The auto industry is speeding up the expansion of artificial intelligence (AI) features, but cases that translate into actual revenue remain limited, an analysis showed. Automakers have invested for years in voice assistants, connected cars and predictive systems, but higher usage is adding to operating cost burdens, making profitability a key challenge. On May 24, local time, blockchain media outlet Cryptopolitan reported that a live survey conducted during an SBD Automotive webinar found most participants said only about 18 percent of current in-car AI features generate revenue. Automakers have applied various AI technologies to vehicles, including voice recognition tools, driver prediction systems, digital shopping functions and connected services. But building the technology and generating stable revenue from it are entirely different issues, the analysis said. Robert Fisher of SBD Automotive said, "Car AI itself is not a new concept," but added, "Making AI pay for itself is still very difficult." The industry’s biggest burden is operating costs. In-vehicle hardware involves relatively little additional cost after initial installation, but AI features incur cloud computing costs each time they are used. Costs rise as voice command processing, route recommendations, predictive functions and connected services are repeatedly called. Andy Chiu of SBD Automotive said, "This is not a simple technical issue but an income statement issue," and explained that "the core task for car AI is ultimately profitability management." He pointed in particular to a structure in which the more successful AI features are, the larger the cost burden becomes. Chiu said, "Every time users interact with AI features, the cloud meter runs," adding, "This is not a one-off capital investment but operating costs that occur every day." If AI features fail, only research and development costs remain, and even if they succeed and usage rises, operating cost burdens can surge, the analysis