PINAKI MAJUMDAR
Jamshedpur, Feb 4: Tata Steel is at the forefront of technological transformation through the integration of Artificial Intelligence (AI) and Industry 4.0 technologies.
In the last 5-6 years, the company has built over 550 AI models for enhancing Yield, Energy, Throughput, Quality and Productivity, stakeholder experience, safety, and sustainability.
Investment in Generative AI and Advanced Platforms
The company has invested significantly in cutting-edge generative AI platforms which are now powering automated insights, conversational interfaces, and addressing hard-to-solve use cases by combining the abilities of conventional (mathematical) AI with the creative capacities of Generative AI.
Strategic AI Integration Focused on Business Needs
Jayanta Banerjee, Chief Information Officer, Tata Steel, said, “At Tata Steel, we approach AI and tech with a sense of realism, contextualising every AI initiative to our specific business needs and long-term goals. Technology should serve the business, not the other way around, so our tech investments are always tied to clear business KPIs and the tangible value they bring. A crucial part of this strategy is our focus on data. We have prioritised data management, ensuring our AI solutions can truly unlock value. As business models evolve and the future is reimagined, we believe AI should be viewed as a strategic enabler that thrives within a clear, value-driven framework.”
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AI Applications Enhancing Workplace Safety
AI applications are enhancing safety on the shop floor, where real-time detection systems monitor potential hazards, including missing personal protective equipment (PPE) and unsafe practices like improper handrail use, spills, and deviations from standard operating procedures to proactively address risks.
AI further analyses safety observations logged in the system, identifying patterns to predict potential safety incidents, allowing for proactive risk identification and mitigation. This proactive approach creates a safer work environment and minimizes risks.
Predictive Maintenance, Quality Control and Optimizing Operations with AI
Predictive models also support maintenance, assessing equipment health to preempt failures and reduce unplanned downtime, while AI-based defect detection ensures the highest quality standards at CRM facilities.
Tata Steel’s AI-driven insights and hyper-personalised interactions reinforce customer experience, leveraging data to better align offerings with their needs. On the operational front, digital tools streamline supply chain logistics, enhance energy management, and enable remote operations—driving improvements in decision-making, responsiveness, and overall productivity.
