AI investment in auto industry may collapse by 2029, warns report

A new Gartner report has predicted that by 2029, only 5 per cent of automakers will maintain strong AI investment growth, starkly less than the 95 per cent currently engaged

The $100-billion-plus surge in investment across artificial intelligence and automation in 2025, widely hailed as the next industrial revolution, is beginning to show cracks. From corporate boardrooms to assembly lines, the AI-hype cycle appears to be slowing. Global research and advisory firm Gartner has issued a stark forecast: by 2029, only 5 per cent of automakers will maintain strong AI investment growth, a sharp decline from the more than 95 per cent currently engaged.

 

The warning comes alongside broader signals of over-exuberance in financial markets, strengthening concerns that the AI gold rush may be fundamentally unstable.

AI foundations missing in auto sector

 

In its report released on Monday (December 8), Gartner said the auto sector is experiencing an “AI euphoria", with companies rushing to announce bold AI and software-driven strategies without building foundational data and software capacities. Gartner’s VP-analyst Pedro Pacheco noted that “many want to achieve disruptive value even before building strong AI foundations".

 

According to the report, only a small minority of automakers with mature software infrastructure, data capabilities, tech-savvy leadership and long-term commitment will sustain heavy AI initiatives after the next five years. The rest may scale back or abandon ambitions. Legacy manufacturers rooted in mechanical engineering may struggle to match newer tech-focused rivals.

 

The report also predicted that by 2030, at least one automaker will achieve fully automated vehicle assembly, highlighting automation’s potential for radical efficiency. However, this will require substantial investment in robotics, digital infrastructure and re-skilling.

Is AI-bubble heading for a collapse?

 

The auto industry’s trajectory mirrors broader corporate experience. Earlier in August, an MIT report found that 95 per cent of generative-AI projects failed to deliver meaningful financial returns. Companies poured tens of billions into pilots, but only about 5 per cent generated revenue or productivity gains.

 

Many firms attempted to integrate AI tools into existing workflows with minimal adaptation, leading to poor integration, employee resistance and limited transformation.

 

A Reuters analysis in November reported a sharp pull-back in AI-linked stocks, noting that the rally fuelling indices such as the Nasdaq is beginning to resemble the early stages of the dot-com bubble. Traditional valuation metrics like the market capitalisation-to-GDP “buffett indicator” have climbed to levels seen before previous crashes.

 

Meanwhile, a Bank of America survey of global asset managers in October found more than half consider AI a speculative bubble, with 45 per cent identifying it as the biggest tail-risk for portfolios heading into 2026.

 

Economists have warned that if projected AI revenues fail to materialise, a correction could ripple through credit markets, equity valuations and even affect non-tech sectors.

Are there still positives despite the risks?

 

Analysts note that despite turbulence, the structural investments being made, such as data centres, high-performance computing, cloud networks, will form a durable long-term asset base. Firms that invest sensibly, avoid heavy leverage and focus on practical AI deployment rather than hype are likely to emerge stronger.

 

The forecast for the automotive sector from Gartner may seem like an industry-specific caution. If automakers with deep pockets, long product cycles and strong market positions start retreating, that suggests major structural limits to what AI investment alone can deliver. If it combines with the mounting evidence from corporate AI rollouts, plunging returns, market pullbacks, heavy debt, and circular financing, the fear of a much larger AI correction begins to look credible.