CEO Insights India

In today’s rapidly shifting technology landscape, true leadership emerges not from chasing trends but from understanding the deeper principles that shape meaningful innovation. This philosophy has driven the remarkable professional journey of Surendranath Reddy Jillella, Head of AI, QApilot. Over the years he built state of the art AI systems for a wide range of applications spanning across domains – retail, insurance, CPAAS, and financial intelligence.

What makes his journey extraordinary is the unusual foundation on which it was built. Early in his career, he was entrusted with responsibilities beyond the norm for a fresher, encouraged to explore and experiment. This early experience instilled a strong sense of ownership and clear judgment, shaping a leader who approaches every challenge with both technical depth and human insight.

Surendranath took his CS graduate degree form IIT Guwahati and started working with Abzooba in Kolkata. Being part of their machine learning group early in the career, helped him gain practical experience in building ML systems. Supported by strong mentors and a culture of experimentation, he gained the confidence to own products and guide teams long before holding formal leadership roles. This early foundation paved his path to leading impactful AI teams.

Surendranath's mindset found its perfect expression at QApilot, where he now drives an AI-Native Mobile App Testing Platform delivering zero-touch sanity testing through autonomous app exploration. He is advancing the boundaries of AI-Native mobile app testing through innovations such as Bring Your Own Agent (BYOA), enabling teams to integrate their own domain-specific intelligence into QApilot. Under his leadership, QApilot’s AI capabilities are evolving into a flexible, extensible system that adapts to diverse industry workflows and supports deeper, context-aware automation.

We are delighted to engage in an exclusive interview with Surendranath, who takes us through his professional journey and leadership insights.

What challenges and opportunities have you observed in applying AI to software testing, especially compared with other domains you’ve worked in?

Compared to other domains, the key challenge is meeting the high reliability requirement in QE, provided the probabilistic nature of AI. Our focus on mobile app testing adds to this complexity. Mobile testing frameworks haven't kept pace with the rapid growth of mobile apps, and vibe coding only increases the demand for robust testing. Yet this space offers strong opportunities. By entering early, concentrating on mobile, and building proprietary technology, we’ve created a differentiated product.

How have your cross-industry experiences influenced your approach to leading AI engineering teams today?

My leadership style for AI engineering teams is shaped by early mentors and experience across industries. I’ve evolved from applying machine learning everywhere to using it purposefully as a tool to build high-quality products.

In my view, AI is valuable only when it reinforces the product and elevates the user experience.

How do you encourage your team to stay innovative and ahead in a rapidly evolving tech ecosystem?

With AI evolving rapidly, we focus on cutting through the noise and reinforcing fundamentals. I share highquality resources and encourage the team to stay grounded in core ML principles rather than aimlessly riding the GenAI hype. To support our team of young professionals, we bring them exposure to industry through AI events, expert talks, and hackathons, fostering the culture to experiment, remain curious, and keep the innovation going.

Which emerging techno- logies are you most excited about introducing to the market?

Zero-touch sanity testing is one of our most disruptive technologies, bringing a new level of testing

beyond manual, automated, and AI-assisted methods. We achieve this through a network of agents that explores an app like a real user, mapping journeys and identifying what needs to be tested. At the core of this workflow is a knowledge graph that represents the app’s structure and behaviour, enabling agents to make context-aware decisions and scale automation reliably. We are working towards expanding this foundation into a broader, unified framework that connects all testing modes, allowing teams to move seamlessly across approaches without switching tools.

What is the next chapter in your professional journey that you look forward to pursuing?

I aim to build QApilot into a truly AI-native product that delivers real value to customers, not just feature-level AI demonstrations. With the product gaining strong user traction, my focus is on creating something we are genuinely proud of. Additionally, I’m committed to scaling and strengthening our young AI team so we continue operating at the cutting edge of the field with the same level of enthusiasm and execution.

What advice do you have for budding industry leaders?

My advice is to stay curious and take ownership. Knowledge is everywhere, but execution sets you apart. I see this in my own team; the moment a problem is shared, they take initiative to solve it.

Ask questions that lead to solutions, not questions for the sake of asking. And, above all, lead with a people-first mindset.

Surendranath Reddy Jillella, Head of AI, QApilot

Surendranath brings together deep technical ownership and cross-industry experience to build AI-native testing systems that deliver reliable, autonomous mobile app quality at scale.

Hobbies: I’m very active in sports; mainly cricket, hockey, and badminton; and I love watching movies, especially Telugu films.

Favorite book: I prefer books on politics and history

Favorite travel destination: I enjoy mountains the most; especially the Northeast; Sikkim and Arunachal Pradesh.

Favorite cuisine: I enjoy spicy non-vegetarian food the most, especially South Indian cuisine.