Elon Musk has publicly criticized legacy automakers for not licensing Tesla’s Full Self-Driving (FSD) software, calling their reluctance “crazy” in a November post on X. However, recent industry developments reveal that automakers are strategically choosing to develop their own autonomous driving AI systems rather than outsourcing to Tesla, viewing vehicle technology as a brand-defining competitive advantage.
Rivian is taking vertical integration to new heights by designing a proprietary chip for its autonomous driving computer. CEO RJ Scaringe announced at Rivian’s Autonomy & AI Day in early December that the company is even considering entering the robotaxi business, signaling ambitious plans for AI-powered autonomous vehicles.
Ford announced at CES 2025 that it plans to develop eyes-off driving software for public roads by 2028, bringing development in-house to cut costs by 30% while gaining greater control over software integration and deployment. Paul Costa, Ford’s head of electrical engineering, emphasized that in-house development enables the company to achieve “smaller, cheaper, and higher performance” systems simultaneously without coordinating multiple suppliers.
Industry experts explain the strategic rationale behind this trend. Chris Ahn, a principal at Deloitte, notes that automakers must decide what level of autonomy their specific customer base wants and how to achieve it—whether through lidar or camera-only systems like Tesla’s approach. “This is a competitive business for them,” Ahn explained, emphasizing that Ford owners and Mercedes owners have different expectations that each brand must address uniquely.
Steve Man, a senior auto analyst for Bloomberg Intelligence, describes the autonomous vehicle technology stack as three interconnected components: software, sensors, and actuators. Integration challenges make in-house development more cost-effective than managing multiple suppliers, Man argues.
Nvidia’s new Alpamayo platform is making autonomous driving development more accessible. Introduced at CES, Alpamayo provides AI reasoning models, simulation tools, and datasets that automakers can use to build self-driving technology. Mercedes-Benz became Nvidia’s first major customer, planning to launch a Tesla FSD-level advanced driver assistance system (ADAS) built on Alpamayo by year’s end. Hugh Nguyen, a KPMG partner specializing in autonomous driving systems, says Alpamayo “democratizes” AV development by reducing training costs and time.
Nvidia CEO Jensen Huang praised Tesla FSD as “completely world-class” while clarifying that Nvidia aims to “enable the world’s autonomous industry” rather than compete directly as a self-driving car company.
Key Quotes
When legacy auto does occasionally reach out, they tepidly discuss implementing FSD for a tiny program in 5 years with unworkable requirements for Tesla, so pointless
Elon Musk posted this on X in November, expressing frustration that legacy automakers show minimal interest in licensing Tesla’s Full Self-Driving technology and impose requirements that make partnerships impractical.
To integrate, I can’t do this with all these suppliers. We need to bring this stuff in-house, and it allows for this ability to do the trifecta at once: smaller, cheaper, and higher performance
Paul Costa, Ford’s head of electrical engineering, explained to Business Insider why the company is developing autonomous driving software internally rather than licensing external solutions, emphasizing the integration and cost benefits.
It’s not so much like, ‘I’m taking it in-house because I don’t want to use somebody’s technology.’ But this is a competitive business for them. People who own Fords own Fords for certain reasons that are probably different reasons than why people who own Mercedes own Mercedes
Chris Ahn, a principal at Deloitte who consults for major automakers, explained that in-house AI development allows each brand to tailor autonomous driving features to their specific customer base and brand identity.
We’re not a self-driving car company. We just want to enable the world’s autonomous industry. Everything that moves should be autonomous
Nvidia CEO Jensen Huang clarified at CES that while he considers Tesla FSD “completely world-class,” Nvidia’s strategy is to provide AI tools and platforms that enable all automakers to develop their own autonomous systems rather than competing directly.
Our Take
The automakers’ rejection of Tesla FSD licensing represents a fundamental shift in how the industry views AI as a competitive moat. Rather than treating autonomous driving as a feature to be purchased, companies like Ford and Rivian recognize it as core intellectual property that defines brand identity and customer experience. Nvidia’s strategic positioning is particularly astute—by providing the picks and shovels for the autonomous driving gold rush through Alpamayo, they avoid direct competition while capturing value across the entire industry. This mirrors successful AI infrastructure plays in other sectors. The 30% cost savings Ford projects challenges conventional wisdom about build-versus-buy decisions in AI, suggesting that integration complexity and supplier coordination costs can outweigh the advantages of licensing proven technology. Tesla’s FSD may be world-class, but in automotive AI, customization and control trump technical superiority. This fragmentation could either accelerate innovation through competition or delay widespread autonomous vehicle adoption through duplicated efforts.
Why This Matters
This story reveals a critical inflection point in the automotive AI industry where traditional automakers are rejecting third-party solutions in favor of proprietary autonomous driving systems. The shift demonstrates that AI-powered vehicle technology has become a core competitive differentiator rather than a commodity that can be licensed.
The emergence of platforms like Nvidia’s Alpamayo lowers barriers to entry for autonomous vehicle development, enabling more automakers to build custom AI systems tailored to their brand identity and customer expectations. This democratization of AV technology could accelerate the timeline for widespread autonomous driving adoption while fragmenting the market across multiple competing AI approaches.
For the broader AI industry, this trend illustrates how companies increasingly view AI capabilities as strategic assets that must be developed internally rather than outsourced. The 30% cost savings Ford projects from in-house development also challenges assumptions that licensing established AI systems is always more economical. As autonomous driving technology matures, the battle for AI supremacy in vehicles will be fought through proprietary systems rather than a single dominant platform, with significant implications for AI chip makers, software developers, and the future of transportation.
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Source: https://www.businessinsider.com/elon-musk-tesla-fsd-licensing-adas-autonomy-legacy-automakers-2026-1