Indian enterprises must fix cloud readiness before scaling AI, says Genesys’ Albert Nel

Indian enterprises are gradually shifting their customer experience strategies, with cloud adoption and Artificial Intelligence (AI) playing a growing role. Genesys, a global provider of AI-powered cloud and hybrid contact centre software, is seeing increased interest in tools that improve efficiency and service quality, though most large enterprises still operate on-premise systems. 

In a conversation with TechCircle, Albert Nel, Senior Vice President, Asia Pacific & Japan, discusses the pace of cloud migration, emerging AI use cases, regulatory challenges, and the role of India as both a market and an R&D hub. Edited Excerpts: 

How is customer experience viewed in the Indian boardrooms you’re speaking to? Is it still seen as a cost center, or has that started to change?

Not yet. We're starting to see a slow shift in India, but the adoption of AI is still mostly focused on improving efficiency. The idea of using AI to build customer loyalty is gaining traction globally, and we believe it's possible to achieve both efficiency and loyalty through AI. In India, though, most of the focus remains on efficiency. Some digital-native brands are beginning to explore loyalty-driven use cases, but it's early.

In large enterprises the infrastructure is still largely on-premise. Many of these companies are still deciding whether to move to the cloud. A significant number continue to rely on traditional data centers, infrastructure, and on-premise licences. However, we're seeing increasing openness to cloud migration.

There's a growing recognition that to effectively use AI and realise its efficiency benefits, operating in a cloud environment is necessary. This understanding is beginning to drive more enterprises to shift from on-premise systems to cloud-based infrastructure.

Across Asia Pacific, India remains one of the slowest markets in making this transition to the cloud.

We hear a lot about contact centres becoming experience hubs. What does that shift actually look like in terms of teams, tech, or KPIs?

We run an annual State of Customer Experience survey, and the results continue to show rising customer expectations. If you compare this to five years ago, the typical contact centre interaction was fairly straightforward: a customer would call, explain their issue, provide details, and expect a resolution. Today, customers expect more personalised and informed responses.

We're seeing a shift toward deeper, more context-aware interactions. Despite fewer calls coming directly into contact centres, thanks to chatbots and self-service, the actual volume of meaningful conversations is expected to nearly double over the next three years.

The stakes are high. According to the survey, 30% of customers will leave a brand after just one bad experience. This makes agent training and enablement critical. Agents need to be fully prepared to handle inquiries effectively and deliver the right outcomes.

That’s where co-pilot tools come in. These tools support agents by providing access to knowledge, customer history, and context, helping them deliver accurate and consistent service. We're also seeing similar tools being used by supervisors. AI is now helping supervisors understand and review conversations at scale by capturing and transcribing all interactions, not just a few manually selected ones.

Traditionally, a supervisor might only have time to review one or two calls per day. Now, with AI, they can assess all conversations, identify patterns, and receive recommendations for coaching, training, or process improvements.

A key focus is empathy. Whether through a live agent or a virtual one, showing empathy during interactions is essential. AI tools are being used to evaluate agent performance on empathy and suggest targeted training to improve it.

The broader goal is to make contact centres more efficient while improving the quality of customer experience. This aligns with a wider trend. Many companies, especially publicly listed ones, are now highlighting customer experience as a top strategic priority in their financial reporting. There's growing recognition that better engagement and more personalised service are central to business performance.

How ready are Indian enterprises for cloud and AI beyond the headlines? Are adoption patterns here noticeably different from countries like Japan or Australia?

Australia has typically been an early adopter, and we’re seeing the same pattern in AI and cloud technologies. Australia moved to the cloud about five to seven years ago. Japan, which was slower to adopt, has now made a strong commitment to the cloud. India is still behind, but some of the less regulated industries there are starting to move faster. Digital-native companies in India, including many startups and unicorns, are leading this shift.

In contrast, large enterprises in sectors like banking and insurance are moving more slowly, mainly due to regulatory constraints. We're working with financial institutions and regulators in India to show how cloud adoption can still ensure the protection of customer data. The pace is slower compared to other parts of the Asia-Pacific region, but the intent to shift is becoming clearer.

A key challenge remains the attachment to physical data centres and on-premise licenses. Shifting that mindset toward cloud is happening, but it’s taking more time than in other regions.

What’s one use case, beyond chatbots, that’s actually delivering real value today? And what’s one that still feels more like hype than reality?

Right now, most generative AI tools function as chatbots. That’s the current state. But we’re moving toward agentic AI, something we started with our launch last week, where a virtual agent can learn autonomously. The idea is to evolve from a basic chatbot into a more capable virtual agent, and eventually into a voice-enabled system.

This shift means the system won’t just respond to set scripts or structured inputs. It will be able to communicate intelligently, understand context, and adapt based on specific customer interactions. Unlike today’s chatbots, which are limited and mechanical, agentic AI can adjust in real time, making conversations more natural and responsive.

In customer experience, where empathy is essential, how do you see the balance between AI-led actions and human judgment?

We started last year by setting up an internal ethics board focused on AI. That work has continued, and with the recent launch of AI Studios and AI Guides, you can see how we've built empathy into our large language models. This is central to how we create virtual agents for agentic systems, they’re designed with empathy at their core.

As we shift from a generative model, which simply responds to questions, to an agentic model that learns, improves, and starts making decisions on its own, putting the right guardrails in place is essential. These guardrails are shaped by company policies, operational processes, and regulatory requirements, and they form the foundation of how we've built our virtual agents and agentic capabilities.

This is especially important because we're operating in a service economy. Our role is to deliver customer service, and these AI virtual agents will increasingly become the frontline of customer interaction, and by extension, a representation of your brand. Ensuring they can protect that brand and help build customer trust and loyalty, not just improve efficiency, has been a key focus for us.

With global AI and data privacy regulations tightening, and India introducing the DPDP act, are Indian enterprises being proactive, or are they still reacting to these changes?

It depends on the industry. Some companies are already engaging with us on these topics, and we're seeing more of these conversations come up in discussions with our customers. That's also why we have our own internal AI ethics teams who can get involved when needed.

Our security teams across the region, including specialists in India, are seeing a lot of activity around these issues. We work closely with them to stay aligned with new regulations as they come up. We're also working with customers who want to understand and prepare for the impact of these regulatory changes.  

Is India mainly a customer market for your company, or does it also contribute to product innovation, R&D, or solution design? How are you using the region beyond sales?

India is a key market for Genesys, not just from a go-to-market perspective but also in terms of research and development. It hosts our third-largest R&D centre globally. We recently opened a new office in Chennai, which includes our Asia-Pacific Executive Briefing Centre, our only one in the region. This reflects the level of innovation coming out of India. Our India R&D centre is among the top within Genesys for filing patents and plays a central role in shaping our future innovations. Its role goes well beyond sales; it is a core hub for our R&D efforts.

Looking ahead, what's one major shift in customer experience you think Indian enterprises will go through by next year or by 2027?

I believe next year will mark a significant shift in cloud adoption. Many large enterprises that have held back so far will finally make the move to the cloud. The main driver will be the need to stay competitive by using AI, which increasingly depends on cloud infrastructure. That urgency to remain relevant in a rapidly changing landscape will push them to act.

Looking ahead to 2027, I see a broader and deeper adoption of AI. Initially, this will take the form of generative AI tools designed to support agents and enhance customer interactions. But over time, the focus will expand. Companies will begin using AI in more comprehensive ways to improve operational efficiency and build customer loyalty. By 2027, the role of AI will shift from being a support tool to becoming a core part of how businesses operate and grow.