A new study has cast a sharp beam of cold light onto the auto industry’s runaway enthusiasm for artificial intelligence, warning that almost all of today’s aggressive spending will fade long before the end of the decade.
The report, released Monday by technology research firm Gartner, says only a handful of manufacturers have the structure, leadership, and long-term discipline needed to keep pushing deep into AI through 2029. It challenges the optimism that has fueled boardroom strategies, investor narratives, and headline-grabbing claims about self-driving ambitions, in-car intelligence, and automated factories.
According to Gartner, over 95% of automakers today describe themselves as being in a phase of strong AI investment growth. By 2029, that number collapses to just 5%.
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The research is part of Gartner’s predictions for 2026 and suggests that the industry’s current surge of spending is not built on stable foundations. The firm concludes that only companies with strong software cores, tech-oriented leadership structures, and a clear long-term commitment to AI will keep moving forward. Everyone else risks slipping into stagnation.
This widening divide reflects a basic structural problem within the industry. Traditional carmakers such as Volkswagen were built on engineering muscle, decades of mechanical innovation, and manufacturing discipline. They grew into sprawling organizations optimized for hardware, supply-chain mastery, and incremental upgrades to combustion engines. That foundation is now a disadvantage in a world where intelligence, code, and automation increasingly determine who wins.
Gartner’s report argues that the leadership model inside legacy companies is one of the biggest obstacles. Many of these manufacturers adopted software teams only reluctantly, and too often placed them deep within the hierarchy where they lacked influence. Gartner analyst Pedro Pacheco said many firms are still dealing with internal resistance, slow decision cycles, and outdated cultural habits that treat software as an accessory rather than the engine of competitiveness.
He told Reuters that success requires turning these organizations into digital-first companies and clearing away internal roadblocks that slow innovation. That includes giving software leaders a direct line to the CEO and putting technology at the very top of strategic planning. Without that shift, he said, firms will struggle to compete with players like Tesla and BYD, which were built around software from the start.
“A company that is not great at software … is going inevitably to struggle,” Pacheco said, summing up what has become an increasingly accepted truth across the global auto landscape.
The divide is not just about who writes code well. It is about who can sustain the enormous spending required to build industry-leading AI systems. As automakers roll out advanced driver assistance, predictive maintenance, in-car voice systems, automated production lines, and next-generation battery management, their costs increasingly resemble those of the world’s tech giants. That level of spending is difficult to maintain for firms still carrying legacy manufacturing costs, debt burdens, and the weight of combustion-era supply chains.
The industry’s internal structure is colliding with another challenge: a rapidly cooling investor appetite for speculative AI projects. While AI remains the hottest narrative in global markets, investors are no longer impressed by slogans about “software-defined vehicles” unless companies can produce genuine revenue improvements. Many automakers who rushed into grand AI announcements now face pressure to justify the billions they have already committed.
The risk heading into 2026 is that companies trapped between rising costs, slow cultural change, and shifting investor sentiment may pull back from ambitious projects before they yield results. That could stall unfinished automation systems, slow the rollout of next-generation EV capabilities, and weaken attempts to develop in-house operating systems. Companies that hesitate now will only widen the gap with Tesla, BYD, and the small group of tech-forward newcomers who view AI as their native territory rather than a strategic add-on.
This trend also affects long-term competitiveness. If only 5% of the industry maintains strong AI investment growth by 2029, the rest may find themselves dependent on external suppliers for critical vehicle intelligence. That would push them closer to becoming low-margin hardware assemblers in a market where the value sits inside the software stack. Carmakers who cannot build or control their own AI systems risk losing pricing power, market influence, and brand authority.
These pressures are reshaping the competitive environment faster than expected. Tesla continues to treat software as its core operating system, using continuous over-the-air updates and integrated data loops to make each vehicle smarter over time. BYD is expanding this model at an enormous scale, blending advanced electronics with aggressive production growth in China and beyond. Their momentum amplifies the urgency felt by legacy manufacturers struggling through internal reform.
The “euphoria” described in the Gartner report has driven carmakers to announce sweeping AI ambitions. But the coming years will test whether they can pay for those promises, reorganize their cultures, and compete with companies forged in the language of code. The report’s numbers suggest the vast majority will fall short.
The auto sector enters 2026 with two realities pulling in opposite directions. One is the growing expectation that vehicles will soon operate with meaningful autonomy, predictive intelligence, and self-improving software. The other is the industry’s internal difficulty in transforming itself fast enough to deliver that future. If Gartner’s forecast holds true, the next three years will be decisive—and only a tiny fraction of automakers will emerge with the strength, vision, and long-term discipline to remain competitive in the AI race.
The rest may find themselves watching from the sidelines as a new hierarchy takes shape.