1. By Vivek Ganesh, Regional Vice President, OutSystems India
On National AI Day, I believe that the winners will be those who build intelligent agentic systems thoughtfully and with intention over speed. AI is making enterprise software more complex before making it simpler. I have noticed everyone is over-indexing on the build phase like how fast we can generate code, how fast can we ship an agent, while quietly creating bottlenecks downstream in quality control, security, and maintenance. That’s not a prediction; this is a pattern we are already witnessing across businesses. The focus for the coming year should not just be about building faster and coming up with new frameworks and systems, but also about governing what we have already built. All of which includes the core software, the foundational systems, and the mission-critical applications that enterprises run on. Enterprises that understand this will be able to navigate and monitor smarter with the help of governed agents.
2. Anand (Jude) Kannabiran, Vice President, Asia at Delinea
As we mark National AI Day, it’s worth acknowledging that India is one of the most enthusiastic adopters of agentic AI in the world, and honestly, that doesn’t surprise me. I see this enthusiasm in nearly every boardroom conversation that happens. But research shows that 63% Indian organizations are also accepting more identity risk to fuel AI adoption than almost any other country. The gap between confidence and governance reality is widest here, and that is precisely where attackers will look to gain a foothold. What customers need to keep in mind is that speed without visibility isn’t progress, it’s exposure. Successful organisations will treat identity governance as the foundation that makes sustainable innovation possible. That’s the shift we need to see in the next twelve months and the early adopters will set the pace for everyone else.
3. Marshal Correia, General Manager for India & South Asia, SUSE
This National AI Day arrives at an interesting time, especially given the recent Fable 5 shutdown, which caused a tidal wave of impact across Indian enterprises all the way to boardroom level. It also raises an urgent and fundamental question: beyond adoption metrics and innovation ROI, who is actually controlling the infrastructure enterprises are building on?
Recent developments have brought to light an urgent realization and risk factor. A regulatory decision made elsewhere should not have the power to switch off an organization’s AI operations overnight, with no prior notice. This is clearly not a tenable situation, and it’s precisely why digital sovereignty is crucial. Research shows that 62% of Indian organizations are already investing in sovereign technology initiatives, well above the global average. At the same time, organizations should be architecting on open source, so they retain control over how, and where, their applications run. Digital sovereignty means full visibility over how their data is governed, and agility to innovate on their own terms. This freedom of choice is both a hedge against geopolitical risk, and a stronger foundation for long-term resilience.
4. Ish Thukral, Country Head, India & SAARC, Neo4j
As we celebrate Artificial Intelligence Appreciation Day, it’s clear that the conversation has shifted from building larger AI models to building smarter AI systems. The real differentiator today is not just the model itself, but the quality of the context it can access. That’s where the knowledge layer becomes critical.
A context-rich knowledge graph provides AI with the relationships, meaning, and business insights that traditional data architectures often miss. By connecting structured and unstructured enterprise data into a unified knowledge layer, organizations can significantly improve the accuracy, explainability, and trustworthiness of AI applications while reducing hallucinations and enabling more informed decision-making.
Knowledge graphs are becoming the foundation that enables organizations to build intelligent, reliable, and enterprise-ready AI.
5. Terry Maiolo, Vice President & General Manager, Asia Pacific, OVHcloud
AI in India and Asia Pacific has moved quickly from pilot to production and enterprises are beginning to ask the harder questions. They want to know where their data sits, who has access to it, and whether the infrastructure underneath stays open and in their control. That’s sovereignty, and sovereignty starts with ownership. We build our own servers, run our own data centres, including one in Mumbai, and by law, we never share customer data with any government or use it beyond what the customer needs. This is the thinking behind how we have approached AI more broadly, from GPU infrastructure to workspaces like OVHai that let enterprises build and deploy AI without giving up control of their data. With India’s data protection framework taking shape, such ownership is what enterprises are actively looking for. On AI Appreciation Day, we believe the best way to mark this technology’s progress is to keep building AI on foundations that are open, accountable and in the customer’s hands.
6. Satyam Santosh, Startup Program Lead, APAC, OVHcloud
One mistake we see repeatedly is founders treating early cloud credits as a long-term infrastructure plan. While credits can help a startup move from idea to product, they run out and what happens after determines whether the company can actually scale. Across India, founders are building in agentic AI and copilots, and demand for high-performance compute keeps growing with them. Availability of GPUs is only part of the picture. Founders need the right infrastructure at the right time, with optimum pricing and no hidden costs. We built our Startup Program around that principle, giving founders in India access to open infrastructure with predictable prices early, without the guesswork that usually comes later.”
7. By Prof Prakash Gopalan, President, NIIT University
We are past the point of debating whether AI belongs in education. The real conversation now is about how universities can prepare students to build, deploy and apply AI to solve real-world problems. In an AI-driven world, the advantage no longer goes to those who memorise the most information. It goes to those who can learn quickly, unlearn old habits, and adapt just as fast.
Students need to move from just learning about AI to building with it, because that’s the hands-on experience employers are asking for now, not just familiarity with the tools. The more companies want graduates who can train, fine-tune and deploy AI models, work with enterprise-grade infrastructure and build solutions that solve real business problems. That is the skill universities now need to teach directly, not leave to chance.
For universities this means going beyond traditional classroom instruction and creating environments where students can experiment, collaborate and innovate using the same technologies that power modern enterprises. Students get hands-on experience long before they enter the workforce with access to enterprise-grade GPU infrastructure, industry-standard AI tools and real-world projects.
At NIIT University, we are building on this by embedding AI across the learning journey, training faculty to guide its use responsibly, and exploring AI-based tools, including regional-language support, to make learning more accessible. With our recently launched AI Centre of Excellence, powered by NVIDIA technologies, students have hands-on access to enterprise-grade GPU computing and AI development tools, allowing them to build, train, fine-tune and deploy AI models in a secure, high-performance environment from the first year of their academic journey.
We have seen this play out on our own campus too, our recent 24-hour hackathon brought together over a hundred students working in teams to build AI-based solutions, not just study them in a classroom. These experiences inspire students to think critically, solve real-world problems and build confidence to turn ideas into deployable AI solutions.
We at NIIT University (NU) believe, AI literacy is a core skill for every student, not a specialised elective, and use AI to widen access rather than widen the gap between students who have it and those who don’t. Ultimately, the universities that will define the future are those that empower students to not just understand AI, but to build with it responsibly.
8. Rajesh Ramdas, Senior Director, Field Engineering (India), Databricks
“India’s AI story is no longer about experimentation, it is about execution at scale. On AI Appreciation Day, we see a market that has moved past pilots into production, with enterprises across industries building agents that reason over their own data, not generic models trained on the open internet. The winners in this next phase will not be the enterprises using the best models, but those that bring the most relevant context to those models. This is where contextual intelligence matters.
This shift is powered by unified, governed and trusted enterprise data. Organizations that build this foundation today will be best positioned to translate AI investments into outcomes that hold up at scale.
India’s advantage is talent, with some of the world’s deepest data science and engineering pools now shipping AI systems that move the needle on revenue, cost, and experience. The next 12 months will separate enterprises that ran AI pilots from those that built their data foundation, because that foundation is what will determine who wins.”