Analysts at BCA Research are raising the prospect that the artificial intelligence boom may significantly weaken the economic advantages that have supported outsized profits at many large technology companies. In a client note circulated by the firm, strategists including Peter Berezin laid out how AI could chip away at the classic pillars of monopoly power - economies of scale, network effects, and proprietary offerings - that have long underpinned the sector's margins.
Berezin and his colleagues argue that the emergence of AI-driven products and services presents a paradox for the industry: it is likely to push up variable costs tied to building and operating the massive infrastructure AI requires, while simultaneously reducing the pricing power enjoyed by vendors of off-the-shelf software.
Particularly affected, the analysts say, will be the so-called hyperscalers. BCA Research highlights that these firms are planning sharply higher capital spending on AI infrastructure - projected at about $670 billion in 2026, up from $410 billion in the prior year and $240 billion in 2024. That ramp in spending, the note says, transforms many cloud and platform operators into more capital-intensive enterprises, a departure from the lighter capital model that helped attract investor interest in recent years.
At the same time, software companies face competitive pressure as enterprises consider AI-enhanced development tools. BCA Research warns that businesses may rely increasingly on AI coding assistants instead of traditional software-as-a-service offerings, a shift that could erode revenue streams for established software vendors.
The vulnerability extends to social media platforms, the analysts say. Under the classic hub-and-spoke arrangement, platforms draw users into an ecosystem where network effects enhance engagement and monetization. AI, however, could insert an agentic interface between users and content, turning platforms into little more than content stores rather than destination hubs. Berezin captured the risk with a direct line:
"AI has the potential to upend the traditional hub-and-spoke model by creating an agentic layer between the user and the content. Rather than going to Instagram to find out what is new or see something interesting, people could ask an AI agent for that information," Berezin wrote.
Another structural challenge highlighted by the note is the proliferation of open-source AI toolkits. Those toolkits lower barriers to building and training models, the strategists argue, making it harder for any single company to sustain a monopoly based on proprietary algorithms or code and thereby limiting the ability to maintain elevated pricing for AI-enabled products.
Given these dynamics, BCA Research suggests the primary economic winners from the AI transition will not necessarily be software incumbents but owners of scarce physical inputs and assets - for example, land and natural resources - whose value is less likely to be displaced by code and algorithms.
The strategists also warned of broader macroeconomic implications. Because large technology companies make up a material share of the S&P 500 by market capitalization and U.S. household wealth is heavily exposed to equities, a sustained decline in tech valuations coupled with weaker investment spending could push the wider economy toward a mild recession. Even so, Berezin and his colleagues emphasized that their shorter-term focus is on positioning for a rotation in markets rather than forecasting a full-scale recession.
To that end, BCA Research recommended a set of positioning ideas for 2026: expect Big Tech stocks to lag while long-term government bonds rise; "average" stocks to outperform mega-cap technology firms; emerging market equities to do better than the global average; and a tactical preference for metals such as gold and silver.
The note also referenced the attention on individual large-cap names as investors evaluate whether to buy into the pullback among technology leaders. It underscored that shifts in cost structures, distribution models and the diffusion of open-source tools together form the basis for the firm's view that AI may erode several of the structural advantages that have sustained tech monopolies.
Summary
BCA Research, led in part by strategist Peter Berezin, warns that AI could weaken the economies of scale, network effects, and proprietary tech that have supported high margins at major technology firms. Rising infrastructure spending by hyperscalers and broader use of AI development tools may raise costs and compress software pricing, while open-source toolkits and agentic interfaces could dilute platform power. The firm favors a market rotation away from mega-cap tech toward other assets, including long-term government bonds, emerging markets, and precious metals.
Key points
- AI could increase variable infrastructure costs for hyperscalers, shifting them toward a more capital-intensive model - impacting cloud and platform operators.
- AI-enhanced developer tools and open-source toolkits may reduce reliance on traditional software-as-a-service products and weaken proprietary advantages - affecting software vendors and platforms.
- BCA Research expects a market rotation: Big Tech underperformance, higher long-term government bond yields, outperformance of average stocks and emerging markets, and demand for metals such as gold and silver - affecting equity sectors and fixed income.
Risks and uncertainties
- Higher-than-expected capital spending on AI infrastructure by hyperscalers could further pressure profit margins and investor sentiment in technology - risk to cloud and infrastructure providers.
- Wider adoption of AI agents that bypass platform discovery could reduce user engagement and monetization for social media companies - risk to platform advertising and engagement models.
- The spread of open-source AI toolkits may limit the ability of firms to maintain pricing power on proprietary software offerings, creating revenue uncertainty for software vendors.