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The AI investment landscape is evolving. While Nvidia (NVDA) has been the undisputed winner in the AI boom, the market is shifting its focus beyond chipmakers to companies integrating AI into their business models. We need to explore how AI investment strategies are evolving from CapEx spenders vs. receivers to CapEx beneficiaries—companies that reap AI-driven profits without heavy infrastructure investment.

In this context, I want to introduce you to GAS BAMWAM: Generating AI Scalability in Business, Advancing Market Winners with Widespread AI Monetization.

I can already see the skeptical faces at yet another market acronym, but bear with me for a few minutes—I promise this is more than just buzz.

I’ve been researching several AI-related companies, trying to determine which ones stand to benefit the most over the next 18 months, given the current state of AI. That’s how I arrived at this very bad acronym:

GitLab (GTLB)

Alphabet (GOOG)

Shopify (SHOP)

Block (XYZ)

Amazon (AMZN)

Meta (META)

Wix (WIX)

AMD (AMD)

Micron (MU)

What do they have in common? Most of them are growing fast and showing signs of margin expansion. Let’s take a deeper look.

Building a Framework for AI Stocks

Starting from Ram Ahluwalia’s CapEx receivers/spenders thesis, I’ve expanded the framework to include the application layer—a move Ram initially dismissed as a mistake. In his piece, he argued that, for investment purposes, the Silicon Layer was the safest bet since AI companies couldn’t fully trust outsourcing their data and would inevitably build their own infrastructure. This meant Nvidia (NVDA) was the clear winner—and indeed, it was.

However, I now believe it’s time to reassess the application layer. Not because I think I can pick winners better than the market, but because Palantir has proven that AI can meaningfully transform a business model. If Palantir (PLTR) serves as a proof of concept for AI-driven business viability, we can now examine the CapEx spending by hyperscalers with greater confidence. More than ever, they are likely to recoup their massive investments. If this trend is sustainable, CapEx receivers should benefit significantly.

For this reason, I believe we should update the CapEx framework to include a third category: CapEx benefiters—companies that haven’t invested heavily in AI infrastructure but are reaping the rewards of hyperscaler investments.

CapEx Receivers and Spenders

At the beginning of this AI cycle, Nvidia (NVDA) captured most of the gains in both revenue and profit. Since hyperscalers needed to build AI infrastructure to maintain sovereignty over their data, the market initially perceived this as a risk. As a result, returns for hyperscalers lagged behind Nvidia’s explosive growth.

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However, the narrative around CapEx spenders might be shifting. With improving operating profits, the market could begin repricing these stocks.

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Among CapEx receivers, Nvidia was the dominant winner—no other company came close in terms of market appreciation during the AI explosion.

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Yet, this too may be changing. Micron (MU) and AMD (AMD) have maintained steady revenue growth with improving margins—which could shift investor sentiment in their favor.

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CapEx Beneficiaries: The New Category

This brings us to a new category: CapEx beneficiaries. As I mentioned earlier, Palantir is a prime example. These are companies whose business models are being turbocharged by AI, as reflected in their expanding EBITDA and operating margins.

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These companies are showing a consistent upward trend in profitability. If this continues, a market repricing is likely.

Among this group, we should also include:

Amazon (AMZN) → AI-powered logistics, cloud computing, and e-commerce

Alphabet (GOOG) → AI-enhanced search, advertising, and cloud services

Meta (META) → AI-driven social media engagement and advertising

Each of these companies leverages its own AI infrastructure to improve core business segments:

• Meta benefits from AI-driven ad targeting and content recommendations.
• Alphabet enhances search and advertising through AI-powered algorithms.
• Amazon refines product recommendations and automates logistics with AI.

These businesses stand to benefit the most from AI advancements.

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Valuation

Among these stocks, the most expensive based on the price-to-sales ratio is Palantir (66x sales), followed by Nvidia (20x sales) and Shopify (13x sales).

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When we shift to price-to-earnings, Palantir again tops the list, with AMD and Wix also trading at high multiples.

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This suggests that investors need to be selective—some of these names may be too richly valued to deliver strong returns going forward.

Wrapping up

The goal of this exercise is to build a structured framework for AI investing. Right now, market sentiment is shaped by concerns over Trump’s tariffs and broader macroeconomic fears. AI-related stocks have been sold off along with the broader market.

However, paradoxically, these companies may benefit from economic turmoil. Stricter immigration policies and the potential for a recession could push businesses toward greater automation and efficiency, increasing demand for AI-driven solutions.

That said, further refinement is necessary. In my view:

• Micron is too cyclical.
• Palantir is too expensive.
• Microsoft may not benefit as much as Meta or Amazon in the short run.

Thus, my final AI stock list is:

• Shopify (SHOP)
• Wix (WIX)
• Amazon (AMZN)
• GitLab (GTLB)
• Nvidia (NVDA)
• Alphabet (GOOG)
• Block (XYZ)
• AMD (AMD)
• Meta (META)

Yes, this spells SWAG NABAM—another questionable acronym, but at least it has some “swag” in it.

Jokes aside, I believe SWAG NABAM represents the best AI monetization plays across industries, and this list warrants deeper analysis.

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