In the media industry, audiences provide an assessment with every scroll, click, or skip. Technology can no longer play a backup role; instead, it has to influence content, experience, and revenue in the present moment.
In an interaction with CIONOW, Ninad Raje, Group CIO, Times Group, provides insights into how dashboards do not make the cut, how one can leverage core-robust systems and high-speed innovation together, and also about the road ahead over 12-18 months on quantum, AI agents, and fake news combats.
You have led tech transformation across manufacturing, BFSI, healthcare and media. What’s fundamentally different about transforming a media business?
In most industries, if you make a decision today, you can review the results tomorrow or at least in a couple of days. In the media industry, by the time you finish discussing the decision, the audience has already moved on.
In sectors like manufacturing or insurance, transformation is often about optimizing a relatively predictable operating model. In media, the operating model itself is constantly being rewritten by consumer and audience behavior. The audience decides what’s relevant, on which device, in what format, and increasingly, in which language. Technology can’t sit backstage anymore; it has to be on stage with the business.
Data tells us what audiences are consuming. AI helps us understand patterns and predict intent. Digital transformation allows us to respond at scale. The real shift is from content‑centric thinking to audience‑centric intelligence, and that changes the CIO’s role dramatically. I no longer just ask, “Is the system available?” I ask, “Can the organization understand the audience quickly enough, create the right experience, and monitor that engagement?” Because in media, your audience doesn’t give you a quarterly performance review, they give you one every time they scroll, click, skip, or switch.
Large media houses can’t afford downtime, yet they must innovate fast. How do you balance stability and speed?
I have always believed: the core should be boring; the edge should be exciting. ERPs, finance, HR, cybersecurity, identity networks, and critical production systems must be so resilient that nobody calls the CIO to say “everything is working.” They should call only when something isn’t. That reliability creates the foundation on which you can safely experiment with cloud, APIs, AI agents, automation, modern data platforms, and new digital products.
The mistake many organizations make is treating innovation and stability as opposing forces. They are two sides of the same transformation strategy. I wouldn’t tell a business, “Let’s stop the engine and redesign the car.” Instead, keep the existing engine running reliably while you build the next‑generation engine alongside it using controlled experimentation, sandboxing, APIs, DevSecOps, and very strong governance. In the media industry, speed cannot come at the cost of resilience. If your digital platform crashes during the biggest breaking news of the year, no amount of innovation will make the audience wait. My philosophy is therefore, protect the core, modernize the foundation, and create a high‑speed innovation layer on top.
Times Group spans print, digital, TV, radio. Data volumes are huge. How do you turn that into real‑time decisions that improve both audience experience and revenue?
The biggest challenge isn’t collecting data; we are exceptionally good at that. The challenge is creating trusted, connected, and contextual data. Data by itself means nothing. It has to be trusted, connected, reliable, and contextual so that a business leader can move from “what happened” to “why did it happen,” then “what will happen next,” and most importantly, “what should we do about it?”
Imagine connecting content consumption, search behavior, engagement, subscriber behavior, advertising response, and audience preferences, instead of looking at each dataset independently. Suddenly, the same data ecosystem helps editorial teams understand what audiences are interested in, helps product teams improve digital experience, and helps advertising teams create more relevant propositions.
The shift we need is from dashboards to decision intelligence. Dashboards are passé. We don’t need another 47‑slide dashboard that nobody opens after the first Monday. We need intelligent systems that tell the business: “This audience segment is losing engagement; this content category is trending; this campaign is underperforming—and here’s the action we recommend.” India has no shortage of data; the competitive advantage is who can turn that data into better decisions, faster.
How do you see the role of the CIO changing, especially across the industries you have worked in?
The role of the CIO has changed a lot. I still recollect when this portfolio was called EDP (Electronic Data Processing). Then it became IT (Information Technology) then just “technology,” then “tech and engineering.” Now we’re in the age of automation, AI, Gen AI, robotics and more.
Portfolios have evolved too. Alongside CIO and CTO, we now see Chief AI Officer and Chief Digital Officer. The function has moved from being a support role to an enabler, and now to a driver.
CIOs now wear multiple hats: platforms, cloud, infrastructure, security, and most importantly, automation. Boards are asking about automation: “How do we implement AI, and what results can we expect quickly?” That pressure has redefined the role. I would put it this way: CIOs are still called Chief Information Officers, but today they are largely Chief Intelligent Officers. Intelligence is the game, and that’s where data science and AI come in. Combine data science with AI, and you get the new, changed role of the CIO.
Which tech trends will have the most impact on enterprises in the next 12 to 18 months?
Everyone is talking about AI, but the real technology that will make a difference in the near future is quantum. In layman’s terms: if AI can do something in a minute, quantum can do the same thing in a fraction of a second. I recently had the opportunity to be part of a quantum project for the industry, and the technology is mind‑boggling, so fast‑paced and powerful.
Of course, this puts enormous pressure on infrastructure. If AI is a power guzzler, quantum will be an even bigger power guzzler. But the benefits are huge, especially in healthcare, data analysis, and future prediction based on data. We are moving from prescriptive understanding to predictive understanding. That’s where the technology is heading.
Alongside quantum, with increasing digitization, we cannot ignore cybersecurity. These two, quantum and cyber, will be pillars of the future. And as we improve technology, data will also get cleaned, contextualized, more relevant and more updated. The future of tech is this combination: data, quantum, AI, and cybersecurity.
What are you working on these days? What’s on your short‑term and long‑term priority list for Times Group?
Every organization and tech leader should have a short‑term, mid‑term and long‑term plan.
Short term: Fast‑tracking consolidation of data, making it relevant, controlled and safeguarded. With the DPDP Act now live, this is immediate and non‑negotiable. We need to get this implemented and executed quickly.
Mid term: Doubling down on AI agents. This is where automation kicks in, productivity goes up, and efficiency improves.
Long term: Combining the power of AI agents with editorial content and contextual data so that processing happens in a fraction of a second with minimal human intervention. That demands deep automation. We are already working on robotic AI agents to ensure work that used to take days gets done in seconds.
Another major focus is automation of broadcast technology. Broadcast tech is completely different from “normal” IT. It involves satellites, satellite uplinks, and runs live 24×7 news and movie channels. We are working to automate news generation end‑to‑end.
Very close to our heart is the fight against fake news. We are expeditiously working on an anti‑fake news capability, covering fake news and deepfakes, so that nothing gets published without verification. Imagine publishing fake news unintentionally; it would be a disaster. Today, news isn’t just in print; it flashes across the globe in seconds. Our goal is to have automation identify and block fake or deepfake content before it goes live.
You have worked across media, manufacturing, healthcare, insurance and BFSI. What’s one leadership principle that has remained constant, and one that must change with context?
The principle that has remained constant throughout my career is simple: technology transformation is ultimately people transformation. Boards often say, “This is technology, you get it done.” My philosophy is different: if people don’t understand why the change matters, or don’t believe they can succeed in the new environment, even the most sophisticated ERP, cloud, AI, automation, or data platform becomes like expensive furniture—impressive, but underused.
What changes is the definition of speed, risk, and value, depending on the industry. In BFSI, trust, compliance, and financial risk are paramount. In healthcare, reliability and human impact are critical. In manufacturing, operational continuity and efficiency dominate. In media, speed, experimentation, content relevance, and audience engagement become incredibly important.
That’s why I don’t believe in copying another company’s digital transformation blueprint. I have worked across different companies and industries, and at no point have I adopted the same technology blueprint from a previous organization or sector. Technology may be transferable, but the transformation strategy must be native to the business you’re in. You can reuse technology, but you can’t copy transformation strategy.
After almost 30 years across several industries, my biggest learning is this: technology is the common language, but every industry has a different accent.
