Q4 2025 Market Commentary

4th Qtr 2025 SCM Market Commentary.pdf

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As we enter the final quarter of the year, the economy continues to grow and the stock market continues to rally. Both the economy and the stock market are being increasingly pulled by the technology sector. Outside of the technology sector, things are not as robust. Inflation continues to be stubbornly high and the employment market is weakening. In this commentary, we will discuss the policy challenges this creates for the Federal Reserve because the policy tools needed to fix a weak labor market are opposite the tools needed to reign in higher inflation.

On the surface, the economy looks quite strong. The Commerce Department’s Bureau of Economic Analysis reported the U.S. economy grew 3.8% last quarter, picking up from the 3.3% economic growth from the second quarter, and contraction of -0.5 in the first quarter. The recent quarters growth are very impressive numbers for an economy our size. However, the threat of tariffs in the first quarter caused retailers to front load imports in the beginning of the year (which subtracts from GDP- Gross Domestic Product growth), and since those same retailers did not import as much later in the year, those GDP numbers are higher. Still, the economy is growing any way you slice the numbers.

Under the headline numbers we see things that concern us. The growth we are seeing is a capital spending boom fueled by technology, mainly an AI (Artificial Intelligence) data center and an electrical capacity build out to service AI. The Wall Street Journal reports that the capital spending for the next twelve months for just Alphabet, Amazon, Meta, and Microsoft is close to $400 billion. This is roughly what the EU (European Union) spends annually on defense, and the EU is subsidizing a war in Ukraine against Russia.

The AI center build out also requires a tremendous amount of power, which is further adding to capital spending. Google reported in August the energy cost for an AI search can range from less than 1 watt hour (Wh) for a simple query to over 40 Wh for a complex request, significantly more energy consumption than traditional search. Thus, data centers have become highly energy-intensive and are expected to consume a significant and growing portion of total electricity in the U.S. In fact, C&C Technology Group estimates data center electric demand growing from 4.4% in 2023 to potentially over 12% of U.S. electric demand by 2028.

Where all this money comes from to fund this build out is still not totally certain. On September 23rd, Bain and Company released their sixth annual Global Technology Report where they estimate that $2 trillion in annual revenue is what is needed to fund computing power to meet anticipated AI demand by 2030. This is a huge number. The report also estimates that even if companies in the U.S. shifted all their on-premise IT budgets to the cloud, and reinvested the savings, and invested all R&D (Research & Development) into capital spending on new data centers, the revenue needed to fund the AI data center boom would still fall short. Moreover, Bain notes that AI’s computer demand grows at more than twice the rate of Moore’s law (Moore's Law is the observation that the number of transistors on a microchip doubles approximately every two years, while the cost of computers is halved).

Other analysts have also questioned where the money is going to come from to pay for the projected needs of the AI buildout. Open AI, perhaps the leading new AI startup company has committed to spend $1 trillion dollars on new AI equipment over the next five years despite the fact it has large and growing losses. Barron’s magazine reported that the money raised in IPO’s (Initial Public Offerings) during the tech bubble of 1995 to the year 2000, raised $209 billion dollars. In other words, the largest tech bubble of all time only raised 20% of what Open AI plans to spend in the next five years. This could be considered a sign of how strong the demand is, or how much hype is building. Open AI’s plan is to raise the money via stock, but it could borrow money as well. The largest corporate borrow in the market right now is Verizon, which has $164 billion in debt, but is backed by $265 billion in assets and a highly reoccurring revenue cell phone business generating stable cash flows to repay the debt. So, even if Open AI plans to borrow the money, it is unclear if they will be able to do so. Therefore, we question how long the AI data center/electrical production build out can last when the revenue might not be there to pay for it.

This reminds us of the internet build out in the late 1990s. During that time Cisco (CSCO) was the largest company in the world by market capitalization. Cisco was the driving force suppling routers and hubs needed to build out the internet. By 2000, Cisco stock had reached $82 per share (stock split adjusted). Currently, twenty-five years later, even after most of the grand projections of the internet have largely come true, Cisco stock trades at under $68. Today, just the largest eight technology companies make up over 35% of the S&P 500 by market capitalization. As a result, any slowdown in AI spending would quickly affect the value of investors accounts. However, as one of our clients in the AI space has pointed out to us, during the dot.com days there was a tremendous amount of unused capacity lying around. The dark fiber (fiber laid in the ground but not being used) took years to put to work. Today, every new GPU (graphical processing unit) the brains behind AI, is being put to use as soon as it is shipped.

Compounding the problem for policy makers is that the labor market has been weak, and inflation remains stubbornly high. Partly due to advances in AI reducing the need for some jobs, job growth has been weak. Laura Ullrich, Charlotte branch of the Federal Reserve Bank, notes that the average monthly job gains since January represent the fewest jobs added over the first eight months of the year in 15 years, excluding the pandemic-triggered crisis period of 2020. "We haven't added these few jobs since 2010, and we have 17 million more people in the labor market than we did then." The U.S. Bureau of Labor Statistics reported an average of +186,000 new jobs per month in 2024, and an average of +216,000 jobs per month in 2023. The jobs growth in August came in at only +22,000 new jobs. Making matters worse, last month, the U.S. Bureau of Labor Statistics (BLS) released revisions showing a significant downward adjustment of job growth for the 12 months leading up to March of 2025, revising it down by 911,000 jobs from the initially reported figures. This means that the job market has been weak for over a year.

This is a key point because the current unemployment rate of 4.3% is still low, but the labor participation rate still has not recovered from the Covid pandemic. If the current labor participation rate was the same level as before Covid hit, the unemployment rate would be closer to 5%, a trigger point at which the Federal Reserve would be more aggressive in cutting interest rates.

This is where the Federal Reserve’s dual mandate of full employment and controlling inflation has them in a bind. The labor market is showing signs that the Federal Reserve should lower interest rates to spur new jobs. The problem is that the country’s inflation rate has been above the Federal Reserve’s official target of 2% for over the last four and half years.

The Federal Reserve has been successful in reducing the year over year inflation from the highs reached during 2022 and 2023, but reaching the final target of 2% has been elusive. If the Federal Reserve lowers interest rates to spur job growth, the Fed runs the real risk of reigniting inflation (creating more jobs than people to fill them causing prices to go up) while at the same time not knowing the full effect that the on-going tariffs are having on inflation or where the final tariff numbers are going to settle out. Moreover, aggressive rate cutting when the economy is growing at 3.8% annually would be unusual, but the growth is primarily being driven by massive capital expenditures in AI data centers and electrical production to fuel those data centers, without a clear path of how those massive expenditures continue to get funded.

Longer term, we believe the Federal Reserve monetary policy is going to be pushed lower due simply because of the size of the U.S. debt load. As of the end of September, the U.S. national debt stood at $37.46 trillion. Moreover, the average interest rate to service this debt has gone from a low 1.75% in 2022 to roughly 3.12% today. That translates into over an additional $1.5 trillion dollars in interest payments annually since the 2022 interest rate lows. The higher interest rates climb, the harder funding the U.S. debt becomes, and the more pressure the Federal Reserve will feel to lower interest rates as soon as possible.

In conclusion, we agree with Cleveland Federal Reserve President Beth Hammack when in late September she said the current economic backdrop is “a challenging time for monetary policy.” The policy tools needed to spur employment growth, are the exact opposite of the policy tools needed to rein in inflation. Moreover, the national debt continues to grow, meaning any kind of restrictive monetary policy will make the national debt even harder to pay off, and make unemployment worse at a time when AI is likely to replace a lot of jobs. Moreover, we believe that the AI build out is still in its early stages, but it is unclear if the growth will be in a straight line as funding for the growth is not guaranteed. As a result, we continue to like companies that provide goods and services that consumers and businesses need to use on a daily basis and who are returning cash back to investors through either or both dividends and share buybacks as the best way to invest to deliver positive risk adjusted returns. Thank you for your continued support.

Sincerely,

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