Vasudeva Rao Munnaluri on GenAI & CX Innovation to Revolutionize Customer Experience

Vasudeva Rao Munnaluri, RVP India & SAARC, Zendesk, share insights on how generative AI transforms the customer experience in this insightful DataQuest interview.

Punam Singh
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Vasudeva Rao Munnaluri, RVP India & SAARC at Zendesk,

Vasudeva Rao Munnaluri, RVP India & SAARC at Zendesk

In an era where customer expectations are continually evolving, businesses must leverage advanced technologies to meet and exceed these demands. Vasudeva Rao Munnaluri, RVP India & SAARC at Zendesk, offers insights into how generative AI is revolutionizing customer experience (CX). 


In this interview with DataQuest, Munnaluri discusses the pivotal role of generative AI in personalizing customer interactions, the importance of ethical AI adoption, strategies for balancing AI and human agents, effective training for human-AI collaboration, and the valuable lessons CX leaders can glean from AI integration.


DQ: How can generative AI meet customer expectations for personalized, efficient interactions?


Vasudeva Rao: Generative AI’s capabilities mean that it can act like a personalized concierge for every customer, understanding their history and preferences, and allowing agents to better understand their needs. Generative AI-powered insights help companies deliver personalized conversational service at scale. Instead of replacing human interaction, AI acts as a support tool, providing agents with the context needed to deliver efficient and hyper-personalized customer experiences to every customer.

Generative AI can use data—like order history, behaviors, and preferences—to anticipate customer needs and identify potential problems. This allows businesses to generate proactive solutions and improve customer retention. Teams can also track and analyze unstructured data—like customer sentiment—to see which customers are at high churn risk and immediately give them attention. Generative AI algorithms use predictive analytics with natural language processing (NLP) to look at thousands of different keywords from customer interactions. It provides quick recommendations and automatic alerts to help you monitor and analyze customer sentiments to predict case escalation or customer churn. 

DQ: What role does ethical AI adoption play in creating a transparent human-automation strategy?


Vasudeva Rao: It is important for businesses to be upfront about how the AI works, what data it collects, and how that data is used. Such transparency is necessary to build trust in the technology. When it comes to AI in customer service, communications must be direct, clear, and honest. Not all AI predictions are the same in regard to quality. Sometimes models have high confidence in doing a particular task, while in other scenarios, the confidence is low. By making the quality of AI predictions available to customers, they can take that into account and act accordingly, while building trust in the technology.

Traditional quality assurance in CX often relies on human evaluation. However AI-powered quality assurance can objectively score agent performance, identify customer sentiment, and pinpoint areas where real-time coaching is needed based on data gathered from customer interactions. This allows businesses to identify trends, proactively address issues, and personalize training for agents to ensure they deliver exceptional customer experiences consistently.

DQ: How can businesses strike a balance between AI and human agents in customer support?


Vasudeva Rao: When businesses think about adopting generative AI, it doesn’t mean that traditional channels of communication like voice or email are eliminated entirely. The right strategy is to assess which areas of the customer experience can benefit from the use of generative AI and integrate the technology into existing systems. We think about AI being in service of humans as opposed to replacing them in the value chain of the customer experience.

Generative AI tools enhance agent efficiency and productivity by simplifying workflows, with AI-powered chatbots handling requests and automated processes tackling repetitive tasks. These tools reduce agents’ workload, allowing them to focus on high-value tasks and complex customer issues. 

Intelligent and skill-based routing of customer queries is another strategy to deploy generative AI, striking a balance between AI and human agents. Skills-based routing optimizes customer service by directing tickets to agents based on their expertise, availability, conversation priority, and more. When AI is used as an assistant to help humans, everyone wins. Customers get personalized service, and agents aren’t bogged down by repetitive tasks, ensuring the customer experience is quick and agile. 


DQ: How can training human agents to collaborate effectively with AI enhance overall customer service?

Vasudeva Rao: With every early access program, like generative AI adoption, companies must meet certain accuracy thresholds before they leverage it for customer service. When it comes to AI, the accuracy that must be met—be it high, medium, or low—largely depends on the task or model being tested. Every AI prediction must come with an associated confidence score that is passed to the administrator or agent, so any workflow built on top of AI can take that into account. 

For example, high-confidence predictions can lead to fully automated tasks, whereas those with less confident scores would require a human to be kept in the loop for a better experience for both the agent and customer. Additionally, if the technology is easy to use and can be set up in minutes, it improves productivity, ensuring better synergy between AI and human agents.  

DQ: What lessons can CX leaders learn from the adoption of AI in customer experience?

Vasudeva Rao: By 2025, most customer conversations are expected to be automated, as customers are curious about AI and expect brands to adopt it to deliver better experiences. In India, 82% of customers believe chatbots should have the same level of expertise and quality as highly skilled human agents. CX leaders can learn from those who have already deployed generative AI for better CX—91% of CX leaders who are already using generative AI in India report high ROI. This is because AI improves efficiency and productivity by eliminating the mundane, repetitive tasks human agents perform every day. It anticipates customer sentiment and empowers proactive customer service. With low-value tasks being automated, CX leaders can bring down operational costs. With generative AI, businesses can create a chatbot persona that matches their brand identity, helping them maintain a consistent tone and personality across all customer interactions. It makes the brand stand out, enhancing the brand image and increasing customer satisfaction.