The automotive industry is one of the most data-intensive ecosystems out there. Modern vehicles are connected platforms that collect, process, and share massive amounts of information about drivers, passengers, and their surroundings. This creates real opportunities for innovation, but also introduces complex privacy challenges that automotive companies can’t afford to treat as an afterthought. Here are a few worth considering. 

‍

Metal & mobile: Combining physical and online products

Unlike industries like gaming, which operate entirely in digital environments, automotive operates across both physical and online worlds. This is already a unique situation that impacts our approach to data privacy in that sector. 

Data is not generated in a single, controlled environment. It originates in the vehicle through sensors and onboard systems, then flows into apps, cloud platforms, and external services, creating multiple, fragmented collection points and making it harder to maintain a clear, unified view of the data being collected and processed at any given time.

When data flows from a physical product into digital systems and across partners, it is not always obvious who is responsible for what. Is it the manufacturer, the software provider, or the app developer? In many cases, the answer is all of them, which increases the risk of compliance gaps. This hybrid setup can also make it harder to enforce core privacy principles like data minimization, purpose limitation, and retention. 

Mine helps bridge that gap by providing continuous data discovery and real-time mapping across systems. Teams can maintain an up-to-date view of data flows, assign ownership, and enforce policies consistently across the entire lifecycle.

‍

Hyper-sensitive data calls for hyper-qualified technology

When we think about the data our car may collect, we might not be alarmed at first. But a closer look reveals that some of the most sensitive information is revealed on four wheels. Vehicles collect precise location data, often down to exact routes, frequent stops, and daily routines. Combined with driving behavior data, this creates a detailed behavioral profile of individuals. 

Add the common use of cameras, recording every single thing being said and done, both in and outside of the car while driving, and you’ll see why the FTC has been warning about the dangers of unlawful data collection by automotive companies for years. There’s also an alarming transparency issue, as many drivers are unaware of the extent of data collection or how it’s used. 

‍

The carpool lane: Business partners and data sharing

Automotive data doesn’t stay within the car or even within the manufacturer. Recent research found that 84% of car brands share personal data with service providers, data brokers, and others. The ecosystem includes insurers, fleet managers, navigation providers, app developers, maintenance services, and more. Each of these players may access or process vehicle data for their own purposes.

For example, driving behavior data is increasingly shared with insurance companies to calculate premiums or assess risk. 

The regulatory challenge is clear. Automotive companies must ensure that data sharing aligns with regional privacy laws and contractual obligations. Mine’s Vendor Risk Assessment tool and automated sub-processor tracking capabilities allow organizations to continuously monitor how data is shared, who has access, and whether those relationships meet compliance requirements. Companies can ensure that data sharing is not only transparent but also controlled and auditable.

Trust matters for any company, but it carries even more weight when customers are choosing the car they rely on to drive their families every day. With solutions like Mine, automotive companies can turn complex data ecosystems into something easily visible and manageable, never making users feel like they’re being taken for a ride.

‍