AI has transitioned into a mainstream operational tool for UK car dealers, according to new research from Close Brothers Motor Finance (CBMF).
Dealerships are utilising artificial intelligence (AI) to drive operational efficiency, with motor finance, vehicle pricing, and customer service leading the wave of digital adoption across forecourts.
John Cassidy, managing director at Close Brothers Motor Finance, said: “It is encouraging to see dealers up and down the country embracing AI to improve efficiency in a way that adds genuine value to the customer journey. As AI continues to evolve, we’re committed to helping dealers understand its potential and build the confidence to adopt it in a way that works for their business.
“Ultimately, any use of AI must always have the customer at its heart. By using these tools to refine processes and create smoother customer journeys, rather than simply as a way to cut corners, dealers can build genuine trust and strengthen lasting customer relationships.”
Nearly two-thirds (65%) of UK motor dealerships are already actively using AI tools in their business today, with a further third (32%) planning to introduce them in the future.
Supporting customer finance options leads the way (40%), followed by vehicle pricing and valuation (37%), and customer service tasks such as chatbots (31%).
A little over a quarter (28%) use the technology for risk and compliance functions including fraud detection and finance checks.
Around one in four adopting dealers report using or planning to use AI for targeted marketing and advertising (27%), lead generation and sales insights (26%), stock management and forecasting (24%), and aftersales servicing (23%).
Just 4% of surveyed dealerships have ruled out using AI tools altogether. Among the non-adopters, 71% do not trust the technology while 57% believe AI would not provide meaningful commercial benefits.
The same number (29%) of non-adopters prefer traditional manual processes, are unfamiliar with AI tools, feel AI is not relevant to their specific needs, worry about the accuracy of AI outputs, or believe implementation costs outweigh potential benefits.
Just 14% cite data privacy or cyber security risks as their main concern.
