After spending the past few years expanding its product portfolio and nearly quintupling passenger vehicle volumes, Tata Motors is shifting its focus to an area where it has historically faced criticism – quality.
At its Investor Day, the country's third-largest passenger vehicle maker said product quality will be the cornerstone of its next phase of growth, backed by artificial intelligence (AI), digital twins, software validation, Total Quality Management (TQM) and deeper supplier integration.
The company said the transformation comes at a time when vehicles are becoming increasingly software-driven and technologically complex, making conventional quality processes inadequate.
"On product quality... there are two stress points as far as quality is concerned. One is steep growth, leads to the system coming under stress and the second is the new tech. Therefore, we have to prepare the system proactively rather than reactively," Managing Director and Chief Executive Officer Shailesh Chandra said.
The renewed emphasis marks a strategic shift for Tata Motors, which over the past few years has focused on launching new products across internal combustion engine (ICE), CNG and electric vehicle (EV) segments. The company has grown its portfolio from six products in FY20 to 15 in FY26, while passenger vehicle volumes have increased almost five-fold to 640,000 units over the same period. As scale and product complexity rise, Tata Motors said world-class quality has become critical to sustaining growth.
The company said it has already made progress, reducing early-life vehicle issues by nearly 60 per cent through tighter factory quality gates, improved logistics processes and electronic proof-of-delivery systems.
To further strengthen quality, Tata Motors will deploy system-level simulations, early product validation and stricter manufacturing controls while investing in digital engineering tools such as hardware-in-loop testing, software-in-loop validation and digital twins.
"Given the number of new softwares and new technologies which are coming in, you have to create this digital infrastructure of hardware-in-loop, software-in-loop, digital twins to ensure that you do not always need a physical test... but are able to fully model it and test it within the development process itself," Chandra said.
The company also plans to use AI and telematics data to predict defects before they occur and continuously improve product performance.
"State-of-the-art quality infrastructure across our plants will enable precision manufacturing, leverage data and AI especially to identify early defects, prediction and continuous learning," Chandra said.
Beyond manufacturing, Tata Motors is extending the quality programme across engineering, suppliers and customer service. Chandra said Total Quality Management would become "a way of life" across the organisation and supplier ecosystem through structured problem-solving and prevention tools.
The company is also introducing AI-based diagnostic tools in its service network to reduce repair time and repeat failures.
"Going forward you will have diagnostic tools which are AI based which completely maps the fault tree and is able to immediately identify the real problem and therefore the turnaround times become higher, the repeat failures reduce," Chandra said.