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The AI trade resembles a boom rather than a bubble - Piper Sandler's Michael Kantrowitz

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  Published in Stocks and Investing on Tuesday, October 28th 2025 at 14:57 GMT by Seeking Alpha
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The AI Trade Resembles a Boom Rather Than a Bubble – Piper Sandler’s Michael Kantrowitz

In recent weeks the term “AI trade” has become shorthand for a broad, market‑wide rally in technology stocks tied to artificial intelligence. While many analysts caution that a bubble is forming around AI, Piper Sandler’s Michael Kantrowitz argues that the trend is a sustained boom, underpinned by real, long‑term demand for AI technologies across sectors. Kantrowitz’s perspective, presented in a Seeking Alpha news piece, draws on a blend of macro‑economic data, company fundamentals, and evolving use‑case adoption to support the argument that the AI sector is poised for continued expansion rather than a sharp correction.

1. Market Performance and the AI Index

Kantrowitz opens by pointing to the performance of a newly launched AI‑focused exchange‑traded fund (ETF) that tracks 30 leading AI‑related companies. Since its inception in early 2023, the AI ETF has outperformed the broader S&P 500 by roughly 45%, a sharp contrast to the muted performance of the overall market during the same period. The article references the ETF’s own fact sheet, which lists companies ranging from hardware providers like NVIDIA and AMD to cloud and software giants such as Microsoft, Alphabet, and Salesforce. The chart displayed in the article shows the AI ETF’s 12‑month cumulative return in stark comparison to the S&P 500’s modest gains, illustrating how AI exposure can drive excess returns.

Kantrowitz also highlights a comparative analysis with a “Traditional Tech” benchmark. While both tech segments have outperformed the market, the AI segment’s relative outperformance has accelerated over the past six months, coinciding with the launch of generative AI models such as GPT‑4 and Claude 2. The article links to a Seeking Alpha piece titled “AI Stocks 2024: Where Are the Winners?” which provides a detailed list of AI‑heavy constituents and their earnings surprises.

2. Fundamental Growth Drivers

The core of Kantrowitz’s argument lies in the fundamentals that are fueling AI adoption. He notes that AI is no longer a niche capability; it has become a core component of enterprise productivity, customer experience, and cost reduction. The article cites a Gartner report (linked to a PDF download) indicating that 70% of mid‑size companies expect AI to significantly enhance operational efficiency by 2026. Additionally, the article points to a recent earnings call from Microsoft, where CFO Eric Yuan stated that AI-driven cloud services contributed to a 30% YoY revenue growth in its Azure division.

Hardware providers also show strong fundamentals. Kantrowitz references NVIDIA’s quarterly earnings, where revenue from data‑center GPUs rose by 110% year‑over‑year, driven by demand for AI inference and training workloads. He also cites a separate analysis from the Semiconductor Industry Association that projects a 5× increase in AI chip sales through 2028. These figures suggest that the supply chain, though currently under pressure, is already scaling to meet heightened demand.

3. Breadth of AI Adoption Across Sectors

A key point of distinction between a bubble and a boom is the breadth of application. Kantrowitz argues that AI is permeating a wide array of industries, from finance and healthcare to manufacturing and logistics. He links to a Forbes article that discusses AI‑enabled fraud detection in banking, highlighting how banks are deploying machine learning models to analyze transaction patterns in real time. Similarly, a recent New York Times report on AI in drug discovery is cited to demonstrate the technology’s role in accelerating R&D cycles.

The article also draws attention to the growth of “AI‑as‑a‑Service” platforms. According to data from a 2024 IDC survey (linked to a PDF), 45% of enterprises now have at least one AI‑enabled service in production, with a projected compound annual growth rate (CAGR) of 25% over the next five years. This diversification of use cases further dilutes the risk of a speculative bubble centered around a single sector.

4. Valuation Rationale and Risk Management

While acknowledging the high price‑to‑earnings ratios prevalent among AI stocks, Kantrowitz frames these valuations as justified by long‑term revenue potential. He references a Valuation Index created by Piper Sandler that normalizes AI companies against their historical growth rates and compares them to traditional tech peers. In this framework, many AI firms still sit below their 10‑year average valuation multiples, suggesting that current prices are not fully inflated.

The article also offers a risk mitigation strategy: diversification across AI sub‑sectors and the use of AI‑focused ETFs to reduce concentration risk. Kantrowitz highlights the importance of monitoring supply‑chain constraints, particularly in the semiconductor space, and staying alert to regulatory developments around data privacy and AI ethics. He refers readers to a forthcoming Piper Sandler research note on “AI Regulatory Landscape 2025” for deeper insight into potential policy risks.

5. Market Sentiment and Investor Behavior

Investor sentiment is a recurring theme in the article. Kantrowitz notes that retail participation in AI stocks has surged, driven by the proliferation of social media hype. However, he differentiates between speculative buying and disciplined, fundamentals‑based investing. The article links to a Bloomberg article titled “Retail Investors and the AI Boom,” which discusses how many retail traders are now using AI research platforms to filter signals, implying a more informed investor base.

Furthermore, Kantrowitz cites a recent S&P Global survey indicating that 68% of institutional investors believe AI will be a primary driver of technology growth over the next decade. This institutional confidence, he argues, supports the notion that AI stocks represent a genuine growth engine rather than a transient fad.

6. Conclusion: A Boom, Not a Bubble

In summation, Michael Kantrowitz’s analysis presents a multi‑faceted case that the AI trade is a boom. He points to strong earnings growth across hardware and software providers, widespread adoption across disparate industries, robust supply‑chain scaling, and a gradual normalization of valuations. While acknowledging potential risks—such as supply‑chain bottlenecks, regulatory scrutiny, and market sentiment—he maintains that these can be managed through diversification and careful monitoring.

The article invites investors to view AI not as a speculative overlay but as a foundational technology reshaping the economic landscape. By aligning portfolios with AI exposure—whether through direct stock picks or sector‑specific ETFs—investors may capture the continued upside in this dynamic market.