Billions spent and hypothetical returns: the AI boom explained with six charts

Global spending on artificial intelligence is projected to more than double to $1.6tn by 2031, according to Goldman Sachs, as a concentrated group of tech stocks reshapes the U.S. equity market and adoption among businesses surges to nearly 80% [1]. The S&P 500 has climbed nearly 80% over the past five years, a rally propelled by a handful of companies with direct exposure to AI. Jim Bianco of Bianco Research found that 41 AI-related stocks now represent close to half the benchmark’s market value [1]. Neil Wilson, an analyst at Saxo UK, described the dynamic in stark terms. “The entire market has become one giant AI edifice,” he said [1]. The so-called Big Five—Microsoft, Apple, Alphabet, Amazon, and Meta—already made up roughly a quarter of the S&P 500 in 2019, a concentration that has only intensified since [4]. Corporate adoption of AI tools has accelerated sharply. McKinsey reports that the share of companies using AI rose from 33% in 2023 to nearly 80% today [1]. Consumer uptake has also set records. OpenAI’s ChatGPT reached 1bn monthly active users, a milestone no other app has matched, according to Sensor Tower data [1]. Anthropic, meanwhile, is gaining ground. Internet analysis firm Kentik tracked Claude’s user traffic growing significantly faster than ChatGPT and Google’s Gemini between January and April, projecting it could overtake ChatGPT by summer [1]. The capital required to sustain this expansion is immense. Goldman Sachs estimates current AI spending at $765bn, rising to $1.6tn in 2031 [1]. Datacentre construction underpins that growth. Bloomberg calculates that 23GW of capacity was under construction globally in 2025, while property firm JLL forecasts an additional 100GW will be added between 2026 and 2030—equivalent to 1,200 new facilities [1]. Cecilia Rikap, an associate professor at University College London, questioned whether governments have fully accounted for the feasibility and environmental cost of such a buildout. “Has the government calculated whether such an expansion is feasible? Do they have the money to do it? Have they taken into account the associated environmental damage?” she asked [1]. The economic footprint of the boom is already visible in national accounts. A Harvard economist calculated that investment in information processing equipment and software accounted for 92% of U.S. GDP growth in the first half of 2025, even as the Trump administration pursued mass layoffs of civil servants through the Department of Government Efficiency [1][3]. Amazon, one of the largest private employers in the United States and a major cloud-computing provider through AWS, exemplifies the kind of diversified tech platform channeling resources into AI infrastructure [5]. Cost pressures are mounting on the user side. OpenAI prices GPT-5.5 at $5 per million input tokens and $30 per million output tokens [1]. Liam Betsworth, founder of British AI startup Pendra, said developers in his circle rapidly escalate from the cheapest subscription to the most expensive package. “The costs are getting completely out of control,” he said [1]. Axios reported on an unnamed company that spent $500m in a single month on Claude Code licenses [1]. Despite the spending, the link between AI capability and workforce displacement remains tenuous. Research organization METR finds that AI models are doubling in capability every four months, with Anthropic’s Claude Mythos model reaching a 50% success rate on tasks that would take a human expert between eight hours and two days [1]. Bouke Klein Teeselink, an academic at King’s College London, said bottlenecks in trust and legal responsibility are slowing adoption. “We are very much at the early stages of the AI revolution still. There are many people doing tasks that could be done by an AI. The amount of change we are going to see will be huge,” he said [1].