The surge in artificial intelligence (AI) and automation investments, surpassing $100 billion in 2025, has been hailed as a transformative industrial revolution. However, early signs indicate that the AI hype cycle in the automotive sector is slowing down.
Global research and advisory firm Gartner has issued a stark warning: by 2029, only 5 per cent of automakers are expected to maintain strong AI investment growth, a dramatic drop from over 95 per cent currently engaged.
This forecast raises serious questions about the sustainability of the AI gold rush amid over-exuberance in financial markets.
According to Gartner’s December 8 report, the auto industry is currently experiencing an “AI euphoria”. Companies are racing to announce ambitious AI and software-driven strategies without establishing robust data and software infrastructures. Gartner VP-analyst Pedro Pacheco remarked, “many want to achieve disruptive value even before building strong AI foundations”.
Only a small subset of automakers, equipped with mature software systems, advanced data capabilities, tech-savvy leadership, and long-term commitment, are likely to sustain heavy AI initiatives over the next five years. Legacy manufacturers, rooted in traditional mechanical engineering, may struggle to compete with newer, tech-focused rivals.
The report predicts that by 2030, at least one automaker could achieve fully automated vehicle assembly, unlocking significant efficiency gains. However, this milestone requires substantial investments in robotics, digital infrastructure, and workforce reskilling.
The automotive industry’s AI trajectory mirrors broader corporate trends. A report from MIT in August highlighted that 95 per cent of generative-AI projects failed to deliver significant financial returns. While companies invested tens of billions into AI pilots, only 5 per cent generated tangible revenue or productivity gains.
Many firms attempted to embed AI into existing workflows with minimal adaptation, leading to poor integration, employee resistance, and limited operational transformation.
Reuters’ analysis in November noted a sharp pullback in AI-linked stocks, with AI-driven rallies resembling early stages of the dot-com bubble. Traditional valuation metrics, like the market capitalization-to-GDP ratio (“Buffett Indicator”), have reached levels previously seen before major market crashes.
A Bank of America survey in October found that over 50 per cent of global asset managers view AI as a speculative bubble. About 45 per cent identified it as the biggest tail-risk for portfolios heading into 2026. Economists warn that if projected AI revenues do not materialize, it could trigger corrections across credit markets, equity valuations, and even non-tech sectors.
Long-Term Structural Investments
Analysts emphasize that despite near-term turbulence, investments in data centers, high-performance computing, and cloud infrastructure will create lasting assets for companies. Firms that prioritize practical AI deployment, avoid excessive leverage, and invest strategically are likely to emerge stronger.
Gartner’s caution suggests structural limits on what AI investment alone can deliver. Even major players with strong market positions and deep pockets may face constraints if AI funding retreats. Coupled with plunging returns, market pullbacks, and complex financing, the potential for a larger AI correction becomes increasingly plausible.
The AI investment wave in the automotive sector has sparked a global industrial buzz. Yet, Gartner’s report highlights the risks of overhype and insufficient foundational readiness. While AI and automation hold transformative potential, only a minority of automakers are positioned to reap sustained benefits. Companies that balance innovation with robust infrastructure, careful risk management, and realistic deployment strategies are likely to navigate the coming challenges successfully. The next five years will determine which automakers can turn AI ambition into tangible, long-term value.