Riding on the AI‑based solutions high, Pune‑headquartered prescriptive AI firm, Infinite Uptime, is now eyeing top‑dollar heavy industry projects in the US, Europe and Australia. Even as the company has earmarked up to 30 per cent capex for overseas expansion, Karthikeyan Natarajan, CEO, tells INFRASTRUCTURE TODAY’s Manish Pant that India must maximise its digital public infrastructure to ride the next AI wave.
In your view, what key factors—from pandemic disruptions to geopolitical shifts and demographic changes—have driven the rise of AI in this decade?
Over the past 25 years, three forces reshaped the world: the dot‑com boom, which connected people globally; smartphones, which put data at our fingertips; and the cloud, which transformed computing into a consumption‑based service. Together, they laid the foundation for today’s AI revolution. AI is not a passing trend; it is the “intelligence engine” of the next century, comparable to electricity or the steam engine in its transformative power. Investment projections of $80-90 trillion reinforce the scale of change. While the pandemic and geopolitics accelerated adoption, they are secondary to this structural shift. We are still at the start of the journey, perhaps the third kilometre of a marathon. There will be bubbles, as valuations outpace revenues, but the long‑term trajectory is clear: AI will place both consumers and enterprises at the centre, driving exponential data consumption and steadily falling costs. Just as electricity became the invisible backbone of modern life, AI will become the unseen architecture of the next century.
How are Infinite Uptime’s products and growth strategy aligned with this expansion of AI?
We are riding this wave at the right time. Manufacturing, alongside fintech and semiconductors, is one of the world’s three largest economic pillars, valued at around $20 trillion. Yet inefficiencies remain vast, with between $1-2 trillion lost annually due to downtime, poor prediction, and outdated tools. Infinite Uptime is building what we call an intelligent manufacturing engine, a prescriptive AI platform for autonomous operations. Its pillars are maintenance, energy efficiency,
and throughput improvement. By embedding intelligence into plant operations, we aim to transform manufacturing from reactive to predictive and ultimately autonomous.
This approach is not just about technology; it reflects a global shift. Nations are re‑prioritising domestic manufacturing for reasons of geopolitics and national security. Steel and cement, for example, are now seen as strategic assets. Our platform enables smarter, more resilient production in this new environment, ensuring that factories are not just productive but future‑ready.
You have had demonstrable successes with your product, helping industries such as steel and cement enhance efficiency. Could you share a couple of examples?
Our customers have reported significant gains. A leading tyre manufacturer in India achieved a 12-15 per cent improvement in throughput in FY2024-25 by maximising uptime across its machinery. A major steel producer, with revenues of $30 billion, recorded a 200 per cent improvement in uptime, a transformative impact on its operations. Other clients have seen energy efficiency gains of around 5 per cent. We have also worked with cement plants, where predictive maintenance prevented costly spillages and reduced downtime. These results matter because manufacturing is traditionally conservative and risk‑averse. Plants rarely allow external solutions without clear proof of value. Demonstrating tangible outcomes has been critical to our success in India and is now enabling us to expand into the US, Europe,
and Australia.
Have you determined a timeline for overseas expansion, given Infinite Uptime’s strong brand presence in India’s manufacturing sector?
We have built a robust prescriptive AI engine, tested successfully in the US, Europe, and Australia. The equipment used in steel, cement, and mining plants in India is largely imported from Germany and Italy, so our solutions are already globally compatible. The difference lies in context. In the US and Europe, skilled labour shortages mean customers need more automated decision‑making and closed‑loop systems. Instead of partial recommendations, they want platforms that can generate work orders and complete tasks end‑to‑end. This is where we see opportunities to adapt and upgrade our products for these markets. India’s customers are cost‑sensitive, often seeking incremental improvements. In contrast, Western markets demand automation at scale, creating opportunities for us to deliver higher‑margin solutions.
What capital expenditure have you earmarked for this project?
We have already invested in building strong sales and marketing teams across the US and Europe. I am currently operating from the US, where we have hired a country sales head and team, and we have replicated this structure in Europe. Around 20-30 per cent of our planned investments will be directed towards these geographies, including Australia. The rationale is clear: price realisation and margin
expansion are significantly higher in developed markets. Unlike India, where customers pay in pennies, here contracts are valued in dollars and euros, offering us greater scope for sustainable growth.
Returning to the macro discussion, how do you see AI applications spreading across industries to become part of everyday life?
Consumerisation has already begun. ChatGPT, for instance, has made AI accessible to everyone; even my wife now checks it before believing me! This shift mirrors the smartphone revolution: once adopted by consumers, it naturally permeates enterprises. On the shop floor, workers facing issues will increasingly turn to AI tools for quick solutions. Adoption cannot be avoided; the challenge is to make it secure and scalable. By 2028-29, AI will be mainstream, with more than half of enterprises using it. Early adopters are already driving momentum, with penetration expected to rise from 10-15 per cent today to 30-35 per cent next year. This is not just about convenience; it is about embedding AI into the rhythm of everyday work, from office productivity tools to factory operations.
What role do you see this technology playing in enhancing efficiencies?
AI delivers predictability and peace of mind. Manufacturing has long been a “heroic drama,” with daily crises resolved by individuals stepping in as heroes. AI shifts operations towards structure and reliability, reducing shocks and surprises. It also addresses the skilled labour shortage in the West. By capturing knowledge into enterprise expert systems, companies can retain expertise
even as older workers retire. Predictive maintenance, for example, can prevent unplanned outages, saving millions in lost production. This ensures continuity, reduces emergency interventions, and makes processes more efficient and sustainable.
Having witnessed Industry 4.0 unfold over three decades, how do you see human and AI capabilities conflicting or complementing each other in the years ahead?
Initially, AI will strongly complement human capabilities. For the next three to four years, humans are essential to teach the systems; keeping a “human in the loop” until the machine learns. Once that happens, human intervention can become a distraction, opening up new job descriptions and ways of working.
This shift is less about job loss and more about productivity. As longevity increases and people remain healthier for longer, working lives will extend, creating opportunities for new roles. Rising incomes, particularly in India, will also drive demand for new services and industries. In the long run, disruption will generate more jobs and possibilities, making AI a net positive for humanity.
I guess I will need to share my CV with you to become future‑ready!
[Laughs] All of us must continuously upgrade our skills; this is going to be critical in the AI era. I often discuss this with my two sons, both in their twenties. They told me how AI tools such as Anthropic, ChatGPT, and cloud‑based agents have transformed their work. By adopting these platforms, they became 30-40 per cent more efficient and productive almost overnight. When I asked what they did with that extra capacity, their answer was telling: “We’re not doing less, we’re doing more.” Instead of reducing effort, they accelerated their company’s product roadmap, compressing a three‑year plan into two. That is the real impact of AI: it doesn’t just save time, it multiplies output.
Companies are now measuring productivity by outcomes rather than headcount. The gains are being reinvested into faster delivery, innovation, and expanded scope. Hiring may not increase immediately, but the same teams are producing significantly more. In the short run, this means higher efficiency; in the long run, it opens up new areas of work and new opportunities. This is the future‑ready mindset we all need. AI is not about replacing jobs; it is about reshaping them, demanding that each of us learn, adapt, and expand our capabilities.
With India working to emerge as an AI powerhouse through policy interventions and investments in data centres, what is the country’s future potential?
I am somewhat neutral to negative on India’s prospects in AI infrastructure. The global leaders—Taiwan, Korea, China, and the US—are already far ahead in semiconductors, computing, storage, and networks. India, as a $4-5 trillion economy, cannot match the deep pockets required for this wave. The train has left the station. The first wave of AI value creation is being captured by infrastructure companies, those building chips, data centres, and compute stacks. Unfortunately, India has already missed that bus. We cannot realistically compete with nations investing hundreds of billions in these areas.
But there is still an opportunity. India can benefit at the application layer, where our billion‑strong consumer base and strong tech services industry give us leverage. The real value lies in building businesses on top of AI infrastructure, not trying to replicate it.
Since you said India missed the first wave, how best can we leverage the second wave to avoid repeating the mistake?
We already have strengths in digital public infrastructure, such as Aadhaar for identity, UPI for payments, and ONDC for commerce. These platforms create vast data hubs that can be mined for new services. Healthcare is another area: India spends less than 3 per cent of GDP on it, compared to 6-7 per cent in developed countries. Smart healthcare solutions can deliver better outcomes without proportionally higher spending. So, while India may not dominate the infrastructure stack, it can still emerge as a beneficiary of AI, creating new businesses in finance, healthcare, entertainment, and consumer services.
The challenge is to ensure we don’t miss this second wave, as we did the first. This second wave is India’s chance to leverage its
consumer scale and data to create new businesses, ensuring it does not miss the opportunity again.