As artificial intelligence becomes a strategic priority for organisations, technology leaders believe that the focus must now shift from experimenting with AI models to building trusted, secure and scalable AI ecosystems that deliver measurable business outcomes. They say the future of AI will depend on responsible innovation, high-quality data, resilient infrastructure and governance that enables enterprises to deploy AI with confidence.
CP Gurnani, Co-Founder and Vice Chairman, AIONOS, highlighted AI’s potential to drive inclusive growth. He said, “Artificial Intelligence is at its best when it’s applied intelligence. The AI worth appreciating is the kind that reaches someone who never had access before. That’s the real story of India. We sit on 1.4 billion people generating data every single day, and the moment we stop treating that as infrastructure and start treating it as opportunity, everything changes. I’ve already seen glimpses of what’s possible: a chatbot answering a farmer’s questions about government schemes in his own language, frontline health workers using an app to catch newborn malnutrition early enough to save a life. If this is what’s happening at the early stages, I can only imagine what the next few years will bring. On AI Appreciation Day, I’m not just celebrating the technology, I’m celebrating who it’s about to reach next.”
Sharing his perspective on enterprise AI deployments, Amit Agrawal, President, Techno Digital, said, “AI Appreciation Day shouldn’t be about applauding models; it should be about recognizing the people, infrastructure and operational discipline that turn them into reliable business outcomes. The deployments creating lasting value are often the least glamorous: predictive maintenance reducing unplanned downtime by 30-50%; AI-assisted security operations shrinking response times from hours to minutes; intelligent document processing accelerating onboarding by 40-60%; and demand forecasting improving product availability while reducing working capital. Those outcomes don’t come from a smarter model alone. They come from validated environments where high-performance compute, distributed low-latency inference, resilient power, secure connectivity, and operational runbooks operate as a single system. That infrastructure discipline is what separates impressive pilots from enterprise-scale production.”
Dhananjay Ganjoo, Managing Director, India and SAARC, F5, said secure application delivery will be fundamental to scaling AI successfully. He said, “Every AI application depends on a continuous flow of APIs, inference requests, and model interactions, where even minor delays, downtime or security gaps can directly impact business outcomes. Keeping these AI applications fast, resilient, and secure requires more than powerful models it requires an application delivery and security architecture purpose-built for AI. As AI workloads grow, APIs connect AI models with enterprise applications and data, while application delivery intelligently manages AI traffic to maintain low latency, optimise performance and ensure high availability. AI gateways provide the control point to inspect prompts, govern model interactions, and enforce runtime guardrails, while workload security protects AI applications and inference services from threats such as prompt injection, API abuse, and data leakage. Together, these capabilities ensure AI applications remain performant, resilient, and secure in production environments. At F5, we see application delivery and security as the foundation for production AI, enabling organisations to confidently deploy and scale AI applications without compromising performance, resilience, or security.”
Speaking about the importance of trusted data, Mayank Baid, Regional Vice President, India & South Asia, Cloudera, said, “AI has evolved from a promising technology into a strategic business priority, reshaping how organizations drive competitive differentiation, efficiency, and growth. As enterprises move from pilots to production, success increasingly depends not just on deploying the right models, but on ensuring access to trusted, governed data that serves as its foundation. Today, the focus is shifting toward building AI that is sustainable, secure, and accountable across complex environments. Organizations that can combine trusted data with strong governance, transparency, and control will be best positioned to move beyond experimentation and deliver meaningful business outcomes while building long-term confidence in AI.”
Atul Ahuja, Area Vice President and General Manager, Elastic India, said organisations must focus on improving the quality and accessibility of enterprise data to realise AI’s full potential. He said, “Decades of enterprise knowledge sit locked inside applications, business systems and workflows, leaving every organisation with information that is valuable but rarely connected in ways AI can readily use. Deloitte’s State of AI in the Enterprise report puts a number to where India stands nearly 40 per cent of Indian organisations already report significant or full-scale AI adoption, and 94 per cent expect AI investment to increase over the next year. The momentum is real, but investment alone does not produce reliable AI outcomes. Attention is increasingly turning to the quality of enterprise data and the ability to retrieve it efficiently, because AI can only work with the information it can access. Retrieval brings together information spread across the enterprise, giving AI the context it needs to understand relationships, reason more accurately and produce reliable outcomes. AI agents make that capability even more important because they operate across multiple applications and business functions rather than within a single system. Their effectiveness depends on retrieving the right information and understanding how it relates to the task at hand. Organisations that invest in a strong retrieval layer will be better positioned to deploy AI with confidence and realize meaningful business value. The competitive advantage of the next few years will not go to whoever deploys the most AI. It will go to enterprises who give their decision makers and users with AI solutions that provide complete picture of what is actually happening in their business.”
On customer experience, Kaustav Das Modak, Developer Evangelist, Ecosystem – APJ at Twilio, said, “While many use AI to automate the ordinary, the true value of AI lies in solving problems. In the customer experience space, this means making customer journeys simpler, more useful, and more intuitive. A small boutique brand can now offer 24/7 customer support without needing a massive global team. Businesses can instantly communicate with customers in their exact local dialects, dropping the language barriers that used to make it difficult to communicate. As AI becomes integrated into daily tasks, customers will not dwell on whether they are interacting with AI; instead, they will simply expect every interaction, regardless of the channel to be seamless, personalized, and context-aware. Companies must focus on this aspect. By combining conversational AI with omnichannel engagement, real-time context, and customer data, businesses can deliver experiences that are consistent, empathetic, and tailored to individual customer needs. In the era of AI, the organizations that will lead are those that demonstrate AI’s value through ‘never before’ outcomes, thereby making every interaction faster, more meaningful, and truly more human.”
Highlighting the importance of trust in autonomous AI, BG Mahesh, CEO, Sahamati, said, “AI’s true potential will not be measured by how autonomous it becomes, but by how responsibly it can act on behalf of people. As AI evolves from systems that assist humans to agents that can discover information, make decisions and execute workflows autonomously, trust becomes as important as intelligence. Responsible innovation is no longer just about building better AI models. It is about building the trusted infrastructure that enables AI agents to identify themselves, obtain user consent, operate within defined guardrails and remain accountable for every action they take. India has already shown the world how Digital Public Infrastructure can enable trusted, population-scale innovation through open and interoperable ecosystems. The next opportunity is to extend these principles to AI, creating trusted digital rails in which identity, consent, governance and interoperability are embedded by design. This is where India can lead again by demonstrating that the future of AI is not just intelligent, but trustworthy, inclusive and built for public good.”
Sharing his views on AI’s impact on software engineering, Naresh Agarwal, SVP, Engineering, India, Harness, said, “AI is one of the most consequential shifts we’re seeing across industries today, not just in what it can do, but in how it is fundamentally changing how work gets done. From healthcare to finance to manufacturing, the ability to generate, analyse, and act on information at scale is redefining productivity, decision-making, and the pace at which ideas turn into real outcomes. In technology, that shift is even more pronounced. The role is moving beyond building features to shaping intelligent systems that can learn, adapt, and operate in real-world environments. As a result, value itself is being redefined. What begins to matter more is judgment, understanding context, navigating trade-offs, and making decisions that hold up in production. In that sense, AI is not a shortcut, but a multiplier. It amplifies those who can think beyond execution, guide systems, shape outcomes, and operate with a deeper understanding of how everything comes together. The real shift is not in access to AI, but in the ability to integrate it meaningfully into how we build and operate. What makes this moment worth appreciating is not just the technology itself, but the expansion of what’s possible. We are moving toward a world where systems are not just automated, but increasingly autonomous, capable of acting, learning, and improving continuously.”
Ranga Jagannath, Senior Director – Growth, Agora, added: ”Artificial intelligence is reaching a point where people will judge it less by how powerful it is and more by how natural it feels to use. The real shift we are seeing is from AI that simply generates outputs to AI that can hold conversations, understand context and respond in real time. As AI becomes more embedded in everyday experiences, the focus will move from technology itself to the quality of the interaction it enables. This is creating opportunities for businesses to engage customers, employees and communities in entirely new ways. But great AI experiences are not built on intelligence alone. They depend on responsiveness, trust and the ability to communicate naturally.”
Speaking about how AI augments human potential, Sriram Dinavahi, SVP – Engineering, Salesforce, said: “Every technological revolution has redefined what’s abundant. The Industrial Revolution multiplied production. The internet multiplied information. AI is multiplying expertise, and that changes everything. For most of history, expertise has been constrained by geography, time, and scale, concentrated in a handful of people or institutions. AI breaks that constraint. It extends deep knowledge across organisations, helping more people make better decisions, solve harder problems, and move faster. This is what we’re building at Salesforce: an agentic platform that doesn’t just automate tasks, but delivers real, measurable outcomes because moving from AI experimentation to enterprise-grade impact is the challenge every organisation faces today. And yet, the biggest opportunity isn’t efficiency. It’s inclusion. In India alone, we’ve committed to skilling one million learners in AI by 2030 because we believe access to expertise shouldn’t be determined by where you were born or who you work for. The organisations winning in the AI era are those treating it as an equaliser, not just an accelerator. Here’s what I keep coming back to: as AI takes on more of the routine, distinctly human capabilities only become more valuable. Asking better questions. Exercising sound judgment. Making decisions with context, ethics, and empathy. These don’t diminish in an agentic world, they become the differentiator. That’s why at Salesforce, our approach to AI is anchored in trust: systems that are powerful, yes, but also transparent, accountable, and built with human oversight at the centre. On AI Appreciation Day, what I appreciate most isn’t the technology itself, it’s what it makes possible: a world where human potential is more accessible, more scalable, and more inclusive than ever before.”
