AI could save OEMs a lot of cash – up to £200m a year

According to consultant Deloitte, AI could be used to improve analytics for warranties, saving the industry hundreds of millions of quids.

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Greater use of advanced analytics, and AI in particular, could produce a saving of between £150m and £200m in reduced warranty claims for car manufacturers, according to Deloitte.

And across the entire automotive value chain, the use of analytics to make sense of data, drive insights and automate decision making is adding value in terms of driving operating margin, revenue growth and asset efficiency.

The estimated saving is based on a typical market-leading original equipment manufacturer (OEM) with annual revenues of £100bn, incurring between 1% to 2% of total annual revenue on warranty costs each year, said Deloitte.

It added that warranty costs are the result of vehicles exhibiting lower-than-expected build quality, and that these issues tend to be the result of a design or manufacturing process, rather than isolated cases.

Using AI to interpret, often handwritten, diagnostics can categorise quality concerns quickly and accurately when vehicles arrive for repair.


Developing analytics’ capabilities from the traditionally descriptive to include diagnostic, predictive and prescriptive analysis will equip organisations to make more informed, faster decisions.

The potential value created through the use of analytics is huge, said Deloitte. For example, the use of advanced analytics to categorise warranty claims and identify and predict future issues could save an OEM between 15% and 20% of warranty costs. For a large OEM group with a revenue of £100 billion, spending 1 per cent of revenue on warranty, this can mean a saving of £150-£200 million per year.

In total, it says that AI has a strong part to play in the future of analytics that play a larger part of a cost saving mission for the industry.

It says that quality AI and the use of self-learning techniques on high-lead innovative data sources to predict emerging quality concerns, their root cause and appropriate countermeasures are the future of the car industry.


AI and analytics