Enhancing Customer Service Experiences: Bridging the Gaps and Embracing AI for Seamless Customer Experience

Imagine you call your telecom service provider to resolve a billing issue. You explain your problem to one agent, only to be transferred to another department and asked to repeat everything. This frustrating experience is a classic example of poor service design, where gaps between departments, processes, and people create a disjointed journey for the customer. What is even more frustrating is that most of these issues linger on — neither can customers take definitive actions from their end, nor do companies have the intention or understanding to resolve the issues effectively.

In my decades-long experience, I have seen how the customer service landscape is changing. However, one fundamental thing remains almost unchanged. For most companies, customer service is still treated as an obligation, not an opportunity to create loyalty. While many boast high NPS scores and can make glossy presentations about customer delight, customer service is still considered a cost center. This is why it often remains mediocre.

What is even worse is that, in the endless game of efficiency improvements and cost-cutting, companies have gone overboard with automation, making customer service robotic and faceless. It is uncertain whether companies are genuinely trying to gauge customer dissatisfaction because everything, including feedback, feels transactional. Sometimes, customers are even prompted for better feedback irrespective of their actual experience.

In today’s hyper-connected world, customer experience can determine a company’s success. Service design is the blueprint that shapes how services are delivered, but it often suffers from glaring gaps. These gaps arise due to siloed departments, poor coordination with third-party vendors, and senior management being disconnected from ground realities — viewing customer service as an obligation rather than an opportunity to create a unique experience and build a long-term customer relationship.

On one hand, technology is transforming this landscape. Artificial Intelligence (AI), Agentic AI, Robotic Process Automation (RPA), and other process automation tools are helping businesses bridge these gaps, creating smooth and efficient customer journeys, increasing productivity, and reducing costs. However, this is leading to an association between brands and customers that feels monotonous, robotic, and devoid of human touch. Until the next phase of hyper-personalization is introduced by AI, many customer experiences will lack personalization due to standardized process automation.

Common Gaps in Service Design

Siloed Approach

Departments often work in isolation, leading to fragmented experiences. When customers are transferred between teams, their information is not shared efficiently, forcing them to repeat their details. Recently, I requested my home loan repayment schedule from one of the largest public sector banks. I wrote to the branch where I held the loan, and they forwarded the request to the Regional Processing Centre. There was no response, so I called the call center. After a long wait, I reached an agent and explained my issue. He asked me to contact the branch again. Finally, I escalated the matter to the head office via email and got a response. This simple requirement could have been fulfilled through a self-service feature on net banking, or at least a clear procedure should have been laid out. The branch and the regional office were unclear about who was responsible for servicing such a request. This is just one example; there are countless others like it.

Poor Value Alignment and Lack of Coordination with Third-Party Vendors

Businesses frequently outsource services such as delivery, support, or billing. When third parties are not aligned with a company’s values or service standards, customer experience suffers. Often, these vendors employ low-quality resources to save costs, and their staff are paid per transaction. As a result, they rush through tasks to meet daily quotas and lack the mindset to prioritize customer satisfaction.

Once, I had to return a piece of furniture bought through a large e-commerce company because it did not meet my expectations. While the company agreed to refund my money after the pickup, I had a terrible experience. Each time someone came to collect the consignment, they left without taking it because they arrived on bikes instead of a van. This happened three times due to poor coordination.

In another case, a friend working in a reputed laboratory applied for a loan from a reputed private bank. A third-party verifier visited his office without prior notice and insisted on taking his photo at his desk. My friend was furious because external visitors were not allowed inside the lab. He was also uncomfortable with the verifier questioning his colleagues. Ultimately, he dropped the loan application due to privacy concerns.

Lack of Senior Management Visibility

I remember my boss asking us to call our service call center, posing as customers, to evaluate agent performance. We were in the business of selling and supporting IT equipment. I wonder if CEOs of large banks or telecom companies ever do the same. Senior management often delegates service delivery, leading to a lack of real customer feedback. Middle managers and operational teams are so absorbed in daily tasks that they seldom have the bandwidth for systemic improvements. Annual customer satisfaction surveys often fail to reflect reality due to poor sample representation, and customers may avoid giving poor ratings to escape follow-up questions or for fear of sounding rude.

Over-Reliance on Automation

Automation saves time and costs, but relying solely on it can create a mechanical customer experience. In the late ’90s, when centralized call centers were new, my company faced difficulties convincing customers that they would still receive prompt service. Customers preferred a familiar local contact. Today, automation has replaced many human interactions. You chat with bots, message on WhatsApp, or send an email. However, this can be overwhelming. Recently, I needed assistance with a booking through a popular website. Their chatbot and online forms did not address my issue, and their call center was only for sales inquiries. I eventually resorted to Facebook Messenger, where a human finally helped me. This was pretty annoying and I had to spend disproportionate time on simple tasks.

Automation should be preceded by process reengineering. Without reviewing and refining underlying processes, automation can amplify inefficiencies.

Lack of Empathy Toward Customers

Businesses often prioritize functionality and optimization over creating a great customer experience. Customer satisfaction is subjective and difficult to measure, so companies focus on hard KPIs like response time and agent productivity. Many service design principles lack a Design Thinking approach centered on empathy.

Consider government websites — many are disjointed, with poor UI design and sluggish responses. A well-known open university in India has an unsecured website that frequently times out. Even in physical services like healthcare, processes are siloed, and disjointed, and testimony of lack of proper empathy.

Customer feedback collection often feels like a formality. How many times have you received a call from a car service center asking for a 10-point rating after a service visit? They are interested to know real feedback, they just need a put out good statistics.

Principles for Effective Service Design

Customer Experience as the Center of Gravity

Service design must prioritize customer experience over internal business convenience. Companies should view every interaction as an opportunity to create long-term loyalty. Acquiring new customers is costlier than retaining existing ones. In today’s connected world, negative feedback spreads quickly. Companies that cannot offer personalized services due to low margins should set realistic expectations and automate processes to ensure seamless experiences.

Collaboration Across Teams

For low-value items where personalized services are not possible, the company must ensure that they build a robust service delivery process and automate it to perfection to create seamless and uniform experiences.

Applying Design Thinking Principles

Design Thinking emphasizes empathy, iteration, and prototyping. By understanding customers’ pain points, businesses can redesign services to meet real needs. While designing for the first time or redesigning, one must consider the customer’s entire journey, cutting across different segments, and bringing seamlessness and uniformity. For example, for a SaaS company, the sales and customer success processes could be two very distinct functions, yet the customer must feel they are dealing with two integrated entities within the same organization. From sales closure to installation to customer service, the transition must be smooth. I have seen a company’s installation engineer call customers to ask for basic details about the product they had purchased; the engineer should have been internally briefed beforehand.

Process Standardization and Reducing Person-Induced Variability

Standardizing processes ensures consistency and reduces errors caused by individual differences. Customers should receive the same quality of service regardless of who handles their case. Naturally, individuals vary in their service delivery approach. Some go the extra mile, while others are happy with doing the minimum. Therefore, it is better to outline Standard Operating Procedures (SOPs) that all service delivery professionals must follow. For behavioural aspects, clear guidelines should be provided on how to maintain the business code of conduct and handle objections without being hostile to customers. Training plays a crucial role in ensuring this consistency.

Personalization

While standardization is important, personalization is equally crucial. High-level automation limits personalized human interaction to a great extent. However, AI is unlocking new opportunities for personalization. AI can analyze customer data to customize offerings and interactions, creating a more engaging experience. This opens up whole new frontiers. Today, based on past data and behavior, many companies can recommend what customers should buy, what to watch, or where to dine on the weekend.

It Is a Team Game

Customer service delivery is not the responsibility of just the frontline customer service engineer or mid-level manager. The entire company, including those who may not directly interact with customers, must imbibe the ethos of customer-first principles. When it comes to solving customer issues, invisible corporate walls should not be impediments. Similarly, senior management should not only have a bird’s-eye view but also experience being a customer of their own company. There are many stories of legendary business leaders rolling up their sleeves to work on the front line, staying in touch with ground realities. This is why they never lost their edge. Customer service is too critical a function to be fully delegated without oversight.

How AI and Automation Are Transforming Service Delivery

Artificial Intelligence (AI)

AI offers faster resolution to many issues through automated responses and can personalize customer interactions. Machine Learning helps improve interactions over time. Some solutions already deployed in the industry include:

• Chatbots: Many banks and companies deploy AI-powered bots to handle queries 24/7, reducing wait times.
• Sentiment Analysis: Tools like IBM Watson assess customer emotions, helping agents adapt their tone.
• Predictive Support: E-commerce platforms like Amazon predict potential delivery issues and proactively notify customers.

Agentic AI — The Next Step

Agentic AI refers to intelligent systems that act independently, learn from experiences, and adapt. Unlike traditional AI, it can handle complex, multi-step processes dynamically. Some of solutions that Agentic AI can deliver are:

• Contextual Awareness: It tracks customer journeys across departments, ensuring smooth transitions.
• Proactive Solutions: Assume your flight is delayed, Agentic AI can then automatically offer passengers alternative bookings.
• Self-Healing Systems: In IT services, AI detects software glitches and fixes them without human intervention.

Robotic Process Automation (RPA)

RPA automates rule-based tasks, reducing manual work and errors. Some of the use cases could be :

• Data Entry: Some banks use RPA to process applications faster.
• Document Verification: Insurance companies use bots to check claim documents.
• Ticket Routing: RPA ensures customer complaints reach the right departments quickly.

Intelligent Automation — Combining AI and RPA

AI and RPA together create Intelligent Automation, revolutionizing customer service. Few examples are :

• Loan Processing: AI assesses risk, while RPA handles paperwork.
• Customer Onboarding: An MNC bank automated this process, reducing processing time by 50%.

A Real-Life Case Study

A leading global coffee chain faced challenges managing in-store and mobile orders. Customers experienced delays, and staff were overwhelmed. The company introduced an AI-driven algorithm to manage order flow and redesigned store layouts to separate mobile pickups. This reduced wait times and improved customer satisfaction.

Future Possibilities

AI and Automation are set to revolutionize customer service delivery. It will change the way we avail services. Most service delivery will be digitally automated and available round the clock. Tasks will increasingly be performed based on prompts. With Agentic AI, customers will simply state their requirements, and the agent will figure out how to serve them. Some emerging areas include:

• Hyper-Personalization: AI can tailor offers and communication to individual customers.
• End-to-end Autonomous Service: Agentic AI could handle an entire travel booking, from flight selection to refunds for delays.
• Human-like Digital Assistants: Virtual agents with human-like expressions and speech (e.g., Samsung Neon) could deliver empathetic support.

Challenges and Risks

While it is greatly promising, AI and Automation pose several risks. Major are

• Workforce Displacement: AI and Automation are going to create large-scale displacement of the existing workforce.
• Over-Automation: Hyper automation may lead customers seeking empathy may feel alienated.
• Lack of Human Touch: Automated systems may lack emotional understanding.
• AI Bias: If trained on biased data, AI could reinforce discrimination and may amplify biases.
• Legacy Systems: Integrating AI can be costly and complex for companies with legacy systems.

The future of service delivery lies in blending human empathy with AI efficiency. Companies that align their departments, empower leaders with insights, apply design thinking principles, standardize processes, personalize interactions, and leverage AI-driven automation will deliver superior customer experiences. Businesses must embrace these technologies while keeping the human element at the core.