dispute following a family emergency. The first scenario fits neatly into AI's capabilities.

When Humans Excel: Complex Issues

The second scenario demands:

1. Empathy
2. Flexibility
3. The ability to read between the lines

These skills remain firmly in human territory.

Responsible AI Deployment: A Must for Companies

Responsible AI deployment has become a critical concern for companies implementing these technologies. Josef Teglas from Allianz emphasizes the importance of rolling out AI "in a responsible and safe manner." This caution comes from real-world feedback showing that poorly implemented AI can damage customer relationships instead of strengthening them.

When AI mishandles a sensitive situation or fails to recognize when human intervention is needed, the resulting customer frustration can undo years of brand loyalty.

Challenges in Agentless Customer Service

The difficulties with agentless customer service also apply to:

• Situations requiring creativity
• Problem-solving outside established protocols
• Making judgment calls that balance company policies with customer needs

These scenarios occur daily in customer service environments, making fully automated solutions both impractical and potentially harmful to the customer experience.

The Hybrid Customer Service Approach: Combining AI and Human Agents

Industry leaders widely agree that the hybrid customer service approach is the best way forward. Kathy Ross, co-author of Gartner's study on AI in customer service, explains this vision clearly. "AI and automation are transforming how customer service organisations serve customers, but human agents are irreplaceable when it comes to handling nuanced situations and building lasting relationships," she says. This view sees AI as a partner rather than a replacement, allowing companies to provide better support for complex or sensitive issues.

Jo Causon, chief executive of the London-based Institute of Customer Service, supports what she calls a "blended approach in customer service." Her philosophy is based on a simple idea: AI is a tool to make humans more effective, not to eliminate human involvement. "I don't think that we would want to see AI as a pure replacement for human skills. It's more about the tool to make humans more effective," she says. This framework recognises that the human touch is still crucial in AI customer service strategies, even as technology handles more routine interactions.

How the Integration Works in Practice

Companies using this model usually organise their systems based on a strategic division of tasks. AI takes care of the initial contact with customers, gathering important information and resolving simple queries. When situations become too complex for AI to handle, the system transfers the interaction to human agents—but only after passing on all the details collected during the automated stage.

Expedia demonstrates this smooth transition process effectively. Chief product officer Shilpa Ranganathan reveals that AI resolves more than 50 per cent of customer queries at the travel portal.

The technology manages simple bookings and standard questions, but knows when complexity requires human intervention. "We use AI as our first touch but, at the same time, whatever information the AI collects is seamlessly transitioned to the human agent," Ranganathan explains. This approach eliminates the frustration of customers having to repeat themselves when speaking with a person.

The Collaborative Advantage

The advantages of collaboration between AI and human agents go beyond operational efficiency. Human agents receive detailed information from AI systems, enabling them to jump straight into problem-solving instead of spending time gathering information. The technology takes care of repetitive tasks that drain energy and morale, allowing staff to concentrate on situations where empathy, creativity, and nuanced judgment add real value.

Jonathan Corbin, chief executive of MavenAGI, views this relationship from a customer-focused perspective: "We're actually letting humans be able to engage with the customers who need it most: folks like my mom who really need that human touch." This viewpoint shows how the hybrid model optimises resource allocation, ensuring that human attention goes to those who benefit from it the most.

Case Studies of Companies Embracing the Hybrid Model

Real-world implementations demonstrate how organizations across different industries are successfully balancing AI capabilities with human expertise. These companies show that the hybrid model isn't just theoretical—it's delivering measurable results right now.

Allianz: Prioritizing Urgency Through Intelligent Voice Assistance

Allianz deployed a multilingual voice assistant in September that handles roadside support across more than 20 languages. The system's intelligence goes beyond simple query resolution—it's trained to recognize urgent situations requiring immediate human intervention.

When a lone parent calls at midnight with young children in a broken-down car, the AI identifies the urgency and transfers the call directly to a human agent without delay. This approach ensures vulnerable customers receive personalized attention when they need it most, while the AI handles routine breakdowns efficiently.

The German insurer also launched an app in Australia that processes refrigerator food spoilage claims following power outages. Josef Teglas, Allianz's group head of data and AI, describes the technology as a "superpower" that reduces turnaround times and resolves claims faster—but he emphasizes deploying it responsibly and safely.

Expedia: Seamless Transitions for Complex Travel Planning

At Expedia, AI now resolves more than 50 percent of customer queries. Chief product officer Shilpa Ranganathan explains their strategy centers on using AI as the first point of contact, collecting information that seamlessly transitions to human agents when needed. Complex travel itineraries—multi-city trips with specific requirements or last-minute changes—get transferred to staff members who can navigate the nuances that AI can't fully grasp.

easyJet: Crisis Management with AI-Powered Social Scanning

easyJet takes a collaborative approach where AI suggests responses to customer inquiries via telephone, live chat, and email. Staff review these recommendations and adjust them before sending replies. Customer service director John Leighton views this as an investment in customer experience rather than cost-cutting.

The airline's AI-powered social media scanning tool proved its value during the 2023 Greek wildfires. The system flagged keywords like "stranded" and "elderly," enabling staff to identify and assist the most vulnerable customers quickly. This combination of AI detection and human compassion helped easyJet manage a crisis situation that required both speed and sensitivity.

The Very Group: From Apprehension to Record Satisfaction

The Very Group, a UK-based online retailer, experienced initial employee apprehension about AI implementation. Nick McBrien, financial services chief executive, reports that concern dissolved once staff realized the technology supported their performance rather than replaced them. The company achieved its highest-ever customer satisfaction scores in the financial year ending June 2025—a result McBrien attributes partly to AI guidance helping employees deliver better service.

The Importance of Human Touch in Improving Customer Satisfaction with AI Support

The technology behind today's customer service platforms may be impressive, but it cannot replicate the fundamental human ability to understand and connect with others. When you're dealing with a frustrated customer who's had a service issue, or someone going through a difficult situation, being able to recognize their emotions and respond with genuine understanding becomes crucial.

Why Human Connection Matters in Service

Human connection in service works on multiple levels that AI simply cannot reach. Take the example of Allianz, where a single parent is stuck at night with young children—while the AI system correctly identified this as urgent, the actual support needed human judgment to navigate the fear, stress, and specific circumstances of that family's situation. The voice assistant picked up on certain words and patterns, but the human agent grasped the significance of the moment.

When Does Customer Satisfaction with AI Support Improve?

Customer satisfaction with AI support reaches its highest point when human agents step in for complex situations. Here are some examples:

1. A grieving customer needs to cancel a deceased family member's travel plans
2. Someone requires changes to their accommodation due to unexpected medical emergencies
3. Customers are facing financial difficulties and need flexible payment solutions
4. Complicated complaints involve multiple service failures that require creative problem-solving

What Makes Human Agents Better at Handling Situations?

Human agents are skilled at understanding what isn't being said. They can sense when a customer's voice is hesitant, recognize when someone feels embarrassed about fully explaining their situation, or understand cultural contexts that affect communication styles. These agents have the ability to make judgment calls that balance company policies with compassionate exceptions when necessary.

How Do Human Agents Build Relationships?

The value human agents bring goes beyond solving problems; it extends into building relationships. They remember past interactions, anticipate needs based on customer history, and create genuine connections that turn transactions into meaningful experiences. This emotional effort—the ability to make customers feel heard, valued, and understood—cannot be replaced when it comes to creating long-lasting relationships that Gartner's research highlights as crucial for effective customer service.

Responsible Implementation and Ethical Considerations of AI in Customer Service

The power of AI in customer service comes with significant responsibility. Josef Teglas, Allianz's group head of data and AI, emphasizes the critical need to roll out AI "in a responsible and safe manner." This approach recognizes that while AI offers tremendous capabilities, rushing implementation without proper safeguards can damage customer trust and employee morale.

Responsible and safe AI implementation methods

Responsible and safe AI implementation methods require companies to establish clear guidelines before deployment. You need to test AI systems thoroughly in controlled environments, monitor their performance continuously, and create fail-safes for when the technology encounters situations beyond its capabilities.

Allianz demonstrates this principle by training their voice assistant to recognize urgent scenarios—like a lone parent stranded at night with children—and immediately escalate to human agents rather than attempting to handle the situation algorithmically.

Ethical deployment of AI

The ethical deployment of AI extends beyond technical considerations to address the human workforce. When The Very Group introduced AI tools, employees were "quite apprehensive" about their job security. Nick McBrien, the company's financial services chief executive, tackled these concerns head-on through transparent communication.

He made it clear the technology was designed to support staff, not replace them. This honest approach transformed initial anxiety into acceptance as employees recognized AI as a tool that enhanced their performance.

Employee adaptation to AI tools

Employee adaptation to AI tools succeeds when companies invest in proper training and demonstrate genuine commitment to their workforce. The Very Group's record-high customer satisfaction scores—achieved partly through AI-guided employee interactions—prove that workers can embrace technology when they understand its purpose. You can't simply introduce AI and expect immediate acceptance; you must show your team how these tools make their jobs easier and more effective.

Human touch remains key to AI customer service strategies

Human touch remains key to AI customer service strategies even as technology advances. Ethical AI implementation means preserving the irreplaceable elements of human interaction while leveraging automation for efficiency. You're not choosing between technology and people—you're creating a framework where both work together to serve customers better. This balance protects customer interests by ensuring sensitive situations receive appropriate human attention while routine queries benefit from AI's speed and availability.

Future Outlook: Balancing Innovation with Human-Centric Service Models

The future of customer service jobs looks dramatically different from the dire predictions that once dominated industry conversations. Gartner's research paints a revealing picture: by 2027, half of organizations that planned significant workforce reductions due to AI will abandon these plans. This shift reflects a growing recognition that the impact of AI on workforce dynamics requires a more nuanced approach than simple replacement strategies.

The Evolving Role of Human Agents

The evolving role of human agents centers on elevation rather than elimination. As AI handles routine inquiries and data processing, you'll see customer service professionals transitioning into roles that demand higher-level thinking. These positions require:

• Complex problem-solving that involves interpreting unique customer situations
• Emotional intelligence to navigate sensitive conversations and build trust
• Creative solutions for scenarios that fall outside standard protocols
• Strategic relationship management with high-value clients

Companies that successfully navigate this transition recognize AI as what Josef Teglas calls a "superpower"—a tool that amplifies human capabilities rather than replaces them. You're witnessing organizations redesign their service models around this principle. Agents spend less time on repetitive tasks and more time applying judgment, empathy, and creativity to challenging customer interactions.

Transforming the Workforce

The workforce transformation extends beyond individual roles. Training programs now emphasize skills that complement AI capabilities: critical thinking, emotional awareness, and adaptive communication. You'll find customer service teams developing expertise in AI collaboration—learning when to trust automated recommendations and when to override them based on contextual understanding.

This evolution creates opportunities for career advancement that didn't exist in traditional call center environments. Staff members who once handled hundreds of simple queries daily now manage complex cases that directly impact customer loyalty and lifetime value. The technology handles volume; humans handle value.

Conclusion

The evidence is clear: human touch remains key to AI customer service strategies. Companies like Allianz, Expedia, and easyJet demonstrate that the most effective path forward isn't choosing between technology and people—it's strategically combining both.

The hybrid models success factors we've explored throughout this article reveal a consistent pattern. Organizations achieving the highest customer satisfaction scores are those that deploy AI for efficiency while preserving human judgment for complexity. This approach transforms AI from a replacement threat into a collaborative tool that amplifies human capabilities.

Sustainable AI strategies in the service industry require more than just technological implementation. You need transparent communication with employees, responsible deployment frameworks, and a commitment to keeping customers' best interests at the center of every decision. The companies succeeding in this space aren't rushing to eliminate human agents—they're empowering them.

The human touch key ingredient isn't a nostalgic preference for the past. It's a practical recognition that empathy, context interpretation, and relationship building remain uniquely human strengths. As you evaluate your own customer service strategy, ask yourself: Are you using AI to enhance human connection, or attempting to replace it?

The organizations that thrive will be those that view AI as Josef Teglas does—as a "superpower" that makes humans more effective, not obsolete.

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