Tata Steel on Wednesday announced a major expansion of its strategic partnership with Google Cloud to deploy a unified, enterprise-wide agentic AI ecosystem across its global operations. 

As part of the collaboration, Tata Steel has rolled out over 300 specialised AI agents within nine months, aimed at enhancing efficiency, precision, and real-time decision-making across its value chain. 

“Working with Google Cloud has allowed us to turn AI from a technical experiment into a specialised partner for every employee. This isn't just about new tools; it’s about a continuous engine of execution that enables our people to act on insights instantly,” said Jayanta Banerjee, Chief Information Officer at Tata Steel. 

He added that the company is using agentic AI across functions ranging from predictive asset maintenance to reducing customer response times, helping simplify complex processes and drive execution at scale. 

Sashi Sreedharan, Managing Director of Google Cloud India, said Tata Steel’s rapid adoption sets a benchmark for industrial transformation. 

“While many industrial players are still navigating the complexities of digital transformation, Tata Steel has moved at unprecedented speed to deploy AI at scale. Their approach shows how a unified data cloud combined with generative AI can turn industrial complexity into a competitive edge,” he said. 

Building a unified data-driven engine 

At the core of the transformation is Tata Steel’s early investment in a consolidated data architecture on Google Cloud, enabling it to move away from fragmented systems to a unified execution engine. 

Two key platforms are driving this shift. The first, Zen AI, is an internal low-code platform that allows non-data scientists, including developers and frontline managers, to build and deploy AI agents. Integrated with tools such as BigQuery and Google Cloud Storage, it combines structured operational data with unstructured inputs like video and documents. 

The second platform, the Tata Steel Digital Assistant (TDA), acts as a central decision-making interface. It integrates global public data, internal enterprise systems, and proprietary datasets, allowing employees to generate insights from sources ranging from financial records to call recordings and PDFs. 

This integrated approach also enables predictive intelligence. By combining geopolitical signals with commodity price data, the system helps anticipate supply chain disruptions and market shifts. 

Efficiency gains across operations 

The company said agentic AI is already delivering measurable efficiency gains. The TDA platform autonomously resolves over 70% of routine HR queries, significantly reducing administrative workload. 

In core business functions, AI agents are streamlining workflows such as invoice processing, GST classification, and contract analysis. By automating repetitive tasks, Tata Steel is reallocating workforce capacity toward higher-value strategic roles. 

The deployment is supported by scalable infrastructure built on Google Cloud Run, allowing systems to handle demand spikes while maintaining governance and lifecycle control across more than 200 AI models. 

Beyond enterprise functions, Tata Steel is embedding AI directly into manufacturing operations to improve safety and operational efficiency.