The emergence of Generative AI fundamentally fractures the economic logic of this digital hegemony. By collapsing the cost of digital creation of code, content, and even intellectual property, AI is commoditizing the very assets the market is valuing most highly.

We stand at the cusp of a major capital regime change. As the digital world begins to drown in a deflationary supply shock of its own making, the three-dimensional world of atoms, energy, metals, and infrastructure is entering an era of scarcity. The “playbook of the last thirty years is broken,” according to Will Thomson of Massif Capital.

2026 may be retrospectively identified as the pivot point where antifragility shifted from the owner of the software company to the owner of the copper mine. What follows is an examination of this impending bifurcation and the case for a strategic reallocation into real assets.

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A Tale of Two Worlds

AI is a tech marvel reshaping human productivity. But while investors bid up the creators of this digital intelligence, a more profound shift is underway. The global economy is approaching a stark divergence between two distinct ecosystems: the “2D World” of screens, software, and bits, and the “3D World” of energy, infrastructure, and atoms.

For the past fifteen years, the 2D World has been the only game in town. It offered zero marginal costs and infinite scale. A piece of software code can be replicated a million times without spending a penny on steel, fuel, or shipping. The economics of “infinite margin” rightfully seduced the financial world, ultimately leading to unprecedented concentration in the S&P 500.

The rise of Generative AI is a double-edged sword for this 2D dominance. By democratizing code and content creation, AI is unleashing a near-infinite supply shock upon the digital economy. It is commoditizing the very things that the market has been trained to value most. When an AI agent can write code better and faster than a human, the value of a “SaaS wrapper” collapses. When an AI can generate text, images, and video instantly, the value of digital media inventory approaches zero.

In contrast, the 3D World is facing a supply cliff. As Will Thomson points out, one cannot “prompt” a new copper mine into existence. One cannot “generate” a gigawatt of baseload power with an algorithm. The 3D world is governed by the laws of physics, geology, and thermodynamics, not Moore’s Law. Overlay that with the political forces regulating the 3D word, and it is clear that the addition of supply in the real world remains a slow, painstaking process.

Exhibit 1: Key Differences — 2D versus 3D

The Prevailing Bias

For many investors, the psychological difficulty of this necessary rotation cannot be overstated. The market has been conditioned by more than a decade of “Tech Exceptionalism.” Since the Global Financial Crisis, the prevailing narrative has been that technology is the only sector capable of growth in a low-growth world. This belief has become so entrenched that it is now treated as a law of nature rather than a cyclical phenomenon.

Similarly, the belief in “US Tech Exceptionalism” has driven US outperformance for years. Investors have crowded into the same trade (long US large-cap growth, short commodities and value), creating a “suction pump effect,” as described by Murray Stahl of Horizon Kinetics. This effect pulls capital out of the broader market and concentrates it into a handful of mega-caps, distorting valuations.

In investing “what worked yesterday” is often the enemy of “what will work tomorrow.” The market is pricing much of the 2D world for perfection, essentially assuming that margins will remain high forever, while pricing much of the 3D world for extinction. This is the classic setup for a capital cycle reversal. The Mag 7 recently comprised nearly 35% of the S&P 500 market cap, a concentration that leaves passive investors exposed to a change in regime.

Exhibit 2: The Evolution of S&P 500 Market Cap Concentration

AI as an Inflationary Force

The central insight here is counter-intuitive. Many investors view AI as a purely deflationary force because it lowers the cost of labor and intelligence. While this is true for the 2D economy, AI is an inflationary force for the 3D economy.

The irony of the AI age is that it is voraciously physical. The cloud is made of steel, and the data center runs on electrons. An AI query consumes significantly more energy than a traditional search query. The build-out of AI infrastructure (data centers, grid upgrades, cooling systems) requires massive amounts of copper, aluminum, and baseload power.

AI acts as a siphon: it drains value from the digital layer (by increasing the supply of digital goods) and injects value into the physical layer (by increasing demand for physical resources). We are standing at the precipice of a Great Rotation where capital is destined to flee the deflationary, oversupplied 2D World and flood into the inflationary, scarce 3D World. Choosing to get ahead of the Great Rotation is not a speculative act. Rather, it is defensive.

Some may argue that AI will be deflationary in the physical world as well because it will make commodity extraction and production more efficient. Such an outcome is possible, even likely, but it seems out of reach for at least a decade or longer. It is certainly much more remote than AI collapsing pricing in the 2D World.

The AI Eraser

The investment thesis for software has been bolstered by “high switching costs” and “proprietary code.” Generative AI acts as an eraser for these advantages. Consider the SaaS business model. Valuation multiples of 10x, 20x, or even 50x sales have been justified by the idea that once a customer is acquired, they will pay a subscription with 90+% gross margins, essentially forever. This model relies on the difficulty of coding and/or migrating to a competing product.

AI agents are close to being capable of replicating the functionality of many SaaS products, with agent functionality improving rapidly. If an enterprise can use a generic Large Language Model (or a more optimized derivative) to perform the same analytics, customer service, or data processing tasks for which they previously paid a specialized SaaS vendor, the pricing power of that vendor evaporates. We are already seeing signs of a “pricing collapse” in the software sector, where features that were once paid add-ons are now expected to be free utilities. This goes well beyond the typical deflationary forces in the sector.

The implications for a product such as Blinkist, which provides book summaries, may be undeniable, but those same implications also apply — with a modicum of imagination — to a much broader array of software and content.

Exhibit 3: Recent Examples of 2D Pricing Pressure

Exploding Supply and Margin Compression

In the 2D world, supply is quickly becoming near-infinite.

• Content: The cost to produce marketing copy is becoming negligible.

• Code: The cost to produce an application is trending toward zero.

• Analysis: The cost to synthesize complex data is plummeting.

When supply becomes abundant, price collapses. This is the deflationary tsunami facing the 2D world. The moats that investors thought existed are drying up because AI can replicate them quickly and cheaply.

Even in Vertical SaaS, a segment many investors have considered immune, the threat appears acute. The consensus has been that companies providing specialized software for niche industries like construction, legal services, or hospitality are immune to the pressures facing generalist tech. Vertical SaaS products are considered “hard-wired” into customers’ fragmented legacy systems, creating high switching costs. In addition, Vertical SaaS sales teams understand the specific nuances of a customer’s industry, acting not only as vendors but consultants.

Yet, in a world of infinite 2D supply, those are not sustainable moats. AI changes the physics of data integration, as an AI agent does not need a brittle, hard-coded API to talk to a legacy database; it can interpret the data schema, read the documentation, and write the integration code. Or, more radically, it can simply ingest the unstructured data from the legacy system and restructure it on the fly. When an AI agent can serve as a fluid, instant bridge between any two systems, the value of the Vertical SaaS incumbent’s proprietary “plumbing” falls toward zero.

Similarly, the solution-based sales moat is crumbling. In the AI era, the customer no longer needs a vendor to dictate best practices. A construction manager or a law firm partner can prompt an AI model to “design a workflow for managing Tier-2 supplier contracts” or “optimize the patient intake schedule.” The information asymmetry that allowed Vertical SaaS sales teams to charge a premium for “solutions” is disappearing. Even if we are rightfully skeptical of claims that today’s AI can do all of the foregoing, time is decidedly not on the skeptics’ side. What multiple should we put on a business whose moat might be gone in five to ten years?

A Combustible Cocktail: Tech Exceptionalism X Passive Investing

Murray Stahl has poignantly identified the structural risks from an investor’s perspective. The IT sector, inclusive of Amazon, Meta, and Alphabet, recently comprised ~46% of the S&P 500 market value (see page 3 of Horizon’s Q3 letter). If AI makes “intelligence” a commodity, IT sector margins will inevitably compress. The 2D world is entering a war of attrition where the only winner is the consumer, not the shareholder (and even the point about the consumer is debatable due to the quality-of-life implications of the addictive nature of screens and the non-negligible existential threat of AI).

Exhibit 4. Market Cap of Largest US Stock Relative to 75th-Percentile Stock (x) (left axis); Weight of Top 10 Stocks in S&P 500 (%) (right axis)

The mechanism of tech overvaluation is the rise of passive investing. Fund manager Daniel Gladiš discussed eloquently the perils of indexing in a recent interview.

A timely example of the value-destructing reality of passive investing is the impending addition of Carvana to the S&P 500 Index. The shares jumped nearly 10% on the announcement, having already risen 113% year-to-date and witnessed relentless insider selling throughout 2025, in part at materially lower prices. Surely, this is an opportune moment for pension funds and endowments to create value for their beneficiaries by acquiring Carvana shares.

The passive investing trend has created a “suction pump,” according to Murray Stahl, where capital flows blindly into the largest-capitalized companies regardless of valuation. This creates a feedback loop: the higher the stock price goes, the more weight it gets in the index, and the more capital it attracts. This has divorced the price of 2D assets from their fundamental economic reality.

This mechanism also works in reverse. If the underlying fundamentals of the 2D world deteriorate, the “suction pump” will reverse, leading to a liquidity crisis in the very stocks everyone owns. There is “nowhere to hide” in the index when the dominant sector corrects.

Exhibit 5. S&P 500 Sector Weightings

Let’s not forget that the 2D world is constrained by a hard physical limit: human attention. There are only 24 hours in a day. As AI explodes the volume of digital content, the value of an incremental unit of digital engagement approaches zero. We are drowning in “digital noise.” This degrades the value of digital advertising, the lifeblood of the 2D economy. Sure, the creators and companies able to capture scant attention will win, but how do we find them? Nearly every highly valued public company seems like a future winner, but the underlying math does not favor such a conclusion.

Scarcity Premium: The Renaissance of 3D

While the 2D world drowns in abundance, 3D remains constrained. The physical domain is defined by friction, and that friction is now the source of value.

The 3D world has been in a bear market for most of the last decade. Capital has fled the sector since the commodity peak in 2011, resulting in massive underinvestment in productive capacity. As Will Thomson notes, we are moving from an era of globalization and abundant resources to an era of “unwinding” interdependency and resource nationalism.

The “Intelligent Investing 3D” thesis is bolstered by capital cycle theory, popularized by Marathon Asset Management. The theory states that high returns attract capital, which leads to oversupply and lower returns. Conversely, low returns repel capital, leading to undersupply and higher returns.

The 2D world appears to be at the peak of the capital cycle, while the 3D world is at the trough. For a decade, mining and energy companies have been punished by ESG mandates and shareholder demands for dividends over growth. They stopped exploring and stopped building. Bank credit dried up, as pointed out by Mohnish Pabrai in reference to the coal sector.

Meanwhile, oil wells and copper mines deplete every year. If you do not reinvest, supply shrinks. As a result, we have a coiled spring of potential returns. The world has consumed the surplus capacity of the 3D world, and now, just as demand is inflecting upward (driven by AI), supply is hitting a wall.

Goehring & Rozencwajg make a nuanced distinction in the commodity landscape between cyclical weakness and structural strength. In their recent commentary, they split the commodity complex into two camps: (A) Uranium, gold, and platinum group metals have remained “stubbornly immune” to economic malaise because their supply deficits are so acute that they override cyclical demand fears; and (B) oil and base metals, which have reacted to fears of recession and tariff-induced trade wars.

This split may present an entry opportunity. The “Camp B” assets are being priced for a recession or worse, while the gloominess may be overshadowed by secular demand from the AI buildout. The “Next Inflationary Surge,” according to G&R, will lift all boats in the 3D sector, but the entry point today is most attractive in the unloved cyclicals.

It is also instructive to look at the “Return on Invested Energy.” As geology degrades, it takes more energy to get resources out of the ground. We are moving from the “easy oil” and “high-grade copper” era to a period where resource extraction is more energy-intensive and capital-intensive. This raises the floor price for all commodities. The 3D world is not just scarce; it is becoming structurally more expensive to access, granting immense pricing power to the incumbents who own the high-quality assets. Exploration and production, aided by AI, may be an offset in the future, but such a future appears quite remote at this point.

The Great Convergence: Why 2D Needs 3D

The most critical misunderstanding in the market today is the belief that the 2D economy is independent of the 3D economy. In reality, the 2D world is parasitic on the 3D world. It seeks to consume rapaciously the energy and materials of the physical world. As we move from “traditional computing” to “AI computing,” the physical toll of the digital world is skyrocketing.

• Energy intensity: Training a single large AI model consumes gigawatt-hours of electricity.

• Inference costs: Every time a user asks a frontier model a question, a server farm spins up, consuming electrons and generating heat.

• Data centers: These are not virtual entities. They are massive industrial warehouses packed with silicon, copper, and steel, requiring water for cooling and backup diesel generators for reliability.

The bottleneck for the AI revolution is not Nvidia chips; it is the copper wire and the power plant. According to data synthesized from Massif Capital and Goldman Sachs, an AI hyperscale data center is estimated to be four times more copper-intensive than a traditional data center. A facility may require between 3,000 to 5,000 tonnes of copper for power distribution, grounding, and connection.

Goldman Sachs projects that AI-driven demand is pushing the copper market into an imminent structural deficit. Fast-forward ten years and the global supply gap could swell to six million tonnes, a shortfall that is mathematically impossible to fill with currently commissioned mine projects.

Exhibit 6: The Long Journey of Bringing New Copper Supply to Market

We are seeing a shift from demand constraints (where we worried about the economy slowing down) to supply constraints (where the economy literally cannot grow because we lack the physical inputs). In this environment, pricing power shifts to the provider of the bottleneck. If Microsoft needs copper to keep its $100+ billion AI investment running, it will pay a higher price. Demand is mostly inelastic.

The same logic applies to energy. The AI buildout is colliding with a grid that is already strained by the “green transition” and the electrification of vehicles. We are asking the grid to do two impossible things at once: retire dispatchable fossil fuel power (coal/gas) and add massive new load from AI data centers.

This leads to the “Greenflation” and “Tech-flation” thesis championed by Will Thomson. The demand for reliable, baseload power (nuclear, natural gas, hydro) is set to explode. The 2D world’s need for 99.999% uptime cannot be met by intermittent wind and solar alone. This will drive a renaissance in “old economy” energy sources that can provide the stability AI requires.

As noted by Massif Capital, we are already seeing the “bright spot” in European industrials related to power grids and energy infrastructure. This is the leading edge of the Great Convergence: the digital world paying a premium to the physical world.

Historic Valuation Disconnect

The divergence in valuation between the 2D and 3D worlds offers the most asymmetric opportunity set seen since the dot-com bubble burst.

Investors are paying ~20x sales for Snowflake, a business that consumes capital rather than returning it, and whose core value proposition is under threat from commoditized AI analytics. Even mature giants like Salesforce trade at multiples that imply their moats are sustainable. Conversely, the market is pricing Freeport-McMoRan as if copper is a stagnant industry. Freeport owns the Grasberg mine, a geological anomaly that cannot be replaced.

Exhibit 7: A Few Examples of the Disconnect

Bob Robotti offers a crucial correction to the standard “value rotation” narrative. He argues that we are poised to writness not merely the “Revenge of the Old Economy,” which implies a temporary, cyclical bounce. Rather, it is the “Metamorphosis of the Old Economy”. Bob shared his views on the resurgence of North American cyclicals and commodity-based businesses at Latticework 2025.

Industrial companies have spent the last decade consolidating, cutting costs, and cleaning up their balance sheets. They are no longer the bloated giants of 2011; they are lean, cash-generating machines. They have transitioned from being “disadvantaged” by globalization (which favored cheap labor and outsourcing) to being “advantaged” by near-shoring (which favors domestic capacity and reliability). They are trading near liquidation values despite being the essential engines of the future economy.

Resilience and Antifragility

In a deglobalizing world, the physical location of assets matters. We are entering an era of “friend-shoring” and resource nationalism. Access to physical resources is no longer just a commodity trade; it is a matter of national security.

Will Thomson notes that the next decade will be dominated by the “use of trade as a tool of government statecraft”. Owning a copper mine in Arizona is fundamentally different from owning one in a hostile jurisdiction. 3D assets within secure borders are “antifragile”; they gain value during geopolitical chaos because they represent security of supply.

By comparison, 2D businesses are vulnerable to platform shifts (e.g., Apple changing privacy settings), algorithm changes (Google Search updates), and cyber warfare. A software company can lose much of its value overnight if a competitor releases a better AI agent. A copper mine cannot be “disrupted” in the same way. The rock is still in the ground, and the world still needs it.

Then there’s inflation. Murray Stahl provides the critical nuance here: even if official CPI looks tame, “localized inflation“ in scarce assets is rampant. Stahl uses the example of the Sabine Royalty Trust (SBR), an oil royalty company (a hard asset proxy) that simply collects a percentage of the top line. As oil prices rise, the royalty check rises without a commensurate increase in costs.

3D assets are natural hedges against the debasement of fiat currency. If the dollar loses value, the copper mine (priced in dollars) gains nominal value. 2D assets, which rely on long-duration cash flows discounted back to the present, are in a bind if long-term interest rates rise due to inflation while pricing power vanishes due to AI.

The 2026 Pivot

The central thesis of this essay has been playing out already to some extent. However, we are still in the very early innings.

It would not surprise me if 2026 turns out to be the first year of “The Great Rotation.” The initial hype of AI appears like to settle. The market may recognize that the 2D world is fighting a deflationary war of attrition, while the 3D world is enjoying pricing power born of structural scarcity. The narrative may shift from “software eats the world” to “software needs the world.”

For investors and allocators, waiting to pivot is the more speculative choice. Taking advantage of the still-wide valuation disparity to move capital from 2D to 3D assets at a high “conversion rate” strikes me as not only the defensive but also the forward-looking choice.

Let’s move from concept to execution with The Great Rotation Playbook. Start with the actionable ideas laid out in Part 1: The Energy Backbone.

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This AI-driven capex frenzy is eerily similar to th…

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That is what this post is about. It is not investment advice. Do your own work.

It does feel overwhelming to write about the impact of AI on stock returns, at least in a way that is actionable by investors. In some respects stock prices are already speaking loudly. The price performance of Nvidia, Palantir, and Tesla says volumes about the value creation potential of AI. These companies, and numerous others, are the obvious beneficiaries. Few would argue to the contrary on the fundamentals; any quibbles tend to focus on the likely winners’ stratospheric market quotations:

I will not try to add value here by opining on the market appraisals of Nvidia, Palantir, or Tesla. I’ll let the market decide what multiples it wants to put on these likely AI winners. That said, there are some ways to think about AI winners’ risk-reward tradeoffs. Otherwise, no difference would seemingly exist between investing $1,000 in Nvidia at 1x or 10x the recent market quotation. I explain my thinking in a broader essay entitled, “Why Inversion is Indispensable for Long-Term Success”.

The Bearish Side of the Coin

Today I focus on the fact that we haven’t really seen Mr. Market price in the flipside of AI — the creative destruction that may be about to wreck the business models of a range of public companies. Call it a feature of the long-running bull market: Investors are much more inclined to look for the winners than the losers. Not only that, but even when staring a likely loser in the face, investors seem willing to accept the loser’s narrative about AI being more of an opportunity than a threat.

In the very short term, the losers may be able to throw some AI bells and whistles on top of their legacy products and charge customers an extra fee, thereby boosting short-term results. Investors would be shrewd not to get lulled into complacency or the belief that a loser may actually be a winner. Instead, the short-term bump may be an opportunity to monetize winnings or even reverse the direction of a trade.

Sometimes investors get too deep into the weeds of a company, a situation, or a theme. Industry insiders are often the last to see the writing on the wall. Think Angelo Mozilo or bank analysts in 2007 (“real estate prices only go up”), or Blockbuster executives in the early days of Netflix (“picking a movie at the store is part of the experience”). Not seeing the forest for the trees applies here. Under such circumstances, we may need the perspective of a knowledgable outsider to push us to step back and consider the big picture.

Enter Adam D’Angelo, founder of Quora and AI startup Poe. Adam has a rich pedigree, having joined Facebook shortly after its launch and served as its chief technology officer. He was an investor in Instagram before its acquisition by Facebook. As a board member of OpenAI, Adam voted to remove Sam Altman as CEO. When Sam returned, the other three board members involved in the ouster resigned, but Adam retained his position.

Here’s his take from a couple of weeks ago:

Adam followed it up with this take:

One of the commenters was more explicit:

If you weren’t triggered before, you might be now: “There’s no way AI-generated movies or series can rival the best Hollywood releases. Humans will always prefer movies with real human actors instead of AI-generated characters. Netflix is a platform, so any quality AI productions will simply come onto the platform. Netflix has a massive scale advantage and can invest in AI ahead of its competitors. AI will expand the market, producing many winners, including Netflix.”

The list goes on, and the arguments put forth in favor of Netflix make sense. Yet, lurking beneath the surface is the uncomfortable truth that more supply — especially if it is near-unlimited, near-free supply — has to manifest somehow. Stark example: air — a highly valuable commodity, yet typically free due to near-unlimited supply.

A more mundane example: Groupon, the first mover and scale leader in online deals. Once supply exploded due to new entrants copying Groupon’s formula, the company had to accept an impairment to its business model, and the stock price followed.

Other examples abound in the business world. In hindsight, the argument is easy to comprehend. Looking ahead, though, our imagination usually fails us, especially if we have developed a positive association with an idea.

As an investor in Netflix, how could you not have a positive association with the company? It has been a massive source of good vibes, an example of the adage to let your winners run. You might be thinking, “I am not going to disregard this adage simply because an essay purports to know what might happen.” I don’t blame you.

In the case of Netflix, the most likely manifestation of the coming AI content explosion might be an impairment of the pricing power the company enjoys at the moment. The service can credibly claim that it adds more value than it costs, so demand is inelastic to price increases. Netflix has proven this point multiple times, and the stock price has acted accordingly. What happens if demand becomes more elastic to price in light of a sea of content alternatives, many of which may not only be low cost but also personalized and compelling?

In addition to Netflix, I would put the following companies in the category of incumbents who are likely to be hurt rather than helped by AI:

• Other content owners, such as Paramount and Warner Bros Discovery

• Recorded music owners, such as Universal Music Group

• Gaming giants, such as Electronic Arts and Take-Two Interactive

• Software incumbents, such as Salesforce, Adobe, and even HubSpot

I realize that the above examples are highly controversial, perhaps most of all Universal Music Group. Don’t get me wrong, music will continue to have value, but profitability should migrate toward live events and Spotify, in my humble view.

I won’t argue the specific examples above in detail, as such arguments tend to be futile in foresight. The market narrative and market-implied expectations are simply too optimistic and too powerful in light of the positive historical stock price performance of the companies listed above, with the stark exception of Paramount and Warner Bros Discovery. You might say that what the Internet did to PARA/WBD, AI may do to the other companies on the list. (I would not include PARA/WBD in a bearish trade — the valuations of both companies already reflect deep pessimism.)

Feel free to brush aside my opinion as that of a no-nothing when it comes to high-flying tech areas such as CRM and SaaS more broadly. But how do you brush aside Satya Nadella? In an appearance on the BG2 podcast a couple of weeks ago, the Microsoft CEO provided an outlook for B2B software that shocked many investors.

Check out the first four-and-a-half minutes:

Similarly, in a recent appearance on Bloomberg Technology, Klarna CEO Sebastian Siemiatkowski explained how AI is enabling his company not only to do away with expensive software — cutting out Salesforce and Workday — but also to freeze hiring, leading to a ~20% reduction in headcount annually.

The example of Klarna serves as a warning to investors in incumbents that stand to lose customers — or are forced to make major concessions — in the coming age of AI.

The Bullish Side of the Coin

Perhaps more importantly, Siemiatkowski provides a glimpse into the newfound ability of many companies to dramatically downsize their cost structure. This applies in particular to businesses that are heavy users of technology or, better yet, have large programming staffs.

The bullish setup: Imagine a company whose stock price has declined precipitously as the former highflyer has struggled to turn a profit. Investors have left the company for dead, resulting in a low multiple of enterprise value to revenue. A company that may have enjoyed a valuation of 20x sales or higher a few years ago may now sell for well under 1x sales.

A turnaround in profitability could produce multibagger upside, as sales remain mostly flat while the sales multiple expands due to strong profit growth. Any resumption in sales growth would add fuel to the fire, but the latter is not really needed, as the company already has a large base of sales relative to its recent enterprise value. The company needs margin expansion, which can be achieved through cost rationalization aided by AI.

A key requirement for any tech company I would consider seriously as part of this bullish setup is large insider ownership. I want management to be heavily incentivized to cut costs and grow shareholder value. Otherwise we could be stuck with a situation in which a CEO remains content to run the business near breakeven. I want a CEO who would be reaching into his own pocket if he desired to keep funding an unnecessarily bloated cost structure. Few owner-operator CEOs will do this, if the ability for dramatic cost cutting is staring them in the face thanks to AI.

Finally, I favor companies with strong balance sheets, i.e., a net cash position. This extends the runway and provides strategic flexbility. It also removes the risk of aggressive debt holders opportunistically forcing the company into a dilutive equity offering (or worse).

Behind the paywall, I list three companies that meet my bullish criteria. I believe these are winners of AI over the near- to medium-term. They have highly skewed risk-reward tradeoffs due to high insider ownership, strong balance sheets, large existing revenue bases relative to EV, and a massive margin expansion opportunity due to AI.

I am long all three companies. Not investment advice. Do your own work.

Drumroll please.

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