General Motors is moving beyond its Google partnership to develop its own artificial intelligence system for vehicles, signaling a shift toward proprietary technology that could give the automaker greater control over customer data and vehicle functionality.
The company plans to launch a native AI assistant later this year that integrates directly with GM vehicles in ways the Gemini chatbot from Google cannot match. Anna Santos, GM director of product management of voice and AI/machine learning, explained the strategic difference: "Later this year, we'll be launching a more deeply integrated native AI assistant that combines conversational AI with GM vehicle knowledge and OnStar intelligence to create those capabilities that go beyond what a general purpose assistant can do."
The distinction matters. While Gemini—which launches this year in millions of 2022 model-year vehicles and newer—operates largely like a smartphone assistant with natural conversation and basic vehicle controls like temperature and radio, GM's proprietary system aims deeper. "There's a limit to what an AI that's just sort of sitting at the top level of the vehicle can do," Santos said.
Building Competitive Advantage Through Data
GM is partnering with an unnamed large language model provider to develop technology focused on predictive maintenance, vehicle telemetry, and vehicle-specific features that Gemini simply cannot provide. The company declined to name the new assistant, but Santos made clear the strategy centers on proprietary data and vehicle expertise. "It's data that's going to be proprietary to GM, and our goal is to make sure that we're bringing the right technology forward to enable us to build the deep vehicle expertise that we want to be able to bring to the AI assistant."
This approach reflects a broader business calculation: rather than rely on a third-party AI provider, GM is investing to own the technology layer that interacts most directly with its customers. The system could eventually handle commands like "kids setting," automatically adjusting music, seats, heating and cooling, and door locks for children—functionality that requires intimate knowledge of a vehicle's systems.
Santos framed the initiative as foundational. "This is the beginning of a broader AI journey for us." The timeline suggests GM recognizes it's playing catch-up in a competitive space where vehicle-specific AI capabilities could become a meaningful differentiator.
Defense Tech Attracts Private Capital
Separately, the defense technology sector is drawing significant private investment. Space-Eyes, an Eric Trump-backed defense technology company specializing in AI-enabled systems like drone detection and autonomous platforms, is set to go public through a $638 million SPAC deal announced on July 31, 2026.
The transaction reflects broader investor appetite for AI-powered defense innovations. As military and civilian security applications for autonomous systems expand, companies positioned at the intersection of artificial intelligence and defense technology are attracting capital from both traditional defense investors and newer venture backers.
Why This Matters:
GM's decision to build proprietary AI rather than remain dependent on Google represents a crucial shift in how major manufacturers view technology strategy and customer relationships. By owning the AI layer, GM retains control over vehicle data, customer interactions, and the competitive advantage that comes from vehicle-specific functionality. This approach aligns with sound business practice: companies that own their core technology platforms reduce reliance on external partners and preserve margins. The $638 million SPAC deal for Space-Eyes signals that private markets see genuine commercial opportunity in AI-enabled defense technologies, suggesting these aren't speculative bets but rather responses to genuine demand. Both developments reflect how artificial intelligence is becoming embedded in competition across industries—automotive, defense, and beyond—where companies that develop proprietary capabilities rather than licensing generic solutions will likely capture greater value.