India's Steel Sector Embarks on AI-Driven Transformation for Global Leadership

The Ministry of Steel has launched a comprehensive roadmap to integrate AI and digital technologies across the entire steel value chain. A key feature is the AI in Steel Pavilion, a collaborative platform connecting industry challenges with tech providers for scalable solutions. The initiative aims to support ambitious capacity targets, including reaching 400 million tonnes by 2036, through intelligent automation and data-driven systems. Industry leaders and AI companies engaged in a dialogue to identify high-impact use cases like predictive maintenance and emission reduction.

Key Points: AI Roadmap Unveiled for India's Steel Sector Transformation

  • AI Pavilion for industry collaboration
  • Focus on predictive maintenance & supply chain
  • Target 400M tonne steel capacity by 2036
  • Live sandbox for AI testing
3 min read

Govt unveils roadmap to drive AI-led change in steel sector

Ministry of Steel launches a digital roadmap and AI pavilion to integrate predictive analytics and automation across the steel value chain for competitive growth.

"This expansion will be supported by... AI-driven process control systems to ensure India's steel growth remains globally competitive. - Steel Ministry Roadmap"

New Delhi, Feb 18

The Ministry of Steel on Wednesday unveiled a comprehensive roadmap on Digital Opportunities in the Steel Sector at the ongoing India AI Impact Summit 2026 at Bharat Mandapam, reaffirming its commitment to transform India into a technology-driven global steel powerhouse.

The roadmap reflects a strategic recognition that the next phase of growth in steel will be defined not only by expanded capacity but also by intelligent systems, predictive analytics, automation, and data-driven decision-making embedded across the value chain.

At the core of the initiative is the AI in Steel Pavilion, a first-of-its-kind collaborative platform that showcases real-time industry problem statements and invites AI solution providers, startups, technology firms, and research institutions to co-create practical and scalable solutions.

The pavilion signals a clear transition from incremental digitisation efforts to mission-mode AI integration across mining, logistics, production, quality assurance, marketing, and corporate governance. It underscores the Ministry's intent to move from isolated pilot projects to systemic transformation.

A high-level session brought together leading steel producers, iron ore miners, senior policymakers, and AI innovators to deliberate on the sector's digital future. Major public sector enterprises and private stakeholders presented their forward-looking digitalisation roadmaps, outlining priority areas where AI interventions can create immediate and long-term value.

The dialogue focused on execution. Specific high-impact use cases were identified, and industry leaders articulated the technological capabilities they seek from AI companies and startups, including predictive maintenance algorithms, computer vision systems, supply chain optimisation models, and intelligent decision support systems.

The session enabled a two-way exchange. Industry representatives outlined operational challenges such as reducing downtime, improving yield, enhancing worker safety, optimising raw material blending, lowering emissions, and improving demand forecasting.

AI companies expressed their readiness to contribute advanced technological solutions tailored to these needs. This convergence is expected to create a structured innovation pipeline, ensuring that promising AI solutions are rapidly tested, validated, and scaled across the steel ecosystem.

In his address, Steel Secretary Sandeep Poundrik highlighted the remarkable growth trajectory of India's steel sector. Looking ahead to the vision of a developed India by 2047, he said that the Ministry has set ambitious and time-bound benchmarks: Crude steel capacity is targeted to increase from the current level of approximately 200 million tonnes to 300 million tonnes by 2030 to 2031 and further to 400 million tonnes by 2035 to 2036.

This expansion will be supported by parallel growth in mining output, logistics networks, beneficiation capacity, and downstream value addition. Intelligent automation, digital twins, advanced analytics, and AI-driven process control systems will be critical to ensuring that India's steel growth remains globally competitive and environmentally responsible.

Industry leaders also articulated the support required from AI startups, including domain-specific customisation, scalable system architectures, cybersecurity resilience, multilingual interfaces to facilitate workforce adoption, and solutions tailored to Indian operating conditions.

Besides, the ministry invited AI developers, deep technology startups, academic institutions, and research laboratories to leverage the Steel Research and Technology Mission of India as a live sandbox environment.

- IANS

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Reader Comments

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Priyanka N
Ambitious targets! 400 million tonnes by 2035-36 is a huge leap. While AI can definitely help with efficiency, my main concern is the environmental impact of such rapid expansion. The roadmap mentions lowering emissions - I hope that's a non-negotiable priority and not just a bullet point. We need green steel.
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Rohit P
Good move. The 'live sandbox' idea with SRTMI is clever. Letting AI firms test on real industry problems will speed up innovation. But what about the existing workforce? Mention of multilingual interfaces is good, but we need massive upskilling programs. Can't leave our steel workers behind in this tech shift.
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Sarah B
As someone working in tech, the collaborative platform (AI in Steel Pavilion) sounds like a great model. Solving real-time industry problems is much better than theoretical research. Hope this creates a blueprint for other sectors like textiles or automotive. Execution will be key though.
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Vikram M
Finally a clear plan! The shift from isolated pilots to systemic transformation is crucial. Our PSUs have been doing bits and pieces, but a unified mission-mode approach can change the game. Optimizing raw material blending and logistics alone can save crores. Jai Hind!
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Karthik V
Respectfully, I've seen many such roadmaps and summits. The proof will be in the implementation. The article talks about "time-bound benchmarks" for capacity, but what are the time-bound targets for AI adoption? How many plants will have integrated AI systems by 2027? We need those metrics too.

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