How the AI market could splinter between monetizers and manufacturers

The AI market is poised for a significant transformation by 2026, following a tumultuous end to 2025 marked by sharp sell-offs and rallies. This volatility, driven by complex financial maneuvers and growing concerns about an AI bubble, indicates a potential shift in how investments in artificial intelligence will be approached. Stephen Yiu, the chief investment officer at Blue Whale Growth Fund, highlights that investors are beginning to scrutinize the financial health of AI companies more closely. As the market evolves, Yiu suggests that a clear distinction among companies is becoming crucial. Currently, many retail investors involved in AI through ETFs do not differentiate between firms with viable products and established business models, those burning capital for infrastructure, and those benefiting from AI expenditure. Yiu identifies three distinct categories within the AI landscape: private startups like OpenAI and Anthropic, publicly traded companies investing heavily in AI, and firms focused on AI infrastructure, such as Nvidia and Broadcom. Notably, private companies attracted a staggering $176.5 billion in venture capital during the first three quarters of 2025. While tech giants like Amazon and Microsoft are actively funding infrastructure providers, Yiu warns that the high valuations of many companies in the sector may not be sustainable. He emphasizes the importance of assessing free cash flow yields against stock prices to determine whether current valuations are justified. Market strategist Julien Lafargue from Barclays Private Bank echoes these sentiments, noting that the enthusiasm surrounding AI is concentrated in specific segments rather than the broader market. He cautions that companies securing investments amid the current AI boom without tangible earnings—especially in fields like quantum computing—are particularly vulnerable. As big tech firms transition from asset-light to more capital-intensive models, investing heavily in technology and infrastructure, their risk profiles are also changing. This evolution raises questions about how these companies should be valued moving forward. Dorian Carrell, from Schroders, adds that the reliance on debt to fund AI strategies requires careful consideration. While companies like Meta and Amazon have successfully raised funds, they maintain a net cash position, a crucial distinction from those with tighter balance sheets. Looking ahead, Yiu suggests that if the incremental revenues from AI do not outpace the associated costs, profit margins could suffer, prompting investors to rethink their return expectations. As discrepancies between companies widen, it will become increasingly vital for AI spenders to account for these investments in their financial planning. The next few years are likely to usher in an era of increased differentiation within the AI sector.