AI: There's Silicon in Them Hills

As discussed last week in Part One, Artificial Intelligence (‘AI’) is a natural extension of the technological innovations that began with the proliferation of the Internet over the last 30+ years. Given this connection, and the fact that many readers and investors lived through the “Internet Revolution” in the 90’s, the parallels made between today’s AI-driven market and the ‘Dot.Com’ bubble are unavoidable. We acknowledge the similarities, but also see another piece of US history that could be just as useful as an analog: the California ‘Gold Rush’. In this week’s Strategic View, we want to dig deeper (pun absolutely intended) on this comparison and see what wisdom we can ascertain about today and the near future.

In 1848, gold is discovered in Sutter Mill and in San Francisco, and the gold rush officially began. Using simple tools such as picks and shovels, early miners arrived in mass to extract the surface-level gold. This mining was boom-or-bust; the early miners that found gold had a huge return on investment, but there were more failures than success stories.

As easily extracted gold mining opportunities began to disappear, large mining companies were formed and invested in improving the “picks and shovels” to create more modern mining techniques. This led to a wave of mining innovations that enabled more advanced extraction, which created a more consistent but lower shareholder return. Additionally, due to their size and scale, these mining companies were able to acquire more land and increase the search area for gold.

In the end, the gold rush did not actually end in a ‘bust’, in our view. While the impact of the gold extracted itself was positive, the secondary economic impacts of providing sustenance and infrastructure to a remote part of the US was more profound, as it ended up greatly expanding economic activity in the West. It is widely known that the California gold rush was more profitable for mining companies and the sellers of mining infrastructure than for the miners themselves. Perhaps less understood is that the technological advances in mining and logistics laid the groundwork for the post-Civil War expansion of the United States to become a truly continental nation.

Today we see clear parallels. First, the three parties we discussed above all have modern counterparts, in our opinion:

• Today’s ‘picks and shovels’ providers are represented by the AI infrastructure companies (servers and semiconductor producers) and the industrial infrastructure companies (utilities, cooling, and power generation companies).
• The ‘mining companies’ are represented by “hyperscalers” - providers of data storage, computing and networking.
• The individual ‘prospectors’ are the companies developing today’s early AI applications.

Looking at the timeline laid out by the gold rush, we believe we are still in the early stages of AI proliferation. There are still some surface-level, high risk-and-potential return investments to be made in the early-stage AI applications, many of them speculative and often private companies. We believe that the risks for those early enterprises are akin to being a lone prospector; investments outcomes will be binary, with a lot more losers than winners. Given our more diversified ‘core’ investment philosophy, this is not the kind of speculative prognostication we feel comfortable investing in.

On the other hand, similar to the mining companies of the gold rush, the hyperscalers are currently building infrastructure that will allow for more sustainable investments in the future. We expect profits and growth to slow somewhat from here but remain robust. Investing in this side of the story aligns more with RiverFront’s stock selection process, which focuses on established profitability, earnings and valuations. The physical infrastructure companies are a needed piece of the puzzle that in our view will benefit from organic demand through the hyperscalers’ capital expenditure spending, much like the mining ecosystem of the 1890s. In the table below, we lay out seven different segments of the AI story, how they compare to the gold rush analogy, a description of the segment and some sample companies.

When looking at our current portfolio positioning, all our portfolios are overweight hardware and datacenters relative to their benchmarks, with individual stock positions in each of these segments when our models allow it. Additionally, we have broad exposure to physical infrastructure through thematic ETFs in our longer horizon portfolios. As we continue down our current path, we will monitor the individual companies in each of these spaces and invest in either individual stocks or thematic ETFs when we believe the market is undervaluing their exposure to AI-related drivers.

Looking forward, one of the most important indicators we will watch to differentiate between ‘boom’ or ‘bust’ earnings cycles will be cash flow growth trends in the technology sector (as shown in chart below). We favor cash flow over earnings analysis in tech’s case, as the two concepts are closely related but cash flow is less likely to be ‘gamed’ by accounting tricks.

Tech cash flow growth that is generally consistent with its’ long-term trend of around 11% (blue line on Chart, right) is our Base Case last week’s Strategic View. We believe this pace of growth is more sustainable and will prolong the bull market in stocks. If we begin to see tech cash flow growth start to trend significantly lower (red dotted line), this suggests the AI infrastructure supply is ahead of demand and earnings disappointments are likely to result in a significant decline in share prices – our Bear Case. Conversely, growth rates that more closely replicate the recent 2023-25 AI-driven trend of 18% cash flow growth (green dotted line) match our Bull Case. While this level of growth is clearly good news, the risk is that it creates a true 1990s-style valuation ‘bubble’… but probably not for several years. At that point our concerns will be heightened, and we would have to assess how powerfully AI is transforming other companies and the US economy in order to remain constructive on US stocks broadly.

‘Bubble’ Not Inevitable; Gold Rush Analog Suggests Companies’ Earnings Can Grow into Their Valuations

Many market prognosticators seem to believe that a bubble followed by a bust is the only possible outcome from here. However, as we laid out in last week’s Strategic View, we do not view this as an imminent market outcome. Using the analog of the late 1990s period, we think the S&P 500, if it is indeed headed for a bubble at all, may be only in the relatively early stages today. We will continue to evaluate earnings potential and see if we think valuations are unsustainable and a bubble is forming.

In contrast, we would like to posit a second potential outcome: a more sustained earnings trend, which is analogous to the end of the gold rush. For this scenario to play out, the benefits of AI must become widely adopted and beneficial across our economy. The premise would be that while high valuations may compress returns for AI-centered companies going forward, the medium-term returns will remain positive. Sustainable growth in earnings and cash flow will allow these companies to “grow into” their valuations over time. We currently view this scenario as the most likely.

Additionally, in this scenario, there will be another major opportunity for investors outside of traditional tech. For example, sectors such as healthcare, financials and consumer discretionary are exploring AI applications to help drive higher levels of profitability and growth that might not have otherwise been possible. This “value rotation” could create a multi-stage bull market that broadens out and allows non-tech sectors to participate more in market upside.

By Adam Grossman, CFA

Originally published by RiverFront Investment Group

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