Artificial intelligence is moving beyond factory-floor automation to a broader business question for India’s industrial enterprises: how can AI reshape product design, operations, resilience and revenue?
That was the central theme at the Industrial Leadership Summit in Pune, hosted by Mint CIO Circle and Dassault Systèmes on 21-22 August. The summit examined what it will take to move industrial AI from experimentation to measurable business outcomes.
AI moves onto the CEO agenda
Manpreet Singh Ahuja, chief clients and industries officer at PwC India, said industrial companies need to rethink operating models rather than simply add AI to existing processes.
“AI fundamentally is transforming intelligence. And if you don’t rewire your factory around that intelligence, you’re missing the opportunity,” Ahuja said.
PwC research across industrial companies in 24 countries, cited at the summit, showed 50% of industrial leaders expect highly automated processes by 2030, compared with 18% today, while 68% expect to rely heavily on advanced technology, compared with 26% currently.
“It will have to be a CEO agenda. It will have to be a product agenda. It will have to be an engineering agenda,” Ahuja said.
Boards ask a different AI question
The CEO panel, moderated by Amit Khanna, partner at Grant Thornton Bharat, brought the discussion into the boardroom.
The message was clear: an AI investment must begin with the business problem, not the technology.
“CIO, CDIO, or CTO cannot remain technologists. They have to become business technology people,” Mundra said.
Malhotra said companies need to consider not just the return from adopting AI, but the competitive cost of doing nothing.
“If I don’t do this, where will I be? And if I do this, where will I be?” he said.
Pawar cited AI models at Adani Group being used to forecast component availability for large solar projects, helping anticipate supply-chain constraints rather than simply carrying additional inventory.
Deepak N G, managing director, India, Dassault Systèmes, said Indian companies are thinking seriously about scaling AI and demonstrating its value to CEOs and boards. India, he added, has the talent, technology and industrial base to lead in some areas.
He said companies are also focused on getting products to market faster, reducing manufacturing cycles and lowering costs through digital technology.
“We don’t necessarily have to follow the world. In some areas, India can be the front runner,” he said.
Autonomy raises the accountability question
As AI moves from providing information to making recommendations and, within guardrails, taking action, industrial companies face a harder question: who remains accountable when an AI-driven decision goes wrong?
Malhotra called for a “devil’s advocate” to challenge AI assumptions and test failure scenarios. Mundra put it more bluntly: “Your AI agent cannot face an audit committee.”
Ahuja said AI is progressing from information to recommendations, autonomous action and eventually self-optimising systems, making governance essential from the outset.
“Governance will not be a bolt-on. Governance will not be an add-on,” he said. “It has to be in the core design.”
That puts audit trails, data lineage and decision ownership alongside the AI model.
From pilots to connected industrial systems
A focused-group discussion led by Venkatesh Natarajan, former president-IT and chief digital officer at Ashok Leyland, examined AI across the industrial value chain, including engineering, sourcing, logistics and demand forecasting.
Day two brought CIO-led case studies from Havells India and L&T Energy on manufacturing systems, virtual twins and connected digital engineering.
The lesson was straightforward: AI cannot scale on disconnected data and fragmented systems.
Samson Khaou, executive vice-president, Dassault Systèmes, said sustained adoption also depends on the broader environment. Drawing on the company’s experience in China, he pointed to technological upgrading and policy consistency as drivers of confidence.
“Confidence is driven not just by short-term economic cycles, but by the consistency of government policy and the pace of technological upgrading,” Khaou said.
For CEOs and boards, the question is moving from “What can AI do for us?” to “What could our business become if we built it around AI?”
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