Part 2 - Inside Tata Steel’s Digital Core. The Layered Architecture Explained

If governance and strategy were the backbone of Tata Steel’s transformation, data architecture became the central nervous system that made real AI at scale possible.

The Challenge - A decade ago, data sat in 30+ systems across IT and OT. Sensors streamed inconsistently. Networks couldn’t support real-time decisions. Everyone wanted AI, but the foundations were non existent.

Tata Steel resisted the temptation to 'jump to the model' and instead rebuilt the stack in the right order, a lesson many digital projects overlook.

Infrastructure Layer : The plumbing part

Before AI, they upgraded the basics. A Fibre backbone was installed upscaling speeds from 100 Mbps to multi Gbps. Edge servers were deployed for resilience & a secure hybrid cloud strategy incorporated to avoid lock in.

You cannot run industrial AI on unreliable bandwidth or fragmented compute. Tata Steel mitigated this risk early.

Data Foundation Layer : From chaos to clarity

Data from SCADA, PLCs, MES, SAP, lab systems and IoT devices was unified into a three layer architecture as follows:-

Bronze: Raw machine logs, sensor data, MES/SAP inputs

Silver: Cleaned, standardised, integrated datasets

Gold: Analytics-ready data powering dashboards, APIs and ML models

This single move collapsed weeks of manual analysis into minutes and gave leaders a single source of truth.

AI Models Layer : Post Foundation

Once data was reliable and accessible, Tata Steel built models that solved real business problems

Blast furnace temperature models (energy efficiency)

Bearing failure early-warning (2–4 weeks notice)

Yield optimisation models across lines and grades

These were not pilots. They were products with ownership, deployment plans, and measurable outcomes.

Business Impact : The numbers speak

With foundations + models + governance aligned, Tata Steel delivered:

$1.4B+ value created

40% reduction in critical downtime

10–12% yield improvements

Multiple WEF Lighthouse recognitions

Thus creating a rare example of industrial AI moving from hype to scaled impact.

My Take :-

The sequence here is striking:

Infrastructure - Data - Models - Outcomes.

Most organisations invert this order and get stuck in 'AI theatre'. Tata Steel did the opposite and the results speak for themselves.

Next in Part 3: The human side : capability building, connected workforce, cultural adoption and why

, not algorithms, ultimately determine success.