Goldman Sachs has cast doubt on the economic viability of AI investments, despite substantial spending on AI infrastructure. The firm estimates around$1 trillion will be spent on AI-related infrastructure, including data centres, semiconductors, and grid upgrades. However, Goldman Sachs raises a crucial question: what problem will this massive AI investment actually solve?

According to Jim Covello, head of global equity research at Goldman Sachs, the current scenario contrasts sharply with past technological transitions. He argues that while the internet revolutionised commerce by offering low-cost solutions, AI today is exceedingly expensive and lacks clear applications capable of justifying its high costs. Covello highlights concerns that investor enthusiasm may wane if substantial AI use-cases fail to materialise within the next 12 to 18 months.

Despite these reservations, Kash Rangan of Goldman Sachs acknowledges that the AI cycle is still in its early stages, primarily focused on building infrastructure rather than discovering groundbreaking applications. He remains optimistic that as the AI ecosystem matures, a transformative 'killer application' will eventually emerge.

Looking forward, Goldman Sachs anticipates that the ongoing AI build-out will exert considerable pressure on national grids and electricity consumption. The report forecasts a 2.4% compound annual growth rate in UK electricity demand and projects that data centres will double their electricity consumption by 2030, underscoring the immediate impacts of AI infrastructure development on energy resources.

While AI holds potential for revolutionary advancements, Goldman Sachs suggests that its current trajectory raises fundamental questions about economic feasibility and the pace of transformative breakthroughs needed to justify its substantial investments.