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NewsMaterial3 min readDisconfirmAI Editorial

Monks Investment Trust Quarterly Review: Winners in the AI Supply Chain Depend on Where the Next Bottleneck Is

Monks Investment Trust explains a key distinction in AI infrastructure investment: suppliers addressing the most severe current bottlenecks are not necessarily future winners, because bottlenecks are filled by capital; the truly durable positioning lies in identifying where the next constraint will be—inter-chip connectivity, agent coordination logic, wafer fabrication, and memory deposition.

2026-10-18

There is a time-dimension issue that is easily overlooked in AI infrastructure investment. When a specific link becomes the most severe bottleneck, companies that solve it earn excess returns—but these high returns themselves attract capital to fill that bottleneck. Once the bottleneck is resolved, excess profits compress. The real question is not who benefits from current AI demand, but where the next constraint will appear.

In its October 2026 quarterly review, Monks Investment Trust explicitly drew this distinction. It wrote that so far, the biggest winners have been suppliers addressing the most severe bottlenecks, but many chokepoints may be relatively easy to fix, and the exceptional returns they generate may not persist. The fund’s core AI holdings—NVIDIA, Taiwan Semiconductor Manufacturing Company (TSMC), and Amazon—are positioned as durable building blocks of the system, rather than merely beneficiaries of today’s shortage.

Around this core, Monks tilted toward companies solving capacity constraints this quarter. Specifically, it added to positions in four semiconductor equipment companies, including Disco (whose equipment grinds and polishes wafers) and Kokusai (whose machines deposit layers used in memory chips), citing their dominance at critical steps in the manufacturing process. As technology evolves, new constraints are emerging: Astera Labs’ connectivity chips move data between expensive AI chips to ensure they do not sit idle; SoftBank provides undervalued exposure to the logic chips needed for agent coordination through its holding of Arm, a logic chip designer.

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The technical basis for this framework is that AI agents have already surpassed human usage and are expanding rapidly, despite Cisco President Jeetu Patel noting that less than 2% of humanity uses agents today. As agents become a larger share of AI usage, logic chips capable of coordinating and directing their actions become increasingly important. This is not an abstract investment thesis, but an observation of the evolution of AI system architecture—from computation to connectivity, from connectivity to coordination, with each layer solved exposing the constraint of the next.

It must be stated honestly that this review was written against the backdrop of Monks underperforming the benchmark over the past 12 months (share price return 11.9%, net asset value return 10.3%, compared to the FTSE World Index’s 20.9%). The authors explicitly state that relative underperformance is partly due to different AI exposures. The argument about the 'next bottleneck' is difficult to falsify in the short term—if these companies indeed become winners over the next five years, the framework is validated; if not, it can also be reinterpreted as the 'next-next bottleneck'. The authors have a clear commercial interest in providing a narrative justification for underperformance.

But this analytical framework itself holds value independent of the fund’s performance. It poses a testable question: in the capital expenditure cycle of AI infrastructure, which constraints are temporary (high returns attracting capital to quickly fill them) and which are structural (requiring sustained technological leadership)? Answering this question requires understanding specific manufacturing processes, chip architectures, and system topologies, rather than simply tracking total AI spending.

Monks also emphasized breadth as a hedge: this quarter it added growth sources not driven by AI, including banks benefiting from high US interest rates and light regulatory environments (Texas-based Cullen/Frost), energy companies profiting from tight supply (Cheniere Energy), and participation in the initial public offering (IPO) of Italian software integrator Bending Spoons. The reasons for selling WillScot and Stella-Jones were the lack of evidence of pricing power. This conscious effort to 'not become an AI infrastructure trust' is itself a form of managing single-theme risk.

Sources

  • bailliegifford.com↗
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