Are we in an AI bubble?

Recent swings on the US share market have investors asking whether artificial intelligence (AI) is driving a genuine productivity revolution—or inflating another speculative bubble. 

Over the past year, AI-focused stocks have attracted enormous investment as fund managers, retail investors and private equity houses seek investment in companies promising breakthroughs in generative AI, large language models and automation tools. 

This is evidenced by the growth of the Magnificent Seven; Apple, Microsoft, NVIDIA, Alphabet (Google), Amazon, Meta and Tesla. These companies invest heavily in AI and the collective share price of these seven has grown around 25% over the last 12 months. These seven companies currently represent around 35% of the US share market. 

Enthusiasm in AI has lifted valuations, often far beyond near-term earnings, making markets more sensitive to news, guidance and hype. There are clear reasons for this excitement as AI applications reshape industries, from customer service automation to drug discovery.  

Yet the speed of share price growth for many of these companies has detached from the underlying fundamentals. High price-to-earnings ratios, sky-high revenue multiples for early-stage investment, and heavy retail participation all echo classic bubble dynamics. This results in a large amount of volatility when analysts temper growth forecasts or when regulatory concerns and geopolitical tensions cast doubt on ability or timelines. 

As always, market behaviour also reflects crowd psychology: the fear of missing out pushes more money into a narrow group of ‘AI winners’, while investors rotate out of more diversified or value-oriented sectors. This concentration of investment can elevate systemic risk where a correction in a few headline AI stocks could ripple through ETFs and indices, amplifying market movements. 

For long-term investors the sensible approach remains sound. Invest in companies with credible revenue models, strong balance sheets and clear paths to profitability, rather than chasing the next big thing or narrative-driven momentum. 

Diversification and disciplined rebalancing is key as these strategies can mitigate the impact of headline-driven volatility.  

Whether today’s AI fervour becomes the way of the future or a cautionary chapter in market history will depend on the technology’s real-world impact, regulatory clarity and how quickly profitability catches up with lofty expectations.