What do financial advisers need to know about AI?

Since ChatGPT’s launch in November 2022, the S&P 500 Index has gained around 70%, driven by a 280% return for the mega-cap tech stocks dubbed the MAG7.

Although there have been periods of volatility, AI has been considered by many to be a winning trade so far. The concentrated nature of the performance is due to the current concentrated nature of the benefits of the AI evolution. AI is expected to be a widely transformative technology. However, it’s the hyper-scalers that provide key cloud services to facilitate AI, and the picks and shovels businesses that design and produce chips and hardware, which have seen the biggest financial benefits so far.

With technical complexity, large capital investment and supply chain ecosystems, these businesses have faced little-to-no competition. Most have been extremely cash-generative and have had increasingly large earnings growth rates. 

Despite strong financial performances of these businesses, there have been mounting concerns because of the high valuation levels they currently trade on.

We don’t view current capex levels in the AI sector as comparable to the Dot-Com Bubble. Given the structural differences, today’s investments are led by profitable mega-cap firms with strong balance sheets and internally funded growth. Vendor financing deals within the AI ecosystem are measured, performance-based, and aimed at securing supply chains, reflecting strategic moat-building rather than speculative excess.

Should we worry about the broader US economic backdrop?

Looking to the wider US market and economic backdrop, we’ve seen continued resilience and earnings growth throughout the year. This is despite the policy uncertainty around President Trump’s Department of Government Efficiency (DOGE) efforts, tariff moves and Government shutdown. AI and the capex cycle have clearly been big drivers. However, the consumer in the US has also remained resilient and the employment backdrop, whilst softening, hasn’t hit concerning levels. This has allowed the broader market to continue performing well so far.

What about exposure to AI from beyond the US?

Companies that have already benefited from the AI theme aren’t only located in the US, although this is where most have been listed. Notable examples include Taiwan Semiconductor in Taiwan and ASML in the Netherlands which create chips and manufacturing equipment to the produce them. Due to the complex nature of the production process, these companies are effectively monopolies with regards to their respective products as things stand. 

Since the beginning of the year, Chinese technology companies have been supported by a broadening out of the AI theme. Investors have looked to this market as a source of competition, both in terms of models but also use cases and monetisation. The Korean stock market has also benefited noticeably this year due to Samsung and SK Hynix, both chip manufacturers.

What does this mean for portfolio construction?

We believe investors looking to capture the AI theme should consider a balanced approach to asset allocation. Diversification is crucial. 

Market cap-weighted equity indices can offer core exposure, particularly to US mega-cap tech, but opportunities also exist in Europe, Asia Pacific and China. 

While fixed income offers limited direct AI exposure, infrastructure assets could indirectly benefit from AI-driven demand for data centres and energy. 

We’re focused on strategic allocation being complemented by dynamic positioning where necessary. We’re prepared to adjust for valuation, concentration risk and macro conditions. AI-linked companies with strong earnings potential and low macro sensitivity could offer resilience in uncertain environment, making them a compelling long-term investment theme in our view.

While short-term risks exist, such as earnings disappointment or investor impatience, we believe AI-related companies remain well-positioned due to their ability to generate resilient, macro-insulated growth.

What’s important is a truly multi-asset approach across geographies, market caps and asset classes.