1 April 2026
Technology & Value
Technology & Value
What the AI Infrastructure Race Means for Overlooked Public Companies
What the AI Infrastructure Race Means for Overlooked Public Companies
What the AI Infrastructure Race Means for Overlooked Public Companies
What the AI Infrastructure Race Means for Overlooked Public Companies
What the AI Infrastructure Race Means for Overlooked Public Companies
The biggest capital deployment in technology history is happening right now. Most public companies will not see a dollar of it. That gap is where Altuva looks.
The biggest capital deployment in technology history is happening right now. Most public companies will not see a dollar of it. That gap is where Altuva looks.
$600B
$600B
Projected AI infrastructure spend by the five largest technology companies in 2026 alone
Projected AI infrastructure spend by the five largest technology companies in 2026 alone
Zero
Repeat acquirers of sub-$300M, below-NAV public companies globally
28.7%
Weight of seven major AI-linked companies in the Morningstar U.S. Target Market Exposure Index, nearly tripling over ten years
The five largest technology companies — Amazon, Alphabet, Microsoft, Meta, and Oracle — are collectively projected to spend more than $600 billion on AI infrastructure in 2026 alone, a 36% increase from 2025.
The five largest technology companies — Amazon, Alphabet, Microsoft, Meta, and Oracle — are collectively projected to spend more than $600 billion on AI infrastructure in 2026 alone, a 36% increase from 2025.
Approximately 75% of that figure, or around $450 billion, is directed specifically at AI-related infrastructure: data centres, compute capacity, chips, and energy systems.
The scale is without precedent in the history of technology investment. And for the companies at the centre of it, the returns could be generational.
This article examines the structural causes of persistent NAV discount in public equities and sets out why this condition has never been more pronounced than it is today.
The analysis draws on proprietary balance-sheet screening and third-party research from Research Affiliates, Goldman Sachs Asset Management, Pzena Investment Management, and Russell Investments.
$1.15T
$1.15T
$1.15T
Total hyperscaler capex projected by Goldman Sachs from 2025 through 2027
Total hyperscaler capex projected by Goldman Sachs from 2025 through 2027
Total hyperscaler capex projected by Goldman Sachs from 2025 through 2027
36%
36%
36%
Year-over-year increase in AI infrastructure spending by the top five tech firms
Year-over-year increase in AI infrastructure spending by the top five tech firms
Year-over-year increase in AI infrastructure spending by the top five tech firms
$3–8T
$3–8T
$3–8T
Estimated total digital infrastructure investment required by 2030 depending on AI adoption pace
Estimated total digital infrastructure investment required by 2030 depending on AI adoption pace
Estimated total digital infrastructure investment required by 2030 depending on AI adoption pace
The Concentration Problem
The Concentration Problem
The Concentration Problem
But here is what that conversation almost entirely misses: for every company capturing the AI infrastructure wave, there are dozens of public companies sitting adjacent to it — fundamentally sound, quietly growing, and almost completely invisible to the capital markets.
Market concentration in AI-related names is not anecdotal. Ten years ago, seven major AI-linked companies represented approximately 9.7% of the Morningstar U.S. Target Market Exposure Index. Today, that weight has nearly tripled, with the same group now accounting for 28.7% of the index.3 Investors with broad market exposure are already substantially invested in the AI buildout, whether they intend to be or not.
At the end of 2024, the valuation discount of U.S. small-cap stocks relative to large-cap peers stood at approximately 40%, well below the historical median gap of roughly 5%, and sitting in the bottom 4th percentile since 1990. Global small caps now trade at discounts last seen only during the Nifty Fifty and dot-com eras — extreme episodes defined by irrational concentration at the top of the market.
In the United States, small caps trade at a 26% discount to large-cap peers on a price-to-earnings basis, excluding unprofitable companies, which is close to historic lows. Outside the U.S., international small caps, which have historically traded at a premium to local large caps, have flipped to an 8% discount despite offering higher forward earnings growth.
The numbers that matter most: more than 5,000 public companies globally trade below their intrinsic asset value. U.S. small caps have underperformed large-cap peers by approximately 103% cumulatively over the last decade. The Russell 2500 Value Index price-to-book ratio has fallen to multi-decade lows. And zero repeat acquirers of sub-$300M, below-NAV public companies exist globally. Not few. Zero.
In plain terms: the market has priced the picks-and-shovels correctly. It has not yet priced the businesses that will quietly benefit from AI adoption without being in the AI business.
In plain terms: the market has priced the picks-and-shovels correctly. It has not yet priced the businesses that will quietly benefit from AI adoption without being in the AI business.
The Opportunity Gap
The Opportunity Gap
Goldman Sachs Research confirms that equity gains have been concentrated in AI infrastructure companies. The group of potential AI productivity beneficiaries — companies that would benefit from AI adoption without being in the AI business themselves — has lagged the recent trajectory of their own earnings, representing an attractive risk-reward for investors seeking exposure to AI beyond the infrastructure layer.
At the end of 2024, the valuation discount of U.S. small-cap stocks relative to large-cap peers stood at approximately 40%, well below the historical median gap of roughly 5%, and sitting in the bottom 4th percentile since 1990. Global small caps now trade at discounts last seen only during the Nifty Fifty and dot-com eras — extreme episodes defined by irrational concentration at the top of the market.
In the United States, small caps trade at a 26% discount to large-cap peers on a price-to-earnings basis, excluding unprofitable companies, which is close to historic lows. Outside the U.S., international small caps, which have historically traded at a premium to local large caps, have flipped to an 8% discount despite offering higher forward earnings growth.
The numbers that matter most: more than 5,000 public companies globally trade below their intrinsic asset value. U.S. small caps have underperformed large-cap peers by approximately 103% cumulatively over the last decade. The Russell 2500 Value Index price-to-book ratio has fallen to multi-decade lows. And zero repeat acquirers of sub-$300M, below-NAV public companies exist globally. Not few. Zero.
Who Gets Left Behind
Who Gets Left Behind
Who Gets Left Behind
Consider what it means to be a small or mid-size public company in this environment. Enterprise software companies have seen revenue multiples compress as AI disrupts large swaths of the economy. The fear is not always rational — a business with strong recurring revenue, a loyal customer base, and a capable management team does not suddenly stop being valuable because a language model exists. But perception drives price. And right now, perception is indiscriminate in its punishment of anything outside the AI spotlight.
The result is a growing cohort of public companies that are structurally sound, operationally profitable, and trading well below what a rational assessment of their business would suggest. Not because they are broken. Because they are overlooked.
Three structural forces have combined to create and entrench this mispricing. The first is the passive investing wave. Passive funds now account for approximately 62% of small-cap fund assets, up from 40% in 2014. Passive strategies cannot discriminate between a fairly priced company and one trading at 30 cents on the dollar of net asset value. Capital flows indiscriminately. The result is a systematic failure to correct prices that are obviously wrong.
The second force is the analyst coverage desert. While large-cap stocks are typically covered by an average of 16.4 sell-side analysts, small caps receive coverage from only about 5.7. For micro-cap companies below $300 million in market capitalisation, coverage thins further still, with nearly one-third covered by a single analyst or none at all. Markets are informationally efficient only where information flows. Where it does not, mispricing can persist indefinitely.
The third force is the M&A gap. Private equity firms in the U.S. alone sit on an estimated $1 trillion in dry powder. Yet that capital is systematically directed toward private businesses or larger public companies where deal economics justify the infrastructure costs of a major transaction. Sub-$300 million public companies fall below the minimum viable deal size for institutional capital. They are not overlooked because they are bad businesses. They are overlooked because the market has no systematic mechanism to unlock their value.
The Opportunity in the Shadow
The Opportunity in the Shadow
The Opportunity in the Shadow
This dynamic is not new. Every major technology wave in history — the internet buildout, the mobile revolution, the cloud era — created the same pattern. Capital and attention concentrated at the frontier. Companies adjacent to the frontier got mispriced. Patient acquirers who understood the underlying businesses made excellent deals.
The AI investment cycle is also beginning to generate real productivity gains, with businesses across industries integrating AI as a strategic operational tool.4 Those gains will accrue to established businesses with real customers and recurring revenue — precisely the companies that are currently being overlooked in favour of AI-narrative stocks.
Altuva Group is a NASDAQ-listed permanent capital vehicle built to fill this gap. The platform acquires undervalued public companies using Altuva's own publicly traded equity as acquisition currency. This is not a fund with a fixed mandate and a finite timeline. It is a compounding vehicle designed to grow with every transaction.
By acquiring companies trading at 30 to 50 cents on the dollar of NAV using Altuva equity that trades at a meaningful premium to NAV, each deal is immediately accretive to NAV per share. The acquisition currency grows. The platform's capacity to execute the next deal grows with it.
The team brings over 160 years of combined experience in special situations, distressed investing, and complex capital structures, drawn from Oaktree Capital, Elliott Management, Brevan Howard, Cerberus, BlackRock, Macquarie, and Merrill Lynch, with more than $30 billion deployed across special situations globally.
The Next Phase
Meanwhile, investor rotation is already beginning. Goldman Sachs Research notes that investors have started shifting attention from AI infrastructure companies, where earnings growth is under pressure from intensifying capex requirements, toward companies with clearer links between capital spending and revenue generation.
The rise of passive investing, the retreat of sell-side analyst coverage from smaller companies, and the absence of systematic acquirers at the sub-$300M level are all durable features of modern capital markets, not temporary dislocations.
Research Affiliates projects that U.S. small-cap indexes can outperform large-cap peers by 4% annualised over the next decade, driven directly by the extremity of the current discount.
A company with a stable customer base, positive cash flow, and tangible assets does not become less valuable because it is not in the AI business. In many cases, it becomes more valuable as AI tools improve its operating margins, reduce its cost base, and allow it to serve more customers with the same headcount. The market has not yet priced this.
Altuva Group is a NASDAQ-listed permanent capital vehicle built to fill this gap. The platform acquires undervalued public companies using Altuva's own publicly traded equity as acquisition currency. This is not a fund with a fixed mandate and a finite timeline. It is a compounding vehicle designed to grow with every transaction.
By acquiring companies trading at 30 to 50 cents on the dollar of NAV using Altuva equity that trades at a meaningful premium to NAV, each deal is immediately accretive to NAV per share. The acquisition currency grows. The platform's capacity to execute the next deal grows with it.
The team brings over 160 years of combined experience in special situations, distressed investing, and complex capital structures, drawn from Oaktree Capital, Elliott Management, Brevan Howard, Cerberus, BlackRock, Macquarie, and Merrill Lynch, with more than $30 billion deployed across special situations globally.
The Top Spenders
Amazon
Alphabet
Microsoft
Meta
Oracle
U.S. small-cap P/E discount to large caps: 26% (ex-unprofitable)
International small-cap discount to local large caps: 8%
Passive funds' share of small-cap assets: 62% (up from 40% in 2014)
Average analyst coverage, large caps: 16.4 analysts
Average analyst coverage, small caps: 5.7 analysts
Micro-caps with one analyst or fewer: approximately one-third
U.S. private equity dry powder: ~$1 trillion
The Overlooked Profile
Strong recurring revenue
Loyal customer bases
Structurally sound and profitable
Trading at compressed multiples
$30B+
Combined capital deployed by the team across special situations globally
160 yrs
Combined team experience in special situations and distressed investing
Altuva's Solution
All-stock mergers
No cash changes hands
No debt loaded onto business
Meaningful retained equity
~$90M in annual revenue
$15M in adjusted EBIT
7+ completed acquisitions
15+ global markets
9-year operating track record
Software and digital commerce focus
What Altuva Offers
These Companies
What Altuva Offers
These Companies
Four Reasons Debt-Financed Deals Stall in This Environment
Four Reasons Debt-Financed Deals Stall in This Environment
A company facing compressed multiples in the shadow of AI has options. They can absorb quarterly scrutiny, pursue a depressed cash sale, or find a partner who understands their underlying value.
A company facing compressed multiples in the shadow of AI has options. They can absorb quarterly scrutiny, pursue a depressed cash sale, or find a partner who understands their underlying value.
A company facing compressed multiples in the shadow of AI has options. They can absorb quarterly scrutiny, pursue a depressed cash sale, or find a partner who understands their underlying value.
01
01
All-Stock Mergers
Altuva acquires through all-stock mergers. No cash changes hands. No debt is loaded onto the business, allowing operations to continue unhindered by leverage.
Altuva acquires through all-stock mergers. No cash changes hands. No debt is loaded onto the business, allowing operations to continue unhindered by leverage.
02
02
Retained Equity
The founding team and shareholders retain meaningful equity in a combined, NASDAQ-listed entity, maintaining upside rather than selling out at a discount.
The founding team and shareholders retain meaningful equity in a combined, NASDAQ-listed entity, maintaining upside rather than selling out at a discount.
03
03
Platform Scale
Partners join a platform actively working to close the gap between its companies' market prices and their actual worth across multiple cycles.
Partners join a platform actively working to close the gap between its companies' market prices and their actual worth across multiple cycles.
Market Dynamics
How Capital is Pricing Different Technology Cohorts
All-Stock vs. Alternative Structures for Mid-Market Companies
Cohort
Cohort
Market Perception
Market Perception
Underlying Reality
Underlying Reality
AI Infrastructure Providers
AI Infrastructure Providers
Generational growth opportunity, priced at extreme premiums
Generational growth opportunity, priced at extreme premiums
Intensive
Intensive
High capex requirements pressure near-term earnings
High capex requirements pressure near-term earnings
Productivity Beneficiaries
Productivity Beneficiaries
Beginning to attract capital as rotation out of infrastructure starts
Beginning to attract capital as rotation out of infrastructure starts
Emerging
Emerging
Clear links between capital spending and revenue generation
Clear links between capital spending and revenue generation
Overlooked Public Companies
Overlooked Public Companies
Indiscriminately punished outside the AI spotlight
Indiscriminately punished outside the AI spotlight
Mispriced
Mispriced
Stable customers, margin expansion potential via AI adoption
Stable customers, margin expansion potential via AI adoption
The Long
View
$3.5 Trillion Waiting for Control
The Long
View
The concentration of capital and attention at the top of the market is a feature of this cycle, not a temporary distortion. And the shadow it casts over smaller public companies is not going away.
For the right companies, that shadow is the opportunity. For the right partner, this is exactly the moment to act.
We are not trying to ride the AI wave. We are building a holding company designed to compound value across multiple cycles, multiple sectors, and a portfolio of businesses that the market has not yet learned to appreciate.
If you lead or advise a public company that is ready for a different kind of conversation, we would like to hear from you.
Sources & Citations
CreditSights. "Technology: Hyperscaler Capex 2026 Estimates." know.creditsights.com, November 2025. Top 5 hyperscalers projected to spend ~$602 billion in 2026, up 36% year-over-year; ~75% ($450B) targeting AI infrastructure.
Goldman Sachs. "Why AI Companies May Invest More Than $500 Billion in 2026." goldmansachs.com, December 2025. Hyperscaler capex 2025–2027 projected at $1.15 trillion; equity gains concentrated in AI infrastructure; AI productivity beneficiaries lagging earnings trajectory.
Morningstar. "AI Arms Race: How Tech's Capital Surge Will Reshape the Investment Landscape in 2026." morningstar.com, December 2025. Seven AI-linked companies grew from 9.7% to 28.7% of Morningstar U.S. Target Market Exposure Index over 10 years.
PwC. "Global M&A Industry Trends: 2026 Outlook." pwc.com. AI is spreading rapidly across industries; between $5tn and $8tn required over next five years for AI technologies and enabling infrastructure.
Futurum Research. "AI Capex 2026: The $690B Infrastructure Sprint." futurumgroup.com, February 2026. Detailed breakdown of hyperscaler capex commitments for 2026: Amazon ~$200B, Alphabet $175–$185B, Meta $115–$135B, Microsoft ~$120B+, Oracle ~$50B.
What is your company's
true value?
What is your company's
true value?
What is your company's
true value?
A 30-minute call is all it takes.
A 30-minute call is all it takes.
A 30-minute call is all it takes.
