The automotive industry’s enthusiasm for AI is set for a sharp correction over the next five years, according to Gartner. While nearly every major automaker today is pouring resources into AI, only 5% will continue investing aggressively beyond 2029, driven by a growing divide between companies with mature software foundations and those still struggling with legacy mindset and infrastructure.
Gartner analysts say the current surge in AI spending is driven more by excitement than readiness. Many automakers have set overly ambitious goals without building the technical and organizational maturity required to deliver results. As expectations collide with operational constraints, most OEMs will scale back, leaving only a handful of global leaders to define the next era of AI-driven automotive innovation.
AI Leaders Will Pull Ahead as the Divide Widens
Pedro Pacheco, VP Analyst at Gartner, warns that companies with strong in-house software capabilities and technology-driven leadership will be the primary beneficiaries of long-term AI value. These players already treat software as a strategic asset, not a support function, and are better positioned to build sustainable AI roadmaps.
In contrast, traditional OEMs still anchored to manufacturing-first models will struggle to justify continued AI investment once the expected disruptive gains fail to materialize. Gartner expects consolidation and reprioritization across the sector as firms reassess the cost-benefit equation of AI initiatives.
Fully Automated Vehicle Assembly Expected by 2030
A major shift is also underway in factory automation. Gartner forecasts that by 2030, at least one automaker will achieve fully automated vehicle assembly, driven by advances in robotics, computer vision, and AI-enabled quality control.
Nearly half of the world’s top automakers are already piloting advanced robotic systems. The push for automation is accelerating due to rising labor costs, increasing production complexity, and the demand for faster cycle times. Fully automated assembly lines will shorten manufacturing timelines, lower defect rates, and transform labor requirements.
While automation may reduce the need for traditional assembly-line roles, it will simultaneously create new demand for robotics engineers, AI supervisors, data scientists, and automation specialists. OEMs that invest early in workforce reskilling will have a competitive advantage.
AI Hype Will Give Way to Operational Discipline
As the industry moves past AI hype cycles, automakers will be forced to demonstrate measurable operational benefits. Gartner highlights the need for stronger governance, data readiness, and process modernization to turn AI pilots into scalable, value-generating deployments.
The winners will be companies that approach AI as a long-term capability — rooted in software excellence, robust data pipelines, and leadership alignment — rather than a quick fix for competitive pressure.
