Artificial intelligence companies could face a combined annual revenue gap of $800 billion by 2030, according to a new report from the consulting firm Bain & Co. The firm estimates that the industry will need $2 trillion in yearly revenue to finance the computing power required for projected demand. Bloomberg reports that these findings are detailed in Bain’s annual Global Technology Report.
The predicted shortfall stems from the massive and rapidly growing costs of data centers and related infrastructure. Bain suggests that efforts to monetize AI services like ChatGPT are not keeping pace with these enormous expenses. This raises questions about the AI industry’s current valuations and long-term business models. The increasing popularity of AI services from companies like OpenAI and Google is driving demand for computing capacity and energy at a staggering rate.
“If the current scaling laws hold, AI will increasingly strain supply chains globally,” said David Crawford, chairman of Bain’s global technology practice.
This demand is spurring massive investment. According to Bloomberg Intelligence, major tech firms including Microsoft, Amazon, and Meta are on track to increase their combined annual AI spending to over $500 billion by the early 2030s. To meet demand, global AI computing requirements could reach 200 gigawatts by 2030, with the US alone accounting for half of that, Bain said. Besides infrastructure, leading AI companies are also investing heavily in product development, such as autonomous AI agents.