Investing in AI Stocks vs. AI Users

The artificial intelligence revolution is creating new investment opportunities — as well as new complexity — for discerning investors. Should you invest in companies building AI or in businesses using it to scale faster and operate more efficiently? This question requires understanding of both technological innovation cycles and fundamental business dynamics.

The investment landscape offers two pathways: direct exposure through investing in AI stocks that develop underlying technologies, or indirect exposure through companies integrating AI into operations. AI builders may exhibit higher growth potential but with high volatility, while AI users, more specifically, companies that use AI for business operations, may offer steadier returns with lower risk. Sophisticated investors are pursuing strategic allocation across both categories, focusing on companies with sustainable competitive advantages.

At Avidian Wealth Solutions, we understand that making the most of AI investment opportunities requires personalized analysis aligned with your financial goals. To explore how these strategies might fit your portfolio, we invite you to schedule a conversation with our wealth management team.

Is it wise to invest in AI stock?

Investing in AI companies presents both extraordinary opportunities and significant challenges that require careful consideration. AI companies are positioned at the center of a technological shift that could reshape virtually every industry, potentially creating trillion-dollar markets in areas from autonomous systems to personalized medicine.

Investing in AI does, however, demand sophisticated investment risk management approaches, due to several key factors:

• Valuation volatility: Prices often reflect optimistic future projections rather than current fundamentals, creating potential for significant corrections
• Technology obsolescence: Today’s breakthrough could become tomorrow’s outdated standard as innovation accelerates
• Geopolitical risk: Export controls, trade restrictions, and national security considerations increasingly impact AI companies’ operations and growth prospects
• Market concentration: Leadership concentrated among a handful of companies creates systemic risks
• Supply chain vulnerabilities: Dependencies in semiconductors and specialized hardware pose operational challenges

The combination of transformative potential and multifaceted risks means successful AI investing requires balancing opportunity against complexity. This demands careful due diligence, strategic diversification, and position sizing appropriate to your risk tolerance and investment timeline.

Investing in AI builders vs. AI users

Understanding the distinction between AI builders and AI users is crucial for constructing a balanced technology investment strategy. These two categories offer fundamentally different risk-return profiles, market dynamics, and growth trajectories that can serve complementary roles in a sophisticated portfolio.

AI builders

AI Builders are the pure-play technology companies developing the foundational infrastructure of artificial intelligence:

• Higher growth potential: Direct beneficiaries of AI adoption across all industries, with revenue that can scale exponentially as demand increases
• Greater volatility: Stock prices subject to technology cycles, competitive dynamics, and shifts in AI development paradigms
• Winner-take-all dynamics: Market leaders can establish dominant positions, but competition is fierce and technological disruption constant
• Capital intensity: Require massive investments in research, development, and infrastructure with uncertain payback periods
• Regulatory exposure: Face increasing scrutiny over data privacy, market concentration, and national security implications

AI users

AI Users, by contrast, encompass established companies across traditional sectors that are integrating AI to enhance their operations:

• Operational efficiency gains: Generate value through cost reduction, process optimization, and enhanced decision-making capabilities
• Lower volatility: Benefit from diversified revenue streams and established business models that provide stability
• Gradual adoption curve: AI implementation tends to be methodical and measured, creating steady but incremental improvements
• Defensive characteristics: Often represent essential services or established market positions that AI enhances rather than replaces
• Implementation risk: Success depends on execution capability and change management rather than technological innovation

The key insight for investors is that these categories often move in different cycles and respond to different market forces, making them potentially valuable complements in a diversified approach to AI investing.

Continue reading: Will AI replace financial advisors?

How to invest in AI builders and users strategically

Successful AI stock investing requires a strategic framework that acknowledges both the sector’s transformative potential and its inherent complexity. Rather than chasing headlines or following momentum, sophisticated investors benefit from structured approaches that align with their risk tolerance and investment objectives.

Here’s what to consider:

Portfolio allocation strategy

A common approach is to treat AI as one component of a diversified technology allocation rather than a standalone bet. Some investors choose to limit direct AI exposure to a lower percentage of their equity portfolio, depending on factors such as risk appetite and investment timeline. 

For many high-net-worth investors, AI may function as part of their strategic alternative investment allocation, providing exposure to emerging innovation trends while remaining mindful of portfolio balance.  Within an AI allocation, investors may evaluate a mix of AI builders and AI users based on their preferences regarding growth characteristics versus stability considerations.

Due diligence framework

Effective analysis when investing in artificial intelligence stocks requires evaluating both traditional financial metrics and technology-specific factors. Examine companies’ competitive moats, such as: 

• Proprietary data advantages
• Network effects
• Regulatory barriers to entry

Assess management’s track record in executing technology transitions and their ability to attract top-tier talent. For AI users, focus on implementation capabilities and measurable efficiency gains rather than just AI adoption announcements.

Timing and market cycle considerations

AI investing benefits from a long-term perspective that looks beyond current market sentiment and valuations. Consider dollar-cost averaging into positions during periods of elevated volatility, as AI stocks often experience significant price swings driven by sentiment rather than fundamentals. Pay attention to broader technology adoption cycles, regulatory developments, and macroeconomic factors that could impact AI company performance over multi-year periods.

Direct versus indirect exposure methods

Investors can gain AI exposure through individual stocks, sector-focused ETFs, or broader technology funds that include AI components. Direct stock selection may offer high potential returns but requires significant research and monitoring capabilities. 

ETFs and professionally managed funds provide diversification and access to investment management services with AI expertise, though they may include companies with limited AI exposure. Consider your research capacity and risk tolerance when choosing between concentrated and diversified approaches.

Risk management and position sizing

Given AI’s volatility and uncertainty, implement strict position sizing and risk management protocols. One illustrative example is limiting any single AI stock to a small percentage of the overall portfolio, and establishing clear criteria for adding to or reducing positions based on fundamental developments rather than price movements. Investors may also consider tools such as stop-loss orders or hedging strategies for larger positions, and regularly rebalance to maintain to keep exposures aligned with their intended allocation ranges.

Common mistakes in AI investing

Even sophisticated investors can fall into predictable traps when investing in AI. The sector’s rapid evolution and media attention create unique behavioral and analytical challenges that can derail otherwise sound investment strategies.

• Chasing momentum without fundamentals: Buying AI stocks based solely on price performance or media coverage rather than evaluating underlying business models, competitive positioning, and financial health.
• Confusing AI adoption with AI capability: Investing in companies that announce AI initiatives without assessing their actual implementation success, measurable benefits, or technological sophistication.
• Overconcentration in market leaders: Putting too much capital into a few high-profile AI companies while ignoring diversification across the broader AI ecosystem and related beneficiaries.
• Ignoring valuation discipline: Paying excessive premiums for AI exposure without considering whether current prices reflect realistic growth scenarios and competitive dynamics.
• Misunderstanding the timeline: Expecting immediate returns from AI investments when many applications require years to develop, implement, and generate meaningful revenue impact.
• Neglecting regulatory and geopolitical risks: Underestimating how government policies, export controls, and international tensions could impact AI companies’ operations and market access.
• Following ETF labels blindly: Assuming that funds labeled as “AI” or “artificial intelligence” actually provide meaningful exposure to the AI theme rather than examining underlying holdings.
• Treating AI as a monolith: Failing to distinguish between different AI applications, business models, and market dynamics across sectors like healthcare, finance, and manufacturing.

Avoiding these common mistakes requires ongoing education, disciplined analysis, and often the guidance of advisors who have experience in navigating emerging technology investments.

Ready to explore AI investment opportunities? Let’s talk.

Investing in AI stocks can represent both opportunities and challenges for high-net-worth investors. The decisions you make in this rapidly evolving sector can impact your portfolio’s long-term performance and risk profile. 

At Avidian Wealth Solutions, our experienced team works with investors throughout Houston, Austin, Sugar Land, and The Woodlands to help develop investment strategies that aim to capture AI’s potential while managing its inherent complexities and risks. Whether you’re considering direct exposure to AI builders, exploring opportunities among AI users, or seeking to balance both approaches within your broader portfolio, our personalized guidance can help you evaluate this investment landscape. 

Schedule a conversation with our wealth management professionals to explore how AI investment strategies might align with your financial goals and risk tolerance.

This article is for informational purposes only and is not intended to constitute investment, tax, or financial advice. The views expressed are general in nature and should not be interpreted as tailored recommendations for any individual investor. Investing involves risk, including the potential loss of principal, and past performance is not indicative of future results. Before making any investment decisions, you should consult with a qualified financial advisor who understands your personal circumstances, financial goals, and risk tolerance.

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