Artificial intelligence has moved well beyond experimentation, but for many organisations, translating AI investments into measurable business outcomes remains a challenge. While enterprises continue to deploy increasingly sophisticated AI models, industry leaders believe that technology itself is no longer the biggest hurdle. Instead, the focus has shifted towards governance, trusted data, operational integration, human oversight, business alignment and workforce readiness. On this AI Appreciation Day, technology leaders shared their perspectives on what enterprises must do to unlock AI’s full business value.
Also read: A Cross-Industry Salute to the Transformative Power of Artificial Intelligence
According to AJ Sunder, CPO/CIO and Co-founder, Responsive, the biggest challenge lies in integrating AI into everyday business operations rather than simply adopting new technologies. “The biggest barrier to realizing AI’s true potential isn’t the technology. Most organizations already have access to powerful AI models. The real challenge is integrating AI into day-to-day business processes in a way that employees trust and can actually use. Many AI initiatives begin as isolated experiments. Teams adopt different tools, build disconnected workflows, and generate interesting outputs, but very little changes in how the business operates. Without governance, trusted enterprise knowledge, and clear business outcomes, AI becomes, at best, another productivity tool rather than a business transformation engine.
The one change that would accelerate meaningful AI adoption is shifting the conversation from ‘Which AI model should we use?’ to ‘Which business problem are we trying to solve?’ Organisations that focus on solving measurable business challenges while combining AI with trusted enterprise knowledge, governance, and human oversight will see far greater value than those that simply deploy the latest technology. AI will not replace good business judgment. It will amplify organizations that already know how to combine technology, people, and process into a repeatable system for execution,” he said.
Echoing the need for responsible enterprise AI, Vijayant Rai, Managing Director – India, Snowflake, said India is well positioned to lead the next phase of AI adoption, provided organisations balance technological innovation with human expertise. “India’s dynamic digital transformation, deep technology talent, and growing influence on global innovation place it at the forefront of the AI movement. As we celebrate World AI Day (AI Appreciation Day), the next phase of India’s AI journey will be shaped by organisations that leverage both open and proprietary models, enabling them to choose the optimal solutions for their business needs. At the same time, as AI advances, human judgement, domain expertise, and critical thinking become even more essential. This unleashes the full power of human expertise alongside intelligent systems to deliver exceptional results,” he said.
Niraj Nagrani, Chief Data and AI Officer, Altimetrik, said enterprises must now shift their attention from building better AI models to building trustworthy AI systems. “The race to build more capable AI is giving way to the challenge of building AI that is trusted, resilient, and economically sustainable. As organisations scale AI, the conversation is shifting towards trusted context, intelligent orchestration, token optimisation, governance, and cyber resilience. These are no longer technical considerations. They are the building blocks of production-ready enterprise AI. As AI becomes deeply embedded across business operations, organisations need trusted context, secure architectures, transparent decision-making, and meaningful human oversight. The enterprises that win the next phase will be the ones that continuously engineer, govern, and optimise AI until it becomes something far more durable than a tool,” he said.
Highlighting the importance of operational context, Kaushik Mitra, VP and Head of India GTM, Celonis, said organisations cannot expect AI to deliver business outcomes without understanding how their own processes function. “Enterprise AI is only as effective as the operational context behind it. Our latest Process Optimization Report shows that 90% of business leaders believe process improvement depends on accurate, contextual data, while 76% say there is still significant room to improve their business-critical processes. That’s why Process Intelligence has become the foundation for Enterprise AI. As we mark AI Appreciation Day, the conversation should shift from AI adoption to AI effectiveness. Operational context is what enables AI to move beyond experimentation and create measurable business impact,” he said.
Albert Nel, Senior Vice President, Asia Pacific and Japan, Genesys, believes enterprises now need to rethink customer engagement by combining AI with human judgement. “As organisations across India accelerate AI adoption, the conversation is shifting from experimentation to execution. In the age of autonomous customer experiences, the future is AI and humans working in collaboration to accomplish business and customer outcomes. Organisations that prioritise governance, responsible innovation and human oversight will be best positioned to create lasting value for customers, employees and the business,” he said.
From an organisational transformation perspective, Priti Sawant, Founder and CEO, JoulesToWatts, said lasting AI success depends on enterprise readiness rather than technology deployment alone. “Everyone today is talking about building an AI strategy. But the more important question is: how many organizations are building the capabilities required to sustain it?. The real challenge is not introducing AI. It is embedding AI into an existing organization without disrupting the outcomes it is expected to deliver. The organizations that lead the next decade will not necessarily be those running the largest number of AI initiatives. They will be the ones that successfully bring together AI, talent, operating models, and customer outcomes as part of one coherent business strategy,” she said.
According to Sajeev Viswanathan, Founder and CEO, New Street Technologies, the gap between AI pilots and production remains one of the biggest barriers facing enterprises. “AI Appreciation Day is a good moment to take stock of how far the conversation has moved. A year ago, enterprises were asking whether they should adopt AI. Today they are asking why their AI is still not in production. That gap is not a technology problem. It is what we describe as a FITS problem: Fear, Inertia, Trust issues, and Surprise. The next phase of enterprise AI will not belong to companies with access to the best models. It will belong to those with the best architecture. AI should not just make work faster. It should make enterprises fundamentally more trustworthy,” he said.
Sameer Kanodia, Vice Chairman and CEO, Lumina Datamatics & TNQTech, observed that AI has evolved into a strategic business capability, but governance remains equally important. “Artificial intelligence has evolved from being a productivity tool to becoming a strategic enabler of business transformation. Over the next few years, competitive advantage will not come from simply adopting AI, but from integrating it into end-to-end content supply chains where human expertise and intelligent automation work together seamlessly. Robust governance, human oversight, data privacy, intellectual property protection, and transparent AI practices will be critical to building trust and ensuring reliable outcomes,” he said.
Trust was also identified as the defining factor by Ankur Kanaglekar, Vice President – India, Thales. “As we celebrate AI Appreciation Day, it is important to recognise that AI’s true potential will not be measured by how quickly it is adopted, but by how much it can be trusted. AI must deliver more than performance: it must be secure, transparent, resilient and remain under meaningful human oversight. The future belongs to AI that empowers people to make faster, better-informed decisions while protecting critical data, systems and operations,” he said.
Similarly, Sujatha S Iyer, Head of AI Security, ManageEngine, Zoho Corp, said governance must keep pace with enterprise AI adoption. “As organizations across India mark AI Appreciation Day, the conversation around artificial intelligence must move beyond the hype of automation to a more pressing enterprise reality: how quickly governance can keep pace with AI adoption. The objective is not to slow innovation, but to ensure organizations have the visibility, governance, and controls needed to innovate securely. Enterprises that embed transparency, strong access controls, digital sovereignty, and accountability into their AI strategy from the outset will be better positioned to scale AI responsibly, build trust, and deliver measurable business value,” she said.
Along similar lines, Vasanthi Ramesh, Vice President of Engineering and Site Leader, NetApp India, adds: “AI’s greatest challenge is no longer intelligence, but trust. As AI becomes embedded in every industry, sovereignty is emerging as a strategic imperative. At NetApp, we see data as the foundation of every successful AI strategy, and sovereign AI in particular starts with trusted data. Indian organizations need an intelligent data infrastructure that enables them to innovate across clouds, environments, and AI platforms without compromising security, governance, or choice. The challenge is no longer simply deploying AI, but ensuring it can be adopted responsibly, at scale, and on an organization’s own terms. On AI Appreciation Day, it’s worth recognizing that the true enabler of sovereign AI is not the model itself, but the trusted data foundation that allows organizations to innovate with confidence and turn AI ambition into real-world impact.
