Using AI seems fairly straightforward: you pay a flat fee and prompt to your heart's content. This creates the impression that AI costs next to nothing. The logical conclusion is that AI could replace an arbitrarily large number of human work hours or workers, because it must surely be cheaper.
That illusion is now bursting. Data centers consume land and enormous amounts of energy. The investment bank Morgan Stanley estimates that the global construction of data centers alone could cost around $2.9tn by 2028. This is driven by demand for compute – that is, demand for processing power, which manifests in concrete, tangible form as chips, servers, electricity and data centers that train AI models and handle requests. Here, demand currently far exceeds supply.
It is a gold rush market, but the prices for the tools are rising just as fast as the need to generate profits. The capital required can only be raised on stock markets. Shareholders want to see dividends and share price gains. For this reason alone, AI providers cannot permanently hide their costs behind flat-rate subscriptions.
The Hidden Price Tag
The technology is expensive – the training, IT security, quality control and much else besides. Behind the scenes lie enormous fixed costs. Graphics processing units (GPUs), servers, data centers, cooling, electricity, networks, storage and financing all need to be paid for. Morgan Stanley therefore describes the AI expansion less as normal software scaling and more as an industrial infrastructure boom. Amid the founder frenzy, AI is experiencing the same effect that the early internet once went through: it gives the impression of costing almost nothing, yet proves, when all is said and done, quite expensive.
