The AI Trade Is Evolving Beyond Chips and Mega-Cap Tech
Opportunity is now moving deeper into the value chain — and the money is following. Alpha shows you exactly where.
Market Shift
The First Phase of the AI Trade Is Over
For the past two years, the AI investment thesis was straightforward: buy GPU makers, add large-cap cloud exposure, and wait. That worked when investors focused on model training and the most obvious chip stocks.
But something has shifted. The global semiconductor market is projected to hit $1.29 trillion in 2026 — up more than 50% from last year — and the composition of that growth is changing. Memory revenue is nearly tripling. Data center semiconductors are approaching $477 billion. Hyperscaler spending is flowing downstream into networking, optical components, cooling systems, and power infrastructure.
~3x
Memory Revenue Growth
From commodity to strategic bottleneck
$477B
Data Center Semiconductors
Approaching in 2026
50%+
Semiconductor Market Growth
Global market projected at $1.29T in 2026
According to IDC, CBRE, McKinsey, and the IEA, AI demand is repricing the entire technology stack. Companies positioned at critical bottlenecks are beginning to outperform — and many are not the names clients already own. The question is whether their portfolios reflect the reality that AI is now a full value chain theme, not a single-stock bet.
This Issue
Four Layers of the AI Infrastructure Buildout
Our latest Alpha issue walks through AI as an ecosystem investment. We identify four distinct layers and show you tactical, liquid ways to access each one.
Memory
Moved from cyclical commodity to strategic bottleneck. One focused ETF gives direct access to global high-bandwidth memory leaders — including names difficult to buy individually.
Quantum Computing
Went quiet for six months and just roared back — supported by $12.6B in private capital inflows and $2B in new U.S. government grants.
Data Centers
Vacancy near historic lows, pricing at all-time highs in 2026. A tangible real estate opportunity inside the AI buildout.
Power Infrastructure
AI data center electricity consumption surged 50% last year and is expected to double again by 2030 — a play most investors are still ignoring.
Market Context
Why This Matters Now
The market is becoming more selective. Hardware and infrastructure stocks tied directly to AI capacity are being rewarded, while parts of traditional software face consistent rotational pressure. Investors are asking which software companies will gain pricing power in an AI-driven world (and which will lose it). That concern has already weighed on names exposed to seat-based models and legacy workflow automation.
Clients with broad technology exposure may already be overweight the parts of the market facing headwinds — while missing the companies supplying the memory, networking, data centers, and power that make AI workloads possible at enterprise scale.
The Objective
Not to predict every winner or avoid every loser, but to help clients build thoughtful exposure across the AI value chain while being honest about valuation, sentiment, and where the cycle is maturing.
This issue gives you a framework to do exactly that.
Full Issue
What Subscribers Get in the Full Issue
This is not a surface-level overview. This is a working research report designed to help advisors lead better client conversations and make more informed allocation decisions.
Four Investment Ideas
Memory, quantum computing, data center infrastructure, and power — each with detailed portfolio construction guidance.
Specific ETF Recommendations
Asset size, expense ratios, top holdings, sector breakdowns, and risk profiles included for each idea.
Client-Facing Talking Points
Explains why each layer of the AI value chain matters and how to size positions appropriately.
Actionable, Differentiated Ideas
Context on what makes each opportunity different from the broad technology or semiconductor funds your clients may already own.
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