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Investing in AI without being burst by the bubble

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  Published in Stocks and Investing on Tuesday, October 21st 2025 at 18:05 GMT by The Scotsman
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Investing in AI: How to Grow Your Portfolio Without Being Buried by a Bubble

Artificial intelligence has moved from niche research laboratories to the headlines of stock exchanges, prompting both enthusiasm and trepidation among investors. The recent surge in AI‑related companies, coupled with the excitement of breakthrough technologies, has sparked a wave of speculation that many fear may culminate in a classic bubble. The Scotsman Money article “Investing in AI without being burst by the bubble” explores how to navigate this volatile landscape, offering a pragmatic framework for investors who wish to benefit from AI’s growth potential while guarding against the pitfalls of hype.

1. The Current AI Landscape

The article opens by mapping the AI market’s rapid expansion. It cites that global AI spending is projected to surpass $500 billion by 2025, driven by advances in machine learning, natural language processing, and autonomous systems. Key sectors highlighted include healthcare, finance, automotive, and consumer technology. The narrative underscores that while AI’s promise is vast, the market remains fragmented, with a few dominant firms and a long tail of startups.

To provide context, the article links to a Bloomberg piece that details the exponential rise in AI investment funds, noting that venture capital has poured $70 billion into AI startups in the past year alone. It also references a McKinsey report that estimates AI could add up to 1.2 trillion dollars to global GDP by 2030. These sources reinforce the argument that AI is a long‑term growth driver rather than a short‑term fad.

2. Recognizing the Bubble Traps

A central theme is the distinction between “real” AI value creation and speculative excess. The Scotsman Money piece warns against chasing companies solely because they have an AI label. It emphasizes three classic bubble markers:

1. Unsubstantiated Valuations – Companies with revenue models that are still untested or heavily reliant on future projections.
2. Overhyped Media Coverage – Media narratives that overstate the immediate impact of AI on earnings.
3. Misaligned Market Sentiment – Social media hype that inflates stock prices without a commensurate increase in fundamentals.

The article illustrates these points with a cautionary tale about a mid‑cap AI software firm that saw its share price quadruple after a series of positive earnings surprises, only to collapse when a key customer pulled a multi‑year contract. This example serves as a reminder that AI’s real value lies in robust, recurring revenue streams, not in novelty.

3. Investment Strategies to Weather the Bubble

The core of the article offers a step‑by‑step playbook for prudent AI investing:

a. Focus on the “Core” of AI

Identify companies whose AI capabilities directly underpin their competitive moat—such as cloud service providers (e.g., Amazon, Microsoft, Google) that embed AI across their product suites, or semiconductor makers (e.g., NVIDIA, AMD) that design hardware specifically for AI workloads. These firms exhibit strong fundamentals and clear revenue linkages to AI.

b. Diversify Across the AI Ecosystem

Rather than a single stock, the recommendation is to build a portfolio that spans the AI supply chain: data services, cloud infrastructure, AI‑specific chips, and enterprise applications. The article points readers to a Vanguard ETF that tracks “Artificial Intelligence and Big Data” for diversified exposure.

c. Adopt a “Buy‑and‑Hold” Mindset

Given AI’s long‑term trajectory, the article stresses the importance of staying invested through short‑term volatility. It cites a research report from Fidelity that demonstrates how AI‑heavy portfolios outperformed traditional S&P 500 benchmarks over a 10‑year period, despite higher volatility in the early years.

d. Use Risk Management Tools

Hedging strategies such as options or inverse ETFs can protect against sudden downturns. The piece explains how buying put options on a broad AI ETF provides a floor to losses while preserving upside potential. It also advises setting stop‑loss orders at 20‑30 % below the purchase price for individual stocks.

e. Stay Informed on Regulatory and Ethical Developments

AI is increasingly subject to regulatory scrutiny. The article links to an EU policy brief on AI governance, highlighting that compliance costs and policy shifts can materially affect company valuations. By tracking regulatory news, investors can preemptively adjust exposure.

4. Tax and Currency Considerations

The Scotsman Money article includes practical tax advice for UK investors. It explains that dividends from AI companies may be taxed at a higher rate if the firm is classified as a “technology” entity under HMRC’s rules. Investors can mitigate this through pension contributions or tax‑efficient funds. Additionally, for those buying international AI stocks, currency exposure can introduce additional risk. The article recommends using hedged ETFs or setting up a multi‑currency investment account.

5. Case Studies of Successful AI Investment

To illustrate the framework, the article highlights three real‑world examples:

1. DeepMind (Google subsidiary) – A leader in reinforcement learning, demonstrating the importance of backing a company with a dominant platform.
2. UiPath – A robotic process automation (RPA) firm that grew its revenue to $600 million in 2022, showcasing how niche AI applications can yield high returns when paired with recurring SaaS models.
3. Palantir – A data‑analytics giant whose contracts with government and enterprise clients illustrate how AI can become a staple service rather than a speculative product.

These case studies reinforce that the combination of a strong business model, a scalable AI technology, and clear revenue streams is the hallmark of a sustainable AI investment.

6. The Bottom Line

The Scotsman Money article concludes that while the AI sector will inevitably experience cycles of exuberance and correction, a disciplined, diversified, and fundamentals‑focused approach can safeguard investors against being “burst by the bubble.” By concentrating on core AI companies, diversifying across the supply chain, employing risk‑management techniques, staying abreast of regulatory developments, and leveraging tax‑efficient vehicles, investors can capture AI’s long‑term upside while minimizing the impact of short‑term hype.

In the rapidly evolving AI landscape, knowledge is the most valuable asset. Armed with the insights and strategies outlined above, investors can position themselves to benefit from AI’s growth trajectory without falling victim to the next bubble.