Get Ready To Pay More For Your New Car Soon!

• Rising memory chip prices could add to the cost pressure
• Modern cars are using significantly more RAM, storage and computing power

If you thought rising prices of smartphones, laptops and other electronic products were the only consequence of the global memory chip shortage, there could be another product getting caught in the middle of it - your next car.

The automotive industry is increasingly dependent on semiconductors and memory chips, and the demand for these components is only going one way. Modern cars are no longer just mechanical machines with a few electronic systems thrown in. They are increasingly becoming software-defined products, with powerful processors, multiple cameras, radars, large displays, connected services and advanced driver assistance systems. All of that requires memory.

And now, the same memory supply is being chased by the rapidly expanding artificial intelligence industry.

AI is putting pressure on memory supply

The recent surge in AI data centres has created enormous demand for high-performance memory, particularly DRAM and high-bandwidth memory. This appears to be putting pressure on the supply of conventional memory used in everything from computers to cars.

Automotive-grade DRAM prices are reported to have risen sharply in recent months, with some estimates suggesting increases of around 70 per cent or more depending on the type of memory. Automotive memory is also a relatively specialised product, as it needs to withstand much higher temperatures and operate reliably for several years.

This creates an interesting problem for carmakers. While manufacturers of memory chips are increasingly looking to meet the demand coming from AI infrastructure, cars are simultaneously requiring more and more of these components.

The result could be higher component costs for automakers and, eventually, higher prices for customers.

Take the Mahindra BE 6, for example

The Mahindra BE 6 is perhaps one of the clearest examples of just how much computing power has made its way into an Indian car.

Its cockpit uses a Qualcomm Snapdragon platform with 24GB of RAM and 128GB of storage, along with a dedicated GPU. The SUV also gets Mahindra's Level 2+ ADAS system, which uses a Mobileye EyeQ6 chip with another 2GB of RAM.

That 24GB figure is particularly interesting because it is more RAM than many laptops and smartphones still use today.

The memory isn't there simply to make the touchscreen feel fast. It supports the car's digital cockpit, applications, graphics, connectivity and other software functions. The ADAS computer, meanwhile, needs its own memory to process information from the vehicle's sensors and camera systems.

And the BE 6 isn't an isolated example. Modern cars from Mercedes-Benz, BMW, Tesla, BYD and several other manufacturers are increasingly built around powerful computing platforms. Multiple displays, voice assistants, navigation, OTA updates, connected services and increasingly sophisticated ADAS systems are turning the cabin into something closer to a mobile computing platform.

Where does all that RAM actually go?

Consider a typical modern car.

The infotainment system needs memory to run its operating system, applications, navigation and graphics. Connected-car functions need memory and storage for software and data. ADAS needs memory to process inputs from cameras, radars and other sensors.

Then there are features such as 360-degree cameras, driver monitoring, automatic parking, digital instrument clusters, augmented-reality displays and AI-powered voice assistants.

All of these systems have processors doing the actual computing, but those processors need fast memory to work with the enormous amount of data being generated.

This is also why the move towards software-defined vehicles could make the situation more significant. Cars are expected to receive more functions through software updates over their lifetime, which means the underlying electronic architecture needs to be capable of handling increasingly complex software.

It has already started affecting prices

This isn't necessarily a problem that exists only on a semiconductor industry's balance sheet.

In April, BYD increased the price of its optional God's Eye B LiDAR-based driver assistance system from 9,900 yuan to 12,000 yuan. At current exchange rates, that works out to roughly ₹1.40 lakh to ₹1.70 lakh, with the increase equivalent to around ₹30,000.

The company cited rising global storage hardware costs for the revision.

A 21 per cent increase in the price of a driver assistance package is significant, particularly because it shows how rising memory hardware costs could eventually make their way into the price of individual vehicle features rather than simply being absorbed by the manufacturer.

Will Indian cars become more expensive?

This is where things get slightly more complicated.

Indian carmakers are already dealing with higher raw material, logistics and other input costs, and several manufacturers have increased prices during 2026. However, it would be premature to attribute those price hikes directly to the current memory shortage.

The bigger concern is what happens from here.

As Indian cars get more connected, more electric and more technologically advanced, the amount of semiconductor content in each vehicle is likely to increase. A basic hatchback may not need the same amount of computing hardware as a premium electric SUV with multiple screens, ADAS, 5G connectivity and dozens of electronic control systems.

That means a memory shortage may not add thousands of rupees to every car in the same way. Instead, its impact could vary depending on how much electronic hardware a particular vehicle uses.

A mass-market car with a relatively simple infotainment system could be less exposed, while a technology-heavy EV or premium SUV could have a much larger memory bill.

The irony of the smarter car

There is an interesting irony here. The automotive industry is trying to make cars smarter, safer and more connected. But the technology required to do that is increasingly competing with another industry that is growing even faster.

AI needs memory to train and run its models. Cars need memory to process sensor data, run ADAS, power digital cockpits and support increasingly complex software.

And with both industries looking for the same pool of semiconductor resources, carmakers could find themselves paying more to build the brains of their next-generation vehicles.

So, while the next price hike on your new car may still be blamed on the usual suspects such as raw material costs, currency movements or logistics, memory chips could quietly become another reason why cars are getting more expensive.