A strategic overview of the AI value chain, ETF exposures which represent each level of the ecosystem, and the investment lenses most relevant to long-term portfolio positioning in the AI trade.
AI Ecosystem: Investment Framework
Prepared by Christina F. Copeland · June 2026
A strategic overview of the AI value chain, the ETF exposures that represent each level of the ecosystem, and the investment lenses most relevant to long-term portfolio positioning in the AI trade.
Investment Lenses
Investment Lens
Relevance to AI Investing
Capital Intensity
Assesses how much ongoing investment is required to compete in each layer of the AI ecosystem. Hardware, power, and infrastructure require far more capital than the software layer. 2026 is capital intense.
Margins
Highlights where economics may be most attractive over time. Software and platform businesses often offer higher margins than infrastructure.
Adoption
Measures how quickly and broadly AI is being implemented across real-world workflows, industries, and business models.
Durability
Evaluates whether the advantages of AI are likely to persist through new technology, scarce resources, regulatory changes, and increased costs.
Summary
Artificial intelligence is evolving through a layered ecosystem that spans computing, digital infrastructure, cloud platforms, software applications, and physical automation. From an investment perspective, each layer presents a distinct combination of capital intensity, margin profile, adoption timing, and durability of competitive advantage.
I’ve organized the AI opportunity set into six categories and outlined options using CCA, Inc.’s preferred method of investing in diversified, tax-efficient, low-cost ETFs over individual stock names for both targeted and diversified exposure. The objective is not to identify a single winner, but to allocate where there may be value as AI adoption continues to expand.
I. Semiconductors
SOXX provides exposure to semiconductor names that enable AI training and inference. It is a direct way to participate in the top foundational layer of AI.
XSD offers broader, more equal-weighted semiconductor allocation across a wider set of companies rather than relying on the largest names as SOXX does.
SMH is a more concentrated semiconductor vehicle that leans toward large-cap industry leaders such as NVIDIA and Taiwan Semiconductor. Similar to SOXX, more concentrated.
II. Data Centers, Infrastructure, and Water
SRVR offers exposure to digital infrastructure real estate (REITs) tied to data centers and connectivity. It is one of the more direct ways to invest in the physical assets of AI.
PAVE — while not a pure AI fund, it can benefit from the need for power, industrial equipment, and construction, and has a global allocation.
XLB — a fund that CCA, Inc. has used pre data centers. Similar to PAVE yet US based. Adds broad materials exposure to construction, chemicals, and industrial materials.
PHO — a fund that CCA, Inc. has used for exposure to the limited resource of water given climate change, now relevant within AI as critical in cooling and maintaining data centers.
III. Cloud, Platforms, and Models
SKYY offers exposure to cloud computing businesses that provide environments where many AI workloads are built, trained, and deployed at the platform layer of AI adoption.
CLOU — software businesses that may benefit from rising demand for the consolidation and organization of data using AI. CRMs such as Salesforce are a good example at this layer.
AIQ spans multiple parts of the AI ecosystem, including semiconductors, software, cloud computing, and infrastructure in one diversified fund.
IV. Applications, Enterprise AI, and Security
AIQ also fits at the application layer. See above — it encompasses multiple layers.
IGV provides enterprise software exposure that may benefit as organizations embed AI into workflows and daily productivity. Microsoft’s Copilot is a good example.
CIBR is especially relevant as cybersecurity becomes more important to protecting models, enterprise systems, and the growing value of AI-enabled infrastructure.
V. Robotics and Physical AI
BOTZ offers targeted exposure to robotics and automation companies, reflecting the view that AI increasingly moves from digital into industrial and operational environments.
ROBO provides broader exposure to automation and robotics across industries, capturing the productivity potential of physical AI over time.
ARKQ focuses on autonomous technology and robotics, making it more of a long-term, growth-oriented investment and likely to be volatile.
VI. Power, Grid Modernization, and Electrification
VOLT focuses on electrification power and demand driven by AI. VOLT provides exposure to companies involved in electrification, transmission infrastructure, power management, and grid modernization.
XLI provides exposure to electrical equipment, engineering, industrial automation, and infrastructure companies that may benefit from AI.
Conclusion
The AI narrative has evolved beyond semiconductors alone. There are opportunities in the physical structure required to support the future of AI. This includes adoption, data center build-out, water resources, cybersecurity, robotics, and electrification.
Disclosure
This document is for informational and educational purposes only and is not intended to be, nor should it be construed or used as, an offer to sell, or a solicitation of any offer to buy, any security, or to enter into any advisory relationship, or to make any investment decision. Additionally, the information herein is not intended to provide, and should not be relied upon for, legal advice or investment recommendations. You should make an independent investigation of the matters described herein, including consulting your own advisors on the matters discussed herein.
The information contained in this document has been obtained from published and non-published sources available as of the published date of this document.
The securities identified and described do not represent all of the securities purchased, sold, or recommended for client accounts or the securities available in each sector. The ETFs in the sector discussed are subject to change. The reader should not assume that an investment in the securities identified was or will be profitable.
Conservest is not affiliated with, sponsored by, or otherwise associated with any of the exchange-traded funds (ETFs), funds, or securities referenced herein.
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AI ECOSYSTEM: INVESTMENT FRAMEWORK 2026
AI Ecosystem: Investment Framework
Prepared by Christina F. Copeland · June 2026
A strategic overview of the AI value chain, the ETF exposures that represent each level of the ecosystem, and the investment lenses most relevant to long-term portfolio positioning in the AI trade.
Investment Lenses
Summary
Artificial intelligence is evolving through a layered ecosystem that spans computing, digital infrastructure, cloud platforms, software applications, and physical automation. From an investment perspective, each layer presents a distinct combination of capital intensity, margin profile, adoption timing, and durability of competitive advantage.
I’ve organized the AI opportunity set into six categories and outlined options using CCA, Inc.’s preferred method of investing in diversified, tax-efficient, low-cost ETFs over individual stock names for both targeted and diversified exposure. The objective is not to identify a single winner, but to allocate where there may be value as AI adoption continues to expand.
I. Semiconductors
SOXX provides exposure to semiconductor names that enable AI training and inference. It is a direct way to participate in the top foundational layer of AI.
XSD offers broader, more equal-weighted semiconductor allocation across a wider set of companies rather than relying on the largest names as SOXX does.
SMH is a more concentrated semiconductor vehicle that leans toward large-cap industry leaders such as NVIDIA and Taiwan Semiconductor. Similar to SOXX, more concentrated.
II. Data Centers, Infrastructure, and Water
SRVR offers exposure to digital infrastructure real estate (REITs) tied to data centers and connectivity. It is one of the more direct ways to invest in the physical assets of AI.
PAVE — while not a pure AI fund, it can benefit from the need for power, industrial equipment, and construction, and has a global allocation.
XLB — a fund that CCA, Inc. has used pre data centers. Similar to PAVE yet US based. Adds broad materials exposure to construction, chemicals, and industrial materials.
PHO — a fund that CCA, Inc. has used for exposure to the limited resource of water given climate change, now relevant within AI as critical in cooling and maintaining data centers.
III. Cloud, Platforms, and Models
SKYY offers exposure to cloud computing businesses that provide environments where many AI workloads are built, trained, and deployed at the platform layer of AI adoption.
CLOU — software businesses that may benefit from rising demand for the consolidation and organization of data using AI. CRMs such as Salesforce are a good example at this layer.
AIQ spans multiple parts of the AI ecosystem, including semiconductors, software, cloud computing, and infrastructure in one diversified fund.
IV. Applications, Enterprise AI, and Security
AIQ also fits at the application layer. See above — it encompasses multiple layers.
IGV provides enterprise software exposure that may benefit as organizations embed AI into workflows and daily productivity. Microsoft’s Copilot is a good example.
CIBR is especially relevant as cybersecurity becomes more important to protecting models, enterprise systems, and the growing value of AI-enabled infrastructure.
V. Robotics and Physical AI
BOTZ offers targeted exposure to robotics and automation companies, reflecting the view that AI increasingly moves from digital into industrial and operational environments.
ROBO provides broader exposure to automation and robotics across industries, capturing the productivity potential of physical AI over time.
ARKQ focuses on autonomous technology and robotics, making it more of a long-term, growth-oriented investment and likely to be volatile.
VI. Power, Grid Modernization, and Electrification
VOLT focuses on electrification power and demand driven by AI. VOLT provides exposure to companies involved in electrification, transmission infrastructure, power management, and grid modernization.
XLI provides exposure to electrical equipment, engineering, industrial automation, and infrastructure companies that may benefit from AI.
Conclusion
The AI narrative has evolved beyond semiconductors alone. There are opportunities in the physical structure required to support the future of AI. This includes adoption, data center build-out, water resources, cybersecurity, robotics, and electrification.
Disclosure
This document is for informational and educational purposes only and is not intended to be, nor should it be construed or used as, an offer to sell, or a solicitation of any offer to buy, any security, or to enter into any advisory relationship, or to make any investment decision. Additionally, the information herein is not intended to provide, and should not be relied upon for, legal advice or investment recommendations. You should make an independent investigation of the matters described herein, including consulting your own advisors on the matters discussed herein.
The information contained in this document has been obtained from published and non-published sources available as of the published date of this document.
The securities identified and described do not represent all of the securities purchased, sold, or recommended for client accounts or the securities available in each sector. The ETFs in the sector discussed are subject to change. The reader should not assume that an investment in the securities identified was or will be profitable.
Conservest is not affiliated with, sponsored by, or otherwise associated with any of the exchange-traded funds (ETFs), funds, or securities referenced herein.