23 Jul 2025
As we move through another wave of technological transformation, financial advisers are increasingly being asked how to position portfolios for the rise of AI. The headlines are dominated by groundbreaking developments and showstopping returns but beneath the surface lies a much more complex and nuanced investment picture.
What part is technology playing in markets? Since 2013, US tech has delivered annualised returns of around 20% - more than double the next best-performing sector which is financials. In 2023 alone, the Magnificent Seven drove nearly 90% of the gains when it came to the main market index. In 2024, IT and communications sectors accounted for over 56% of the index’s performance. Remove them, and the market’s return drops from 25% closer to 11%.
What’s the impact of this degree of concentration? It’s both a strength and a risk. On one hand, the AI opportunity is undeniable but on the other, clients chasing those gains without understanding the true underlying risks could be exposed to excessive volatility, valuation uncertainty, and poor timing. Advisers must help clients balance excitement with realism to avoid the pitfalls of hype.
What’s the average investor’s grasp on AI? Unlike previous digital transformations, AI is less obvious and intuitive for the end investor. The commercial models are not always clear, consumers might use AI-generated tools without knowing who built them and unlike familiar ad-based platforms of the past where the consumer is the product and user behaviour is monetised with targeted advertising, revenue generation in AI is still evolving. Not many clients will understand what differentiates one LLM (Large Language Model) from another or why one may ultimately succeed when another won’t.
What paths are open to the investor? The addressable market is vast - AI can lower costs, speed up decision-making, improve efficiency, and unlock new revenue streams. This opens up two broad investment routes: direct exposure to the creators of AI platforms or indirect exposure through the infrastructure and services that support AI development - such as semiconductors, data centres, or cloud computing.
The second path, involving the so-called ‘picks and shovels’ providers, can offer a more stable route to participation in the AI theme. These companies often enjoy consistent demand regardless of which AI platform is leading the race and their revenue models are typically better established and more diversified. Many asset managers favour this approach as it represents a lower-risk entry point.
What influence do AI-related stocks have on the market? Valuations in AI-related stocks have become stretched and the sheer size and influence of these companies means that they’re not just driving returns, they’re also volatility generators. A single innovation or announcement can significantly move the market with recent reactions to breakthroughs like DeepSeek highlighting how rapidly sentiment and valuations can shift.
How can concentration be managed in portfolios? Betting on a few AI names - even the current leaders - could expose clients to downside if expectations don’t come to fruition. The competitive landscape is evolving quickly, with new players continually emerging but many of the newer entrants are unprofitable and highly dependent on external funding.
From a portfolio construction perspective, advisers should focus on helping clients access the AI opportunity in a balanced way. Allocating to active managers with the ability to navigate rapid change or blending growth exposures with quality and value strategies to reduce concentration risk are relevant strategies in this context.
What about the broader economic implications of AI? It has the potential to transform productivity, reshape labour markets, and redefine competitive advantage but there are challenges and pressing questions around ethics, data privacy, intellectual property, and misinformation. As models are increasingly trained on synthetic data, concerns around bias, accuracy, and reliability will only intensify.
For financial advisers, these challenges reinforce the need for client education. It’s not enough just to be optimistic and passionate about AI’s potential; clients need to understand what they’re investing in and why. Drawing lessons from the dot-com era is instructive: the internet did change the world, but many early investors in unprofitable tech firms lost out when the bubble burst.
Despite the risks, real applications of AI are already emerging. Businesses are using AI to automate routine tasks, personalise customer experiences, generate content, and optimise logistics. As adoption increases, some companies will benefit from stronger margins and competitive positioning and the real investment edge will lie in identifying those businesses with healthy balance sheets and defensible moats.
AI clearly represents one of the most compelling thematic opportunities of this generation but how should advisers approach inclusion within client portfolios? As with any emerging theme, realistic expectations, and a focus on quality are essential. For advisers, the role is not to pick winners, but to help clients access the opportunity without taking undue risk. Risk can be evaluated by focusing on fundamentals. Who is making money today and who might dominate tomorrow? What businesses enable the growth of AI without being overly exposed to a single technological outcome? And which strategies provide exposure to innovation while remaining anchored in valuation discipline?
Market cycles are often driven by narrative, but portfolios should be built on process. Advisers who help clients remain grounded in reality - while still embracing long-term innovation - can harness the opportunity and add meaningful value across the years ahead.
Richard O'Sullivan, Investment Research Manager
Katie Sykes, Senior Marketing Manager
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