Artificial intelligence in auto sector has hit speed bump, says Capgemini

A study from the Capgemini Research Institute has found that just 10% of the major automotive companies are implementing AI projects to scale

In the absence of the right use cases, artificial intelligence (AI) for the automotive sector in India may not have a bright future, said Ananth Chandramouli, head of local business services at Capgemini India.

Capgemini’s recent report on AI usage in the automotive sector found that Indian innovation and investment in the space was lagging far behind other nations. This is to an extent that even pilot implementation of a lot of use cases are missing.

A study from the Capgemini Research Institute has found that just 10 per cent of the major automotive companies are implementing AI projects to scale, with many falling short of an opportunity that could increase operating profit by up to 16 per cent. 

While the central government as well as businesses are rushing towards investments in AI use cases, sectors like automotives may take a little longer to find the right fit given the larger input costs involved in automotive manufacturing.

Research shows that fewer automotive companies are implementing AI compared to 2017, despite cost, quality and productivity advantages.  “When it comes to the Indian automotive manufacturer, it is trying to figure out what is the right use case that is beneficial both to the it and the end user so that value is created. Otherwise, some of these things (use cases) will die a natural death,” said Chandramouli.

Since 2017, the number of automotive companies that successfully scaled up AI implementation (globally) has increased only marginally (from 7 to 10 per cent). However, more significant was the increase in companies not using AI at all (from 26 to 39 per cent).

According to the report, just 26 per cent of companies are now piloting AI projects (down from 41 per cent in 2017). This may be due to companies finding it harder to realise a desired return on investment on different use cases.

Notably, there is a large regional disparity with 25 per cent of US firms delivering AI to scale, compared to 9 per cent in China (note, this is a significant increase from 5 per cent to 9 per cent ), 8 per cent in France, 5 per cent in Italy and just 2 per cent in India.

Chandramouli said, “The key question for the Indian car manufacturers is who is going to pay for this. I can do all this great stuff but finally value for money market comes into play. Some of these things done are already a reality in the global automotive market.”

A number of homegrown tech start-ups are leading the pack with investments in AI coming from the likes of Ola and Rivigo which primarily use the technology in analysing driver behaviour on different routes. 

IBM’s acquisition The Weather Company also uses a similar set up for weather predictions on actual delivery routes of logistics companies. This helps them (the companies) predetermine the kind of wear and tear their vehicles are likely to suffer.

Among the larger automobile companies, Hyundai captures 1.2 billion data points a year across all its manufacturing processes. These data points are analysed to gain actionable insights in order to fine-tune its current operational parameters, including predictive and preventive maintenance.

Carmakers in India have been early adopters of automation on shop floors. 

Local subsidiaries of multinational companies have brought in best practices in manufacturing and sophisticated technologies from their parent companies in Japan, US, Germany and Korea.

Chandramouli said that over the next two to three years, the AI adoption levels can change greatly provided companies find the right mix of use cases and cost. 

“Given that the digital journey has been predominantly on the customer experience front, original equipment manufacturers are in a much better position to drive AI used cases in that area,” added Chandramouli.