India’s manufacturing sector is moving beyond boardroom ambition to plant-floor execution—where real-time metrics, predictive maintenance, and smarter decisions are beginning to show up in quality, throughput, and resilience. Industrial AI is no longer confined to strategy decks. It is increasingly embedded in day-to-day operations on the shop floor.
That shift – from promise to performance – was at the centre of the seventh edition of India Inc On The Move (IIOTM) 2026 in Mumbai, presented by Rockwell Automation in association with The Economic Times. The discussions were notably practical: how to integrate AI reliably, how to sustain improvements beyond pilots, and how to build the organisational discipline required for scale.
IIOTM is a premier thought-leadership platform convening leaders, innovators, and influencers to shape the future of smart and sustainable manufacturing in India. IIOTM 2026, themed The Future Is Here: Smart. Sustainable. AI-Driven Manufacturing drew over 1,200 attendees and featured 30+ sessions and 70+ speakers, alongside an expo floor supported by 30 demo booths showcasing technology solutions and use cases.
This year, industry leaders reflected a more pragmatic perspective on AI-driven manufacturing. Executives who previously emphasized AI’s transformative potential were now engaged in thoughtful discussions about maximizing return on capital, improving integration efficiencies, and planning for sustainable operations after pilots conclude.
Dilip Sawhney, Managing Director, Rockwell Automation India, put it plainly: “It is important to understand that in the context of industry, industrial AI is vastly different. It needs to be deterministic, it needs to be explainable, it needs to lend itself to an audit trail.”
The term ‘explainable’ holds particular significance in regulated manufacturing settings. In cases such as a pharmaceutical batch failure or an unexpected outcome in a steel pour, it is essential to reconstruct exactly what the system observed, the recommendations it made, and the reasoning behind those decisions. Transparent and traceable AI systems are crucial for meeting these high standards of accountability.
Upskilling and workforce transformation
Scott Wooldridge, President, Asia Pacific, Rockwell Automation: “Technology alone will not drive transformation. Much of the AI capability already exists. The real shift lies in leadership and culture, in bringing people along and making them comfortable with the journey toward greater autonomy.”
Companies are shifting focus from just investing in software and sensors to prioritizing change management, middle management support, and building trust in dashboard-driven decisions. This approach helps create a tech-friendly, empowered workforce.
Demetrios Georgacopoulos, Global CHRO, Rockwell Automation, acknowledged the workforce dimension directly. “As we accelerate automation, we are partnering across our ecosystem and investing deeply in upskilling. From digital twins to predictive insights, this transformation demands new capabilities. With structured training pathways across roles, we are preparing our workforce to lead the next phase of growth.”
When automation is paired with thoughtful reskilling, factories achieve tangible progress and results.
Meaningful AI impact
What does a genuinely mature AI-enabled plant look like? Vipul Tandon, CEO, Wipro PARI, offered the most concrete answer of the day. “A mature software-defined automated plant is measured by five indicators: agility to meet shifting demand, at least 20 percent productivity gains, robust cybersecurity on legacy shop floors, new value creation through analytics and predictive maintenance, and seamless multi-site integration on a single dashboard.”
For most Indian manufacturers operating on tight margins in highly competitive export markets, achieving more output from the same asset base represents a game-changing leap forward.
Dr Tapan Sahoo, Executive Director, Maruti Suzuki India, was the most direct voice on that gap. “The real question is distinguishing operational reality from over-expectation in AI. Where are we truly creating value, and where are we running ahead of ourselves? AI can unlock insights from vast data, but disciplined application is essential to deliver meaningful impact.”
AI generates real value only when applied with discipline, delivering measurable improvements in productivity, decision-making, and efficiency.
Rohit Pathak, CEO, Birla Copper, spoke about plant process. “As we adopt AI, we must ensure we do not lose the plant’s deep process wisdom. Any tool we deploy should embed how operations truly work. Once that knowledge is lost, it cannot be regained.”
One of the most promising aspects of digital transformation is its ability to enhance plant operations by combining AI and automation with the invaluable, tacit knowledge of experienced workers. By integrating these insights, companies can ensure more effective and resilient processes while honoring the expertise of their workforce.
Advancing through sector-specific challenges
The industry track at IIOTM evolved from discussing AI potential to highlighting practical successes – revealing a remarkable consistency in opportunities and solutions across sectors.
In automotive and tire manufacturing, the narrative is now focused on building resilient, future-ready operations. AI-enabled supply chains and software-defined plants are empowering companies to confidently navigate geopolitical shifts, embrace the rapid advancements in battery technology, and meet evolving localization requirements. The accelerating transition to electric vehicles is inspiring manufacturers to adopt more agile planning cycles, positioning them to capitalize on new opportunities and thrive in a dynamic market environment.
In the food and beverage sector, AI is driving impressive results by enhancing operational efficiency and boosting profitability: predictive maintenance minimizes unexpected downtime, machine learning optimizes product yield, and compliance automation strengthens safety and reduces recall risk. Thanks to these clear and tangible benefits, the food and beverage industry is leading the way in AI adoption.
Life sciences leaders are embracing AI as a powerful tool to support regulatory precision. With real-time quality oversight, robust data integrity, and scalable CDMO operations, AI enables the sector to confidently meet licence-to-operate requirements. These high compliance standards underscore the value of AI, ensuring safer, more efficient operations and providing a clear pathway to industry leadership.
In heavy industry, sustainability conversation is about measurable action: emissions tracking, energy optimization, and closed-loop systems are actively driving improvements in ESG performance and delivering tangible cost savings.
AI is changing how OEMs and machine builders work. As technology moves from testing to wider use, equipment is now valued for sending reliable data, easy integration, and the ability to upgrade without causing downtime or safety issues. Machines are becoming a key part of digital strategies.
Across all sectors, organizations are increasingly embracing opportunities to integrate brownfield sites, align IT and OT systems, strengthen cybersecurity on legacy shop-floor equipment, and foster skill development, turning common challenges into catalysts for progress.
Where Success Is Evident
The most grounded testimony at IIOTM came from operators tying technology to measurable outcomes.
In mining – an environment where the consequences of error are measured in lives, not margins – Kailash Pandey, Mining and Cluster Head, Sambalpur, Aditya Birla Group, was unequivocal about the bar any technology must clear. “In mining, quality control and quality assurance are critical because safety is non-negotiable. Any new technology must prove itself in live environments. With AI and digital twins, we are improving energy efficiency and cutting defects significantly.”
Performance gains in such environments carry a different weight. When the baseline is worker safety rather than throughput, the credibility of a technology’s claims is tested far more rigorously than in a controlled pilot.
At Hindustan Unilever, the gains are showing up in a more familiar metric: speed of decision. Ram Bhadouria, GM – Engineering and Projects, framed it simply. “Productivity improves when you use real-time dashboards to track losses, optimise assets, and act on insights. As we move toward Industry 5.0, the focus is on resilience and human-centric automation.”
By implementing automation at scale across diverse manufacturing locations, the company ensures that systems are designed to empower operators, enhancing their judgment and capabilities rather than replacing them.
Siddharth Chowdhary, Executive Director, Bluecraft Agro, made the case that greenfield players carry an advantage over legacy manufacturers. “For us, automation was never an add-on; it was the foundation of our expansion.”
When a company uses automation from the start, it can adapt and innovate more easily, without the limits of old systems. Instead of seeing brownfield challenges as problems, they become chances to use modern technology and learn from past experiences.
Modernizing network
Factories that have invested in sensors, analytics, and control systems are realizing the potential to unlock even greater performance by modernizing their networks. By moving beyond legacy systems, originally designed to keep operational technology isolated, they can now integrate seamlessly with enterprise platforms and cloud intelligence, overcoming previous constraints and positioning themselves for smarter, more connected operations.
Rockwell Automation and Cisco announced a strategic collaboration to help reimagine the future of manufacturing in India, bringing together IT and industrial automation to support the country’s ambitions for advanced, resilient, and globally competitive manufacturing. With Kartika Prihadi, Vice President, Partner and Routes to Market Sales, Cisco APJC, Shovan Sengupta, Regional Vice President, Market Access, Asia Pacific, Rockwell Automation, and Dilip Sawhney, Managing Director, Rockwell Automation India, on stage, the message was pointed: secure, industrial-grade connectivity is not infrastructure that sits beneath AI. It is the condition under which AI either works or does not.
The partnership also signals something broader about where the industry is heading. As IT and OT converge, the traditional boundaries between network vendors and industrial automation providers are collapsing. The factory in the next decade will be designed as an integrated system from the start.
India’s Moment
The macro argument for India’s manufacturing opportunity is well-known. Supply chain diversification, a large domestic market, a young workforce, and policy momentum behind production-linked incentives have combined to make India a credible candidate for a meaningful share of global manufacturing capacity over the next decade.
Sanjay Sharma, CEO China, ArcelorMittal, and Board Member, NAMTECH, connected that opportunity directly to AI’s role. “India has the talent. India has the ambition. And AI is a powerful and transformative tool to unlock its true potential.”
The ambition is not in question. What IIOTM 2026 made clear is that the execution challenge is more complex than most technology narratives suggest. It is not about access to AI tools – those are increasingly commoditised. It is about building the organisational readiness, the skills base, the integrated infrastructure, and the institutional discipline to deploy those tools on scale, across thousands of machines, in environments where the margin for error is narrow.
India’s factories are closing the gap. The harder question – how fast, and at what cost – will be answered on the plant floor – and across value chains – not in the conference room.
