In an exclusive interaction with Express Computer, Jai Prakash, EVP Technology, Info Edge, offers a deep dive into how the company is reimagining technology as a core driver of business growth in a digital-first world. At a time when enterprises are moving beyond traditional IT metrics, Info Edge is building a culture where experimentation is not just encouraged, but rigorously tied to measurable outcomes—from customer acquisition and engagement to platform reliability and scale.
He also highlights how the company is architecting for the future with a modular, API-driven ecosystem designed for agility and resilience, while simultaneously embedding AI and analytics into the very fabric of decision-making. More importantly, it marks a clear shift in the mindset, where technology teams are no longer measured by delivery alone, but by the tangible business impact they create. The result is a transformation where technology becomes almost invisible, yet indispensable—quietly powering innovation, enhancing user experience, and enabling the business to scale faster and smarter.
How are you building a technology culture within Info Edge that fosters continuous innovation while aligning closely with business outcomes?
At Info Edge, we believe culture isn’t declared—it’s designed and reinforced daily. We’ve built an environment where experimentation is encouraged, but always anchored to business outcomes.
We follow a simple principle: fail fast, learn faster—but never fail without a hypothesis. Every experiment is tied to measurable impact—be it conversion uplift, latency reduction, or improved user engagement.
At the same time, we’ve aligned technology KPIs with business metrics—so engineering isn’t just shipping code, it’s directly influencing business metrics, customer experience, and platform reliability, and all at scale. When developers start talking in terms of customer acquisition cost, retention, availability, and uptime—not just APIs and deployments—you know the culture is evolving in the right direction.
That’s when you know technology is no longer a support function—it’s a growth engine.
As a digital-first organisation, how is Info Edge reimagining its technology architecture to stay ahead of evolving user expectations and platform disruption?
In a digital-first business, static architecture is a liability. We’ve always believed and actively adopted a modular, hybrid, and API-driven ecosystem that allows us to adapt quickly to changing user behaviours and market dynamics.
The focus is on composability and resilience—breaking down monoliths into scalable services, containerisation, investing in observability, and ensuring we can deploy, rollback, and scale without disruption.
At the same time, we’re designing for experience, not just infrastructure. Whether it’s mobile-first interactions, real-time responsiveness, or seamless integrations, the architecture is increasingly shaped by how users behave—not just how systems were traditionally designed.
In simple terms, we’re building systems that don’t just work well today but are ready to evolve tomorrow without a major rewrite quarter-on-quarter. We’re building systems that can evolve, adapt, and scale without friction.
How is Info Edge leveraging AI/ML and analytics to drive personalisation and decision intelligence?
AI/ML for us is not a buzzword layer—it’s becoming part of the decision fabric of the organisation, and clearly, customers are experiencing the available services online.
We’re leveraging it across three key areas:
Personalisation: Delivering more relevant content, recommendations, and matches to users based on behaviour and context.
Decision intelligence: Enabling business teams with predictive insights rather than retrospective dashboards to make their decisions more accurate.
Operational efficiency: Automating repetitive processes and improving system reliability through anomaly detection.
The goal is to move from “data-informed” to “data-driven and increasingly data-autonomous.” And of course, we’re mindful that AI is only as good as the data and governance behind it—so equal emphasis goes into data quality, privacy, protection of data, and its ethical usage.
Digital transformation often comes with significant investments—how does Info Edge measure the real business impact of its IT initiatives, and what metrics truly define success at the leadership level?
We’ve moved beyond measuring IT success through traditional metrics like uptime or delivery timelines—those are expected and business as usual, not differentiators. Today, we look at impact across three layers:
Business outcomes: Business uplift, conversion rates, customer acquisition, and retention.
User experience: Availability, latency, engagement, net promoter score, and overall journey friction.
Operational efficiency: Cost optimisation, automation levels, service availability, and system scalability.
Every major initiative is tied to a clear value hypothesis upfront, and we track it post-implementation to see whether it delivered as expected—or taught us something useful. At the leadership level, success is when technology becomes invisible but indispensable—it just works, scales with the business, and quietly drives growth without needing constant firefighting.
Or put simply: if the business grows faster and smoother because of tech, we’re doing our job right. If the business scales faster and more smoothly because of technology, then we know we’re on the right track.