AI industry needs $6 trillion in annual revenue by 2031 To justify infrastructure boom

The global artificial intelligence industry will need to generate about $6 trillion in annual revenue by 2031 to justify the enormous investments being made in data centres and other AI infrastructure, consulting firm Bain & Company said in its annual global technology report.

Existing consumer and enterprise AI services could generate up to $1.8 trillion of that amount, leaving the industry with a potential $4.2 trillion revenue gap that would need to be filled by new applications and business models, Bain said on September 29, The National writes.

The additional revenue could come from emerging areas including autonomous machines, robotics, drug discovery, mental health and energy generation.

“What the industry needs is a wave of innovation that will dwarf what mobile and cloud unlocked,” said David Crawford, the report’s lead author and chairman of Bain’s global technology, media, and telecommunications practice.

“AI infrastructure is being built well ahead of the demand curve and funding it sustainably will require adding approximately 1 per cent to the annual global GDP growth rate,” he said.

Bain’s assessment highlights the challenge facing the AI industry as companies race to expand computing capacity while questions grow over the financial returns from AI services.

Microsoft, Alphabet’s Google, Amazon, Meta Platforms and Oracle are among the companies investing heavily in data centres to meet growing demand for AI computing.

The size and cost of data centres are doubling roughly every 12 to 16 months, Bain said, citing rising prices for chips from companies including Nvidia and SK Hynix, as well as networking equipment and other components.

The report comes amid increasing debate over whether AI companies can generate sufficient returns to support the scale of investment flowing into the sector.

While much of the current discussion focuses on AI-driven productivity gains, Bain said the economics of the infrastructure build-out will require trillions of dollars in additional revenue beyond productivity improvements.

The consultancy estimates that global spending on data centres could reach $5 trillion to $6.5 trillion by 2030. That investment would add at least 150 gigawatts of capacity and place additional pressure on national energy resources.

Annual spending on AI infrastructure — including data centres, computing capacity and upgrades to accelerator and memory chips — could reach as much as $1.5 trillion by 2031, according to the report.

However, expanding infrastructure is already facing physical constraints.

Data-centre developers are encountering shortages of transformers, water and electricity supplies, while opposition from local communities is delaying or blocking projects.

In the United States alone, local opposition blocked or delayed $68 billion worth of data-centre projects during the June quarter, Bain said.

The infrastructure boom therefore faces a central economic question: whether the AI industry can create enough new applications and revenue streams to support the enormous capital being committed to its expansion.

For Bain, the answer will depend on whether AI moves beyond its current uses and generates entirely new markets capable of absorbing the scale of investment now flowing into the technology.

By Sabina Mammadli