Sector by Sector Digital Enablement

India’s Digital Personal Data Protection (DPDP) Act marks a defining shift in how the nation thinks about privacy, consent, and digital rights. But as AI begins to influence decisions, opportunities, and everyday life, the real challenge lies in governing technology with the same clarity and responsibility with which we build it. The gaps around transparency, fairness, and automated decision‑making are no longer technical issues — they are leadership issues. In my latest video, I break down the core tensions between data protection and AI innovation, and why India must move from compliance to conscience as it shapes its digital future. If you’re interested in how policy, ethics, and technology collide at this pivotal moment, this exploration will give you a sharp, timely perspective. 🎥 Watch the full video here: https://youtu.be/xeouAt08i5Y    

Efficient supply chain management (SCM) has always been complex, with vast data, shifting variables, and multiple stakeholders making it difficult for humans to manage effectively. Agentic AI changes this by enabling autonomous decision-making, proactive planning, and seamless execution across procurement, logistics, and inventory management. Unlike traditional automation or generative AI, it acts independently  - executing tasks, adapting to conditions, and orchestrating processes in real time. Early deployments already show measurable gains in speed, resilience, and cost savings, and EY predicts that by 2030, half of cross-functional supply chain solutions will integrate agentic AI, underscoring its transformative potential. One of the most impactful applications in SCM is demand forecasting . Companies like Blue Yonder use agentic AI to match supply and demand, optimize warehouse labor, and reduce excess inventory. For example, a global retailer deploying AI-driven forecasting...

To remain competitive in today’s rapidly evolving industrial landscape, manufacturers must embrace innovation that drives both efficiency and resilience. One of the most transformative shifts underway is the move from preventive to predictive maintenance - especially when powered by artificial intelligence (AI). Companies like General Motors have already seen the benefits, using predictive analytics to monitor robotic arms and conveyor systems, reducing downtime by 20% and saving millions annually. Historically, maintenance strategies were either reactive - fixing equipment after failure - or time-based, relying on scheduled inspections. While these approaches have served industries for decades, they often result in unnecessary interventions or unexpected breakdowns. Predictive maintenance changes the game by leveraging historical data, analytics, and IoT sensors to forecast potential failures. For instance, Siemens used AI to detect early wear in turbine blades, allowing timely re...

In recent discussions, we've examined how climate change, environmental degradation, and population growth are intensifying pressure on agriculture. To meet these challenges, the sector is undergoing a profound digital transformation—shifting from seasonal, transactional farming to continuous, data-driven operations. This evolution is empowering farmers with real-time decision-making tools, enabling manufacturers to deliver tailored services, and helping agribusinesses streamline supply chains. The result is a more productive, resilient, and sustainable agricultural ecosystem that’s better equipped to meet rising food demand in an increasingly volatile world. At the core of this transformation lies cloud computing—now the central nervous system of modern Agritech. Agriculture, long rooted in tradition, is entering a new era where data and connectivity are as vital as soil and water. In India, AgroStar leverages cloud platforms to deliver agronomic advice and input recommendati...

In this edition of my agriculture digital transformation blog series, we’ll be exploring the evolving world of Off-Highway operations As autonomous tractors and AI-driven agronomy quietly reshape the agricultural landscape, the sector is undergoing a profound digital transformation - moving from seasonal, transactional equipment use to continuous, data-enabled partnerships between farmers and manufacturers. Automation, connectivity, and analytics are now embedded across the value chain: from self-driving harvesters and drone-guided crop monitoring to predictive maintenance and mobile diagnostics. These technologies not only enhance productivity and safety but also generate actionable insights that inform seed selection, irrigation, and yield optimization. The result is a smarter, more resilient farming ecosystem where digital tools empower farmers to make real-time decisions, manufacturers to deliver tailored services, and the entire sector to adapt to climate pressures, labor shifts...