AI market needs to make $6 trillion a year by 2031 to fund its infrastructure habit

The AI sector must generate $6 trillion in annual revenue by 2031 to sustain the infrastructure required to meet projected demand, according to a prediction from management consultants Bain & Company. This figure stems from their 2026 Global Technology Report, which imagines various non-productivity uses for AI, beyond enhancing employee efficiency.

Bain posits that the soaring demand for AI compute infrastructure has reinvigorated the hardware industry, with high-bandwidth memory, advanced packaging, custom silicon, and application-specific integrated circuits scaling rapidly. Datacenter infrastructure and model development now represent significant growth areas for the US economy, fueling a "arms race" among AI-focused tech giants, with capital expenditure by Microsoft, Google, Amazon, Meta, and Oracle potentially reaching $780 billion in 2026.

By 2031, Bain estimates AI infrastructure spending could swell to $1.5 trillion, aligning closely with Omdia's $1.6 trillion forecast. To reach this ambitious revenue target, Bain assumes that capital expenditure will constitute roughly 25% of industry revenue, a share they deem plausible based on cloud provider trends. While existing AI applications, like consumer and enterprise uses, are expected to generate between $1.2 trillion and $1.8 trillion in revenue, a significant $4.2 trillion revenue gap remains to be addressed.

Bain identifies four potential avenues to fill this gap: AI-driven revenue streams from search engines and ads, autonomous vehicle and drone automation, physical AI applications such as simulations, digital twins, and robotics, and emerging AI uses like drug discovery, mental health support, materials science advancements, and scientific research breakthroughs.

However, the path to attaining a $6 trillion AI industry by 2031 remains uncertain, as AI rollouts reportedly yield mixed results and doubts persist over the realization of infrastructure projects.