Beyond Automation: Harnessing Agentic and Voice AI for Seamless Customer Journeys

Agentic AI and next-gen Voice AI are transforming customer experience, closing long-standing visibility gaps and empowering human agents with richer context than ever

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A 3D robotic head with glowing headphones hovers above a smartphone displaying a blue voice-waveform graphic. Colourful chat bubbles float around the device, symbolising AI-driven conversations. The Tata Communications logo appears on the right against a blue background
Contact Center & Omnichannel​Interview

Published: December 1, 2025

Christopher Carey

As customer expectations continue to rise across digital channels, businesses are under growing pressure to deliver seamless, context-rich and proactive experiences.  

Yet many organisations still rely on traditional automation systems that struggle to meet these demands.  

Rigid IVR flows, generic chatbot scripts and siloed customer data often create more frustration than value, leaving customers repeating themselves and brands losing control of the customer journey. 

According to Gaurav Anand, VP and Head of Customer Interaction Suite at Tata Communications, many companies suffer from what he calls the “customer journey black hole” – a gap where context and customer history fall through the cracks, resulting in broken experiences and unnecessary friction. 

“Think about a typical banking interaction,” Anand says.  

“A customer fills in a loan application online, then calls the contact centre for support, only to be asked to provide the same information again. It’s no surprise that customers become frustrated.  

The consequence isn’t just dissatisfaction – 92 percent of customers say they’ll leave a brand after two or more poor experiences.

The Limits of Traditional Automation 

Even as businesses invest in automation to manage scale, traditional systems are increasingly showing their age.  

Script-based chatbots struggle to interpret nuanced intent.  

IVR systems force customers into predefined paths that rarely reflect what they actually want.  

And behind the scenes, data remains fragmented across CRM systems, ticketing platforms, and communication channels. 

“Legacy automation solves tasks, not outcomes,” Anand explains. “It might complete a form or look up an account, but it doesn’t understand the end goal of the interaction. It doesn’t collaborate with other systems.  

“It doesn’t adapt when the customer deviates from the script. Ultimately, it can’t orchestrate a full journey.” 

As customer journeys become more complex and decentralised, these limitations are becoming untenable.  

Organisations are now looking for a more intelligent and adaptive approach that can engage customers in real time, maintain continuity, and drive tangible results. 

Agentic AI in Action 

This is where agentic AI comes into play.  

Unlike traditional automation, agentic AI is built around autonomous, outcome-driven agents that can reason, collaborate and take contextual decisions.  

These agents can be trained for specific use cases such as cart abandonment recovery, KYC completion, proactive service notifications or multi-step issue resolution. This helps brands transition from basic automation to autonomous actions and AI decisioning.  

“Agentic AI is purpose-built,” Anand says. “Each agent understands the goal it needs to achieve, but it also knows how to work with other agents throughout the journey.  

“So you may have one agent focused on customer onboarding, another handling verification, and another coordinating follow-ups – all sharing context in the background.” 

This type of orchestration is increasingly essential for large enterprises. In e-commerce, for example, an agentic AI flow can detect a customer abandoning a cart, trigger hyper-personalised reminders across SMS, WhatsApp or email, and follow up based on engagement. If the customer expresses confusion or dissatisfaction, the agent can switch channels or escalate to a human agent with full context. 

“You’re no longer relying on one-size-fits-all automation,” Anand adds.  

You’re creating a dynamic loop that adapts to each customer’s needs and behaviours.

Voice AI: Transforming Real-Time Interactions 

The rise of voice AI is taking things a step further.  

Advanced speech-to-speech models now enable natural, human-like interactions that go far beyond traditional voice bots.  

These systems can understand real intent, detect emotion, and respond conversationally – making voice channels significantly more efficient and engaging. 

“For many customers, voice is still the channel of choice,” Anand notes.  

“But the experience has often been painful because legacy IVR is so restrictive. With voice AI, customers can speak normally and get real-time problem solving without navigating menus or waiting for an agent.” 

Tata Communications is seeing growing demand for voice AI in sectors such as banking, utilities, retail and travel, where customers frequently need rapid support with complex queries.  

When combined with agentic AI, voice agents can collaborate with other AI systems, retrieve information, complete tasks and escalate with full context when human support is required. 

“The beauty of voice AI is that it doesn’t break the flow,” Anand says. “If an escalation is needed, the human agent gets the full transcript, sentiment analysis and journey history. The customer never has to start again.” 

A Unified Approach 

Tata Communications has integrated these capabilities into a unified platform that connects multiple AI agents, voice systems and human support teams through powerful APIs and data connectors.  

The goal is to create a single interaction fabric that ensures continuity across every channel. 

“When an AI agent hands over to a human, or vice versa, all context is preserved,” Anand explains.  

“This is critical. If customers have to repeat themselves, the customer feels unheard and the journey becomes painful. Our platform eliminates that friction by ensuring that every agent – human or AI – understands the full picture.” 

The company has already seen strong results.  

One electric vehicle brand achieved a 25 percent increase in customer follow-through after deploying agentic AI-driven outreach.  

A large e-commerce marketplace reduced return-to-origin orders by 45 percent following the introduction of AI-powered WhatsApp workflows. 

“These are not incremental improvements,” Anand highlights. “They are major operational gains driven by intelligent automation that understands the customer’s intent.” 

Human-First, Outcome-Driven CX 

Despite the advances in AI, Anand emphasises that human expertise remains essential.  

Tata Communications’ approach is intentionally hybrid – using AI to handle repetitive tasks, streamline journeys and provide real-time insights, but ensuring humans remain central to complex, high-empathy interactions. 

“The best CX strategy is human-first,” he says. “AI should enhance human capability, not replace it. When AI and humans collaborate, you deliver outcomes that are personalised, proactive and genuinely valuable. That’s the future of customer experience.” 

As enterprises look to modernise their digital engagement, agentic AI and voice AI are emerging as critical technologies that can close the customer journey black hole and deliver the seamless, context-aware experiences customers expect. 


To explore how your organization can overcome the customer journey black hole and create seamless, unified experiences, contact Tata Communications to learn more about their integrated CX platform capabilities.   

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