95% of IT leaders in India see data streaming platforms as the key to simplifying AI adoption: Rubal Sahni, Confluent

As Indian enterprises race to scale AI, real-time data has emerged as the game changer. In this interaction, Rubal Sahni, AVP India and Emerging Markets, Confluent, explains why data streaming is at the heart of AI success. From powering 5x ROI to enabling localised GenAI models, Sahni unpacks how Indian firms are using streaming to drive speed, accuracy, and innovation at scale.

How are data streaming platforms simplifying AI adoption for Indian enterprises?

The fundamental challenge most enterprises face with AI isn’t the algorithms, it’s the data infrastructure. What we are seeing in India is that 95% of IT leaders see data streaming platforms as easing AI adoption by tackling the core challenges of data access, quality, and governance head-on.

AI systems need live, contextual data to deliver meaningful outcomes. Traditional batch processing creates lag, which means decisions are made on outdated snapshots. Streaming data eliminates that lag. It provides a real-time, always-on data flow that keeps AI systems relevant, timely, and accurate.

But it goes deeper. Our report shows data streaming platforms tackle the three core data challenges that concern AI projects: continuous access of data, superior quality, and governance or audit to understand authenticity of the data. With streaming, you are feeding your AI with fresh clean, trustworthy data that has proper measures right from the source. That’s why 91% of leaders say they will be happy to use Data Streaming Platform (DSP) more to feed their AI systems with real-time, contextual data.

One standout stat was the 5x ROI some organisations are seeing. What’s behind that level of return, is it speed, automation, better decision-making, or something else entirely?

The 5x ROI comes from multiple value drivers working in tandem. Speed is definitely an important part of this process. I do see that 89% of Indian organisations report faster product deployments. It’s more about how data streaming creates systemic improvements across the organisation.

Because of the speed, it creates a decision-making advantage for businesses. With real-time data streaming, decisions are based on current conditions rather than historical snapshots. Product recommendations become more relevant, fraud detection becomes more accurate, inventory management becomes more precise. The cumulative impact is that every business process becomes more intelligent and responsive.

Then there is the operational flexibility. These systems can scale resources up when demand spikes and scale down during quieter periods, which translates to increased customer satisfaction along with efficiency and cost savings for the organisation. And this can be seen with 86% of organisations reporting improved customer experiences.

Shift left adds another layer of value. 81% of IT leaders are seeing cost and risk reductions by embedding data quality and governance early in the pipeline. This means fewer downstream fixes, bugs, less rework, and more reliable systems.

It’s the combination of speed, better decisions, operational flexibility, and reduced technical debt that creates those exceptional ROI numbers.

How does data streaming help improve product innovation and time-to-market in tangible ways?

Streaming unlocks continuous iteration. Instead of waiting for end-of-day or weekly reports to analyse product usage, you’re getting a live feedback loop from the moment a user interacts with your system. This real-time visibility enables product and engineering teams to make immediate, informed adjustments.

The report shows 95% of Indian organisations are seeing improved product and service innovation as a result. That’s because they’re no longer building in isolation, they’re building in response to live signals from customers, operations, and internal systems.

This creates a culture of agility where innovation becomes a habit, not a milestone. You test, you learn, you iterate, all without waiting.

With AI, cloud, and real-time analytics converging in 2025, what should enterprise leaders prioritise when building their data stack?

My recommendation is to design with streaming in mind from day one. Assume that data will need to move continuously, not in batches. That mindset shift will help you architect systems that are responsive, scalable, and AI-ready.

This doesn’t mean replacing your entire infrastructure overnight. It means layering in streaming capabilities strategically, so you modernise without disruption.

For AI to be effective, especially in customer-facing or mission-critical contexts, it needs real-time, contextual data. That requires infrastructure that moves at the speed of business, and that’s what DSPs deliver.

Also, choose cloud platforms that offer cross-environment flexibility. Your data strategy shouldn’t be confined to one cloud or region. You want a unified data fabric that supports diverse workloads and future growth.

And let’s not forget the human element. Invest in your people. Streaming isn’t just a tool, it’s a mindset. The organisations that scale streaming successfully are the ones that invest in upskilling teams and embedding data thinking into every function.

What trends do you see shaping the future of real-time data streaming and its convergence with GenAI?

India is moving from experimentation to execution. We are seeing companies treat data streaming as a strategic muscle, one that helps them act faster, build smarter, and adapt in real time.

One major trend is the localisation of AI. India is embracing tech sovereignty, from building its own GenAI models to training on indigenous datasets. For these models to work effectively in India’s multilingual, culturally diverse context, they need continuous access to local, real-time data. Streaming provides that foundation, both for training and inference at scale.

Additionally, India’s demographic advantage is creating unique opportunities for AI applications that understand local context. Whether it’s fintech, food delivery, or citizen services, the sheer volume and diversity of data flowing through Indian systems requires streaming architectures that can feed AI models with fresh, culturally relevant information.

Lastly, the convergence of streaming and GenAI is not just about smarter products, it’s about nation-scale innovation. The 96% of Indian IT leaders increasing DSP investments in 2025 are laying the groundwork for AI systems that are not just cutting-edge, but inclusive, relevant, and built for India’s future.