As topics go, they don’t come much hotter than artificial intelligence (AI). AI isn’t just another buzzword or passing trend. It’s a technology that promises to have a genuinely transformative impact on the automotive industry. From the supply chain to the powertrain, AI promises to revolutionize everything from design and planning, through to the customer experience.
At the same time, any conversation about AI is — inevitably — also a conversation about data.
“The two are fundamentally linked,” says Bart Koek, Field CTO at Immuta. “If you want to explore the full potential of artificial intelligence, then you’re also going to need to feed your models with well-structured, high-quality data.”
That’s particularly true when it comes to what he describes as the “most exciting” AI use cases — connected services, predictive maintenance, autonomous vehicles, and more.
“The data that underpins all of those things tends to sit at the higher end of the risk spectrum,” says Koek. “The truly visionary ideas around AI in automotive are going to need customer data to make them work, and specifically personally identifiable information (PII). Without the right kind of guardrails in place, that’s where manufacturers are going to struggle.”
The risk is that this could lead to a thoroughly frustrating future — one in which vehicle manufacturers find themselves sitting on a wealth of data, but not being able to use it for to its full potential. The reason for this concern is simple: regulation around consumer data in the automotive industry is likely to become increasingly stringent.
“The danger is that we get to the point at which it becomes impossible to make those things any better than they already are today,” Koek says. “If you can’t prove that you’re applying the right controls to that information, then you won’t be able use it effectively — and neither will your AI models.”
Market insights, expert commentary, and the latest data security news in Driving Change — Immuta’s dedicated automotive magazine.
