Mahindra & Mahindra is increasingly embedding artificial intelligence (AI) across its automotive business, from customer acquisition and vehicle development to manufacturing and aftersales in order to improve efficiency, lower costs and enhance customer experience.
Detailing the company’s AI initiatives during its first-quarter earnings briefing on Thursday, Group CEO and Managing Director Anish Shah said Mahindra has spent the last two years building its AI capabilities. The group has developed 19 proprietary AI models, trained more than 1,900 employees through its in-house AI academy and is executing over 15 large AI projects with a team of more than 50 AI engineers and specialists.
“We’re revealing our AI work slowly, one at a time,” Shah said, adding that the company evaluates every project on its impact on profitability and customer experience.
In the automotive business, AI is already delivering measurable gains across sales and service operations. Shah said AI-powered customer engagement agents booked more than 91,000 test drives in the last three to four months, helping the company reach prospective buyers it may otherwise have missed.
“These were customers that we would likely not have got otherwise,” he said.
The company has also rolled out AI-powered assistants across its service network, with around 2,600 workshop technicians, representing an 85% adoption rate, using the technology to diagnose vehicle issues, reducing troubleshooting time and improving service efficiency.
At Mahindra’s paint shop, AI-enabled process optimisation has helped improve first-time buy-of, the percentage of vehicles cleared without rework to 90.6% at the pre-treatment and electro-coating stage. According to Shah, the system has reduced paint consumption and rework while improving overall throughput.
AI is also helping accelerate vehicle development. Mahindra said it has reduced the time taken to predict a vehicle’s aerodynamic drag coefficient a key parameter influencing efficiency and range from more than 10 hours to about two minutes, significantly speeding up engineering simulations.
However, Shah declined to quantify the overall impact of AI on vehicle development timelines or whether it provides Mahindra with an advantage over fast-moving Chinese automakers.
“On product development, we shall hold that for a future date,” he said, adding that the company was seeing “meaningful impact” across engineering processes and would share broader outcomes later.
Shah emphasised that the success of AI initiatives depends as much on employee adoption as on the technology itself, citing feedback from workers at the company’s Chakan manufacturing facility, who have increasingly integrated AI into their daily operations.
