Auto AI hype runs ahead of profits as adoption costs bite

Source Cryptopolitan

Most auto AI features are still not paying their own bills, even after years of investment across voice tools, driver prediction systems, connected car services, and digital shopping products.

A live poll run during an SBD Automotive webinar found that only 18% of AI features are profitable for most attendees.

See, automakers can build AI, no one is arguing that in the year 2026, but getting those tools to earn more than they cost is an entirely different story. SBD Automotive’s Robert Fisher said, “AI in automotive is nothing new. But making AI pay for itself is still very difficult.”

Automakers keep paying cloud bills each time drivers use AI tools

SBD Automotive’s Andy Qiu said the industry is looking at the wrong problem when it talks about AI inside cars. “This is not a technology problem,” Andy said. “It’s a P&L problem.”

The point here is that these capabilities of artificial intelligence are not just a one-off investment into new hardware. Unlike other hardware in the car, which once installed becomes silent, the artificial intelligence in the car does not become silent every time its functions are used. Each voice request, route planning, forecast, or connection can entail additional costs through the cloud.

“Every time a user interacts with an AI feature, your cloud meter is running. That’s not capex anymore. That’s ongoing opex every day, forever,” Andy said.

It raises an interesting business dilemma. In case of failure, the feature is an expense item for R&D. Yet in case of success, usage could drive up the cost of operations. Thus, the automobile manufacturer would need to prove that the technology generates sufficient revenue, loyalty, data value, subscription fees, or sales assistance.

Andy noted that most of the manufacturers do not have proper cost management per each individual AI component. This could mean that they would fail to identify which solutions harm margins. Andy referred to it as a portfolio issue, as the solution remains in the portfolio because it looks good in the product launch presentation although customers hardly ever use it.

Andy divided automotive AI solutions into four categories. First is heroes, which have value, generate profit, and require further growth. Second is utilities, which assist users, yet customers assume they should be offered free of charge. Third is zombies, which cost too much to produce while being used infrequently. The last is grudges, making the customer experience worse.

Nissan cuts EV powertrain plans as shoppers still test AI car search

The AI profit problem is landing while the wider auto market is already dealing with weak demand in some expensive product lines. JATCO, a unit of Nissan Motor (OTC: NSANY), has dropped its plan to make electric vehicle powertrains in Sunderland, Britain, after slower demand for Nissan EVs in Europe.

The company revealed the project in January 2025. JATCO planned to invest 48.7 million pounds ($65.39 million), and the project would produce up to 340,000 EV powertrain units annually. Each unit would include an integrated motor, inverter, and reducer for Nissan vehicles.

On the retail end, consumers are experimenting with AI, while manufacturers attempt to perfect the technology. In November 2025, Cars.com Inc. (NYSE: CARS) conducted a survey following the launch of Carson, the AI car search tool.

As per the survey conducted on in-market shoppers and new buyers, 44% used AI-powered car-search tools on platforms such as Cars.com while searching for vehicles. In addition, 71% expressed having moderate to high levels of trust in AI-based tools for reliable information about vehicles.

However, there is a caveat. Approximately half of regular AI users felt comfortable with AI tools suggesting a car and its cost. On the other hand, only 22% stated that they would verify the AI’s suggestion. Simultaneously, 63% feared that AI tools would suggest some biased recommendations.

Regarding the sources of neutral vehicle information, the survey showed that two-thirds of shoppers trusted car-selling and car-review websites. Having used AI-based search tools like Carson, 41% of car shoppers were inclined to visit websites run by dealerships or manufacturers afterward.

When it comes to vehicle suggestions, shoppers are open to salespeople providing them. However, not less than 64% of shoppers welcomed suggestions related to the cost and financing from dealers.

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