Rethinking where automotive AI belongs

As cars get smarter, a fundamental question is coming into focus: where should AI actually run? 

It’s a deceptively simple question – but one that opens a much broader conversation about architecture, user experience, and the future of mobility. 

One-size-fits-all? 

Each approach comes with its own trade-offs. AI can live: 

• Directly in the vehicle  

• In the cloud  

• On personal devices like smartphones  

• Or across a combination of all three  

What’s becoming increasingly clear is that there’s no one-size-fits-all answer. The “right” choice depends on context – latency requirements, cost constraints, update cycles, and, most importantly, user expectations. 

Interestingly, this diversity of perspectives was reflected in a poll we ran on LinkedIn last week. While a slight majority (52%) leaned toward in-vehicle hardware, a significant portion (27%) of respondents favored hybrid approaches, and cloud-based options also held meaningful ground (21%). Notably, personal devices didn’t receive much attention – at least not yet. 

That distribution tells an important story: the industry isn’t converging on a single model. It’s exploring. 

Expanding the architectural mindset 

Traditionally, the head unit has been seen as the central hub for in-car intelligence. And for good reason – it’s tightly integrated, always present, and directly connected to vehicle systems. 

As AI evolves, so does the opportunity to think beyond fixed boundaries. Modern AI systems are inherently flexible. They can shift workloads dynamically, balance local and remote execution, and tap into different compute environments depending on what’s needed in the moment. This opens the door to architectures where intelligence is no longer tied to a single piece of hardware. 

The role of the smartphone – An untapped layer 

One perspective is the idea of extending AI beyond the vehicle itself – leveraging devices that users already carry with them. 

Smartphones, in particular, bring some advantages: 

• They’re continuously updated and improve faster than vehicle hardware cycles  

• They already host powerful AI capabilities  

• They’re deeply personalized and trusted  

When integrated thoughtfully, they can act as a bridge – connecting the in-car experience with a broader ecosystem of intelligence. This doesn’t replace existing systems. It complements them. Even as intelligence becomes more distributed, the vehicle remains central to the experience. 

Connectivity options also play a role in shaping what’s possible. Different integration paths, from lightweight setups that work with existing systems to more advanced configurations, can unlock varying levels of capability. 

An option among many 

Rather than narrowing the conversation, the goal is to broaden it. 

By considering new ways to distribute intelligence – across the vehicle, the cloud, and personal devices – we open up new possibilities for delivering smarter, more adaptable experiences. 

And in doing so, we move closer to a future where automotive AI isn’t defined by where it runs – but by what it enables.