Venki Subramanian: What defines success in AI-powered CX

It’s harder than you think to make software easy to use. That's a mission that Venki Subramanian has embraced for years—and now brings to his new role as Freshworks’ senior vice president of product management for CX. 

Subramanian brings more than two decades of experience as a product leader in enterprise software. In addition to achievements at SAP and Reltio, he led product management for ServiceNow’s Customer Service Management, which evolved into a CRM suite and grew to be a market leader in just four years.

“I love finding problems worth solving, building solutions that can solve these problems, and delivering value consistently and repeatedly,” Subramanian says. One of those challenges is figuring out how to deliver superior customer experience that brings the best of both people and AI. In a recent interview, Subramanian explained his methodology for making good on that promise. 

How can AI improve customer experience while maintaining the human touch?

AI isn’t just about technological advancements—it’s about making technology accessible and solving real problems. A great example is OpenAI’s recent “Operator” demo, where an AI agent can handle a shopping list for Instacart with minimal effort from the user.

In customer service, sales, and marketing, employees spend a lot of time on repetitive tasks. AI can take over those tasks, allowing humans to focus on more complex, purpose-driven work. [See our 2024 global workplace AI report.] The key is ensuring that AI operates with human supervision where needed—what I’d call responsible AI. It’s about delivering tangible value while keeping human connections intact.

What other big trends with CX and AI are you paying the most attention to?

The biggest trend over the past 18 months has been generative AI, which is evolving at an incredible pace. AI isn’t new—think about predictive text or spell correction—but recent advancements have unlocked new levels of capability. One of the most exciting developments is the shift from structured, database-driven applications to AI agents that can think and take action.

However, with great power comes responsibility. AI-driven applications bring productivity gains, but they also raise concerns about jobs and data security. Governance is critical—we can’t let AI run unchecked and risk catastrophic consequences. Companies need to balance innovation with strong data protection and ethical oversight.

What are some key essentials for companies looking to expand their AI capabilities?

I’ve always said that data is the foundation of great customer experience. I’ve worked in CX for over a decade, and time and again, I’ve seen companies struggle with AI and automation because of poor data quality—incomplete or incorrect data. Companies cannot deliver a great customer experience if they do not have a 360-degree view of their customers.

For AI to succeed, organizations must treat data as a first-class citizen. That means ensuring high data quality, implementing governance structures, and protecting sensitive information—especially in regulated industries like healthcare and finance. Without strong data foundations, companies expose themselves to regulatory risks and fail to deliver meaningful AI-driven outcomes.

Aside from having great technology, what else do companies need to win with CX?  

The most successful companies start with a clear strategy. AI is a tool, not the end goal. The best organizations define the customer experience they want to create, invest in the right technology to support that vision, and build teams that align with their strategic goals.

Another common trait among successful companies is their willingness to take calculated risks. Innovation requires experimentation. The companies leading the way in AI-powered CX—whether in retail, hospitality, or finance—are the ones that lean forward, test new technologies, and learn from both successes and failures.

Even successful companies fall into traps with technology. What’s the biggest one you see when it comes to AI?  

The biggest challenge is becoming too inward-focused. As organizations grow, they tend to get comfortable with existing processes rather than staying laser-focused on customer needs. That often leads to risk aversion. Successful companies continuously ask, “Who are we serving? What problems are we solving?”

You have to fall in love with the problem, not the solution. That mindset is critical. Companies that stay obsessed with solving real customer pain points will always be ahead of the curve.