Artificial intelligence companies like OpenAI have announced hundreds of billions of dollars in data center investment plans, but progress in generating revenue to cover these costs remains sluggish. Now, consulting firm Bain has released calculations suggesting this revenue gap may be larger than previously anticipated.
In its annual Global Technology Report released Tuesday, Bain noted that by 2030, AI companies collectively need to achieve $2 trillion in annual revenue to fund the computing power required to meet expected demand. However, Bain predicts that due to the slow commercialization of services like ChatGPT compared to spending demands for data centers and related infrastructure, these companies' revenue may fall $800 billion short of this target.
The report could spark further questions about AI industry valuations and business models. Currently, as services like OpenAI's ChatGPT and Google's Gemini become increasingly prevalent and global enterprises deploy AI initiatives, computing power and energy demands are rapidly escalating. However, cost savings from AI and companies' ability to generate additional revenue through AI have not kept pace with this growth.
"If current scaling patterns continue, AI will create increasingly severe pressure on global supply chains," said David Crawford, Bain's global technology practice chair.
OpenAI currently loses billions of dollars annually and prioritizes growth over profitability, though the company expects to achieve positive cash flow by 2029. However, Bain did not analyze potential impacts if AI companies fail to achieve profitability by 2030.
According to Bloomberg Intelligence data, by the beginning of the next decade (before 2030), tech giants including Microsoft (MSFT.US), Amazon (AMZN.US), and Meta (META.US) will increase their combined annual AI spending to over $500 billion.
Companies like OpenAI and DeepSeek continue launching new models, both stimulating market demand for AI services and driving increased industry investment. Bain noted that by 2030, global incremental AI computing demand could surge to 200 gigawatts (GW), with the United States accounting for half of this capacity.
While technological and algorithmic breakthroughs may help alleviate this pressure, supply chain constraints or insufficient power supply could still hinder the AI industry's development progress.
Beyond computing investments, leading AI companies are also investing heavily in product development. "Autonomous AI agents" represent one key focus area - these agents can complete multi-step tasks like humans with limited guidance. Bain expects that over the next 3-5 years, enterprises will allocate up to 10% of their technology spending toward building core AI capabilities, including agent platforms.
Beyond AI services, Bain's annual technology report also predicts growth in areas like quantum computing. The report states this emerging technology could create a total market value of $250 billion across industries including finance, pharmaceuticals, logistics, and materials science.
While some expect quantum computing to achieve a single breakthrough advancement, Bain believes its development will follow a gradual curve: over the next 10 years, quantum computing will first achieve initial applications in specific niche areas, then gradually expand its application scope.
Bain noted that humanoid robots are attracting substantial capital investment with increasing adoption rates, but remain in early deployment stages and heavily dependent on human supervision. The consulting firm indicated that the commercial success of humanoid robots will depend on ecosystem maturity, with companies conducting early robot pilots positioned to gain industry leadership.