Tata Steel Slashes Delivery Timelines to 3 Days with AI and IoT Push

Under an increased sweeping digital transformation adoption of artificial intelligence, IoT, and automation across global operations, Tata Steel moves its product delivery time from a week to just three days.

The historic steelmaker of 118 years has deployed more than 600 artificial intelligence and machine learning models on its value chain-from mines to mills to markets, making efficiency, safety, and customer experience am sure. The company, which has an annual crude steel capacity of 35 million tonnes and plants across India, the UK, the Netherlands, and Thailand, is using digital platforms to rewire sales and supply chains.

Its online commerce portals Compass (B2B), DigECA (B2SME), and Aashiyana (B2C) enable real-time order tracking, product availability checks, flexible payments, and integrated transactions. Monthly sales from these platforms have already crossed ₹500 crore, according to CIO Jayanta Banerjee. “Digital and AI are not peripheral projects but central to our strategy for future readiness,” he said.

The shift has delivered measurable gains. Orders that earlier took up to seven days now reach customers within 72 hours, supported by integrated visibility across plants and supply networks. An AI-powered margin monitoring system provides end-to-end optimisation, while digital twins and remote operations centres supervise mining and plant activities from off-site locations in some cases as far as 300 kilometres away.

Safety has also been a focus. Tata Steel has rolled out a connected workforce platform using AI, geo-fencing, and video analytics to flag unsafe conditions and generate alerts. “Suraksha” cards track PPE compliance, block unauthorised entry, and trigger SOS signals for rapid rescue.

Banerjee said the company’s digital journey began by laying strong foundations in cybersecurity, cloud infrastructure, and sensorisation before scaling AI use cases. “From our experience, technologies such as AI, digital twins, and Industry 4.0 are already delivering tangible value from early quality detection to lower energy use and optimised supply chain costs,” he noted.

The bigger challenge ahead, he added, is cultural: embedding data-driven decision-making into everyday operations.