March 2026 Client Letter

The Hermès Paradox

I have never followed luxury brands closely, but one thing has consistently caught my attention: Bernard Arnault’s place near the top of global wealth rankings. At times, the chairman of LVMH, owner of brands such as Louis Vuitton and Tiffany & Co., has ranked alongside Jeff Bezos, Larry Ellison, and Warren Buffett as one of the richest individuals on the planet.

The technology entrepreneurs, I understand. The “Oracle of Omaha,” certainly. But the head of a luxury brand?

That curiosity lingered. When an unusually cold stretch of weather hit this winter, I found an excuse to explore it. I figured my parents could use something warm, so I stopped by Louis Vuitton to pick up a couple of scarves. While there, I struck up a conversation with a sales associate about how business compared with a year ago.

Afterward, I walked next door into Hermès.

I had heard of the Birkin bag, long considered the brand’s most coveted product, but I couldn’t have described one. What struck me immediately was what I did not see. The store was filled with home goods, silk scarves, and leather accessories. But no Birkin bags. The most sought-after products were nowhere to be found.

When I asked a sales associate where I might see one, she explained that none were on display. I asked whether one could be ordered. She smiled and said that isn’t
how it works. First, a customer must establish a relationship with the store. And that relationship involves a broader purchasing history over time.

In effect, the company’s most famous product is not something you can simply buy.

Hermès has operated with gross margins north of 70% and operating margins above 40% in certain periods. These are levels sometimes associated with software firms rather than traditional manufacturers. A company founded in 1837 as a harness workshop operates today with the profit structure and demand dynamics more typical of a modern technology platform.

That combination of scarcity by design, controlled distribution, and durable profitability raises a larger question: What kind of business can limit the availability of its most in-demand product and still strengthen the brand over time?

The answer, I would argue, is a business built on foundations that are deliberately difficult to replicate. Hermès business model does not rely primarily on advertising or short-term demand. It relies on decades of craftsmanship, controlled production, cultural positioning, and disciplined distribution. Those characteristics cannot be manufactured overnight. They require time, consistency, and restraint — qualities that resist quick replication.

In investing, we often find many of the most durable businesses share similar traits. They are built patiently over years, sometimes decades, and their advantages tend to resist quick imitation.

Costco: Discipline by Design

If Hermès demonstrates scarcity through controlled access, Costco demonstrates discipline through structural design.

Walk into a Costco warehouse and you may notice what is not there. The selection is limited. Product displays are simple. Marketing is minimal. The company carries a fraction of the products offered by a traditional retailer and operates on intentionally thin merchandise margins. Access to the store itself requires a paid membership, a deliberate gate that reinforces loyalty and recurring revenue.

What makes the structure compelling is that while the products are sold at low margins, the membership program tends to carry far higher economics. The annual
fee, spread across millions of members, generates recurring income that helps support the company’s disciplined pricing model. In effect, Costco can afford to keep product markups restrained because the membership itself carries much of the economic weight.

Costco’s structure has been refined over decades. Supplier relationships are negotiated with extraordinary purchasing power. Pricing discipline is cultural, not promotional. The company often resists maximizing short-term margins in favor of reinforcing long-term trust with its members. The result is a business model that competitors can observe but struggle to recreate. It is more than a warehouse full of goods. It is a system built on operational restraint, cultural consistency, and time.

Like Hermès, Costco’s strength lies less in what it sells and more in how it is structured.

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Key Takeaway

Time is an underrated competitive advantage.

The businesses we favor tend to be built slowly, with structures that competitors can see but rarely reproduce quickly.
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Alphabet: Compounding Data Over Time

If Costco’s advantage is built on operational discipline, Alphabet’s advantage is built on accumulated information.

For more than two decades, Google’s search engine has processed billions of queries each day. Every search and click has contributed to a growing body of data that informs its algorithms and advertising systems. That feedback loop of query, result, and refinement builds on itself over time. It is not a single product advantage but a layered system of infrastructure, machine learning models, and advertising relationships that has evolved for more than 20 years.

Competitors can build search engines. They can invest in artificial intelligence. But replicating two decades of behavioral data, global scale, and advertiser integration would be extremely difficult to replicate quickly. Alphabet’s strength lies less in any single feature and more in the depth of its ecosystem: data centers, software models, and distribution partnerships that reinforce one another.

Like Costco and Hermès, Alphabet’s position is rooted in time. It is the product of years of iteration, reinvestment, and infrastructure buildout that tend to widen slowly and resist quick imitation.

NVIDIA: Engineering That Compounds

If Alphabet’s advantage lies in accumulated data, NVIDIA’s lies in accumulated engineering.

Long before artificial intelligence became a headline topic, NVIDIA was building graphics processing units (GPUs), specialized chips designed to perform many calculations at once. Over time it developed not only hardware but an entire software layer, most notably its CUDA programming platform, which allows developers to write code specifically optimized for its chips. That ecosystem has expanded over the years, embedding itself in universities, research labs, and enterprise data centers around the world.

During the pandemic lockdowns, many households encountered this technology in a different way. My two boys, like many others, spent evenings playing the video game Fortnite with friends across the country. At the time, I did not think much about the underlying hardware. Yet the same specialized chip design that rendered those digital worlds would later become foundational to large-scale artificial intelligence training.

Today, demand for advanced AI computing has brought NVIDIA’s hardware into sharp focus. But the true advantage is not simply the chip itself. It is the surrounding systems of software tools, developer familiarity, optimized libraries, and integrated systems that make those chips widely useful. Competitors can design silicon. They can invest heavily in research. Far more difficult to recreate is the global base of engineers, applications, and workflows that have formed around the platform over time.

Like Hermès, Costco, and Alphabet, NVIDIA’s position reflects time and discipline. Its moat is not a moment. It is an accumulation. And accumulation, once deeply embedded, is hard to displace.

Amazon: Layered Infrastructure at Scale

If Hermès reflects controlled scarcity, Costco reflects operational discipline, Alphabet reflects accumulated data, and NVIDIA reflects ecosystem depth, Amazon reflects infrastructure layered at scale.

Most investors experience Amazon through a package arriving at their front door. For years, that retail convenience defined the company. Today, retail is only the outer surface of a much deeper operation.

Amazon’s retail platform drives traffic. Advertising monetizes that traffic. Amazon Web Services (AWS) monetizes compute. Custom silicon lowers the cost of that compute.

Logistics networks and satellite connectivity extend physical and digital reach. Each layer reinforces the next.

Within its fulfillment centers, Amazon now deploys vast fleets of robots that move inventory, assist workers, and optimize picking and routing. Amazon has also developed robotics capabilities internally over time. What appears to consumers as simple delivery speed is supported by an increasingly automated, data-driven network. This combination of software, robotics, and logistics infrastructure is difficult to replicate.

Importantly, none of this was built quickly.

Amazon’s fulfillment network took decades and tens of billions of dollars before becoming a durable advantage. AWS began nearly 20 years ago as an internal tool before evolving into one of the world’s largest cloud platforms. Today’s investments in data centers, artificial intelligence infrastructure, and proprietary silicon reflect the same long-term orientation: absorbing near-term margin pressure to build assets that are difficult to replicate.

That capital intensity is itself a powerful barrier. Building global data centers, designing custom chips, integrating logistics systems, and deploying satellite networks require scale, patience, and financial flexibility that few companies possess. These advantages take years to replicate.

Competition in cloud computing remains significant. Execution must remain disciplined. Regulatory and capital demands are real. Yet Amazon’s evolution is clear. It is no longer simply a merchant selling goods efficiently. It is constructing the underlying systems through which goods are sold, data is processed, and applications are run.

Infrastructure, once embedded, tends to endure.

In investing, businesses that patiently construct the foundational layers of modern commerce and computing often become among the most difficult to displace.

Of course, even durable businesses operate within broader market cycles.

Market Backdrop: Noise and Fundamentals

So far this year, markets have been unsettled. Major indexes have moved in and out of positive territory, and leadership has rotated across sectors. Historically, strong gains are often followed by digestion, and this year has reflected that pattern.

Recent weeks have added new headlines. Headlines around tariffs and trade policy have introduced additional uncertainty. Renewed geopolitical tensions in the Middle East have unsettled equity and energy markets. War is always a human tragedy, and the images are sobering. From a market perspective, however, investors tend to assess these events based on their potential global economic impact rather than their emotional intensity.

Historically, regional conflicts have generated bursts of volatility, particularly when energy flows are involved. Markets typically adjust as participants evaluate the likely scope of disruption and its implications for global growth. While no outcome is ever certain, broad equity markets have generally proven resilient once initial uncertainty clears.

Beyond the headlines, the broader economic foundation appears constructive. Corporate earnings continue to expand across many industries. Companies investing heavily in artificial intelligence infrastructure—data centers, custom silicon, cloud capacity—are still reporting revenue and profit growth. The capital expenditures drawing scrutiny today resemble investments that in past cycles often became long-term competitive advantages.

We appear to remain in the infrastructure phase of the AI buildout. Chips, servers, robotics, and data centers are being deployed in large numbers, while the application and productivity layers are still developing. If so, today’s spending may represent groundwork rather than excess.

Inflation, while not eliminated, has moderated from prior peaks. Monetary policy remains data-driven, and the Federal Reserve retains flexibility as conditions evolve. Stabilizing interest rates, combined with earnings growth, can provide a supportive backdrop for equities over time.

Risks remain, and markets rarely move in straight lines. Periodic pullbacks are part of the process.

But when I step back from the daily noise, I see more structural positives than negatives: earnings growth, significant long-duration capital investment, inflation pressures that have eased from prior peaks, and a policy environment that is less restrictive.

Within client portfolios, diversification across asset classes and equity sectors has helped navigate this uneven environment with relative stability. That diversification is intentional.

We do not invest based on headlines or short-term forecasts. We invest in businesses we believe are positioned to compound over time—businesses constructed deliberately, with economics that resist imitation.

If earnings continue to grow, history suggests they tend to matter more than the noise.

Bringing It Together

Hermès controls distribution. Costco controls structure. Alphabet compounds data. NVIDIA compounds engineering. Amazon layers infrastructure.

Different industries. Different products. Different management teams.

Yet the common thread is deliberate construction over time.

These businesses did not emerge overnight. They do not depend solely on short-term demand or promotional momentum. Their competitive positions reflect years, often decades, of reinvestment, operational discipline, and strategic patience.

In each case, advantage is the product of accumulation.

At Richard C. Young & Co., Ltd., our philosophy has long centered on a similar principle: diversification and patience built on a foundation of value and compound interest. We seek to align client capital with businesses that, in our view, have advantages that are difficult to erode, whose structures are difficult to replicate, and whose economics allow them to reinvest and strengthen over time. That does not eliminate volatility, nor does it guarantee outcomes. But it does, in our view, tilt the odds toward durability.

Diversification remains essential. No single company, no matter how well constructed, is immune to change. But a portfolio composed of businesses developed deliberately across industries and models can create resilience.

In a market often focused on speed and quarterly results, we continue to favor businesses shaped by time, discipline, and reinvestment.

What is difficult to replicate is often difficult to displace.

And compounding, paired with patience, remains one of the most powerful forces in investing.

As always, we welcome the opportunity to discuss your portfolio and any changes in your financial situation. If you would like to review your positioning or have questions, please call us at (800) 843-7273.

Warm Regards,

Matthew A. Young
President and Chief Executive Officer

February 2026 Client Letter

How everyday observations can lead to investment ideas.

In March of 2023, I was aboard the Celebrity Beyond, somewhere between ports, when something surprised me.

Even though I had promised myself to unplug from the markets for a few days, I couldn’t resist. Silicon Valley Bank had collapsed shortly before we shoved off from Fort Lauderdale, and I was concerned about what its failure could mean for the financial system and for our investments more broadly.

Since we were at sea, I wasn’t expecting much in the way of an Internet signal.

But the Internet worked. Smoothly, quickly, without the usual buffering or dropouts that most of us associate with being miles offshore.

This wasn’t supposed to be possible. At least not according to our old assumptions about how connectivity works.
For decades, Internet access at sea meant compromise: slow speeds, limited access, and frequent disconnects. Yet there I was, staying connected to unfolding financial news as if I were sitting in my office.

The reason for this connection wasn’t the ship.

It was space.

The Celebrity Beyond was the first ship in the Celebrity fleet equipped with SpaceX’s Starlink satellite network, which officially launched aboard the ship in September 2022. Instead of relying on traditional maritime systems, the Beyond pulled connectivity directly from low-Earth-orbit satellites overhead.

That experience stuck with me. Not because the Wi-Fi was fast, but because it revealed how much of our modern life depends on infrastructure we never see. In investing, those unseen systems are often where durability resides.

For many people, space still feels abstract. Rockets. Astronauts. Distant exploration. But space is becoming part of our everyday economy, powering the systems we rely on for navigation, communication, coordination, and awareness, and now even something as ordinary as checking the markets on a cruise ship.

McKinsey estimates the global space economy could reach $1.8 trillion by 2035, driven not just by launches and satellites but by a growing layer of commercial services that support industries ranging from ride-sharing to global supply chains.

The Commercialization of Space

For most of modern history, space was primarily a government project driven by national pride, defense priorities, and scientific exploration. That is changing. Today, much of the momentum in space activity comes from private companies pursuing commercial opportunities. Governments still matter, but increasingly they are customers rather than sole operators.

Several forces have converged to make this possible. Reusable rockets, faster launch cycles, smaller satellites, and more powerful onboard computing have materially lowered the cost and complexity of getting into orbit.

At the center of this shift is SpaceX, which has reset expectations for launch economics and satellite deployment. SpaceX remains a private company, and while there have been periodic reports that it could go public at some point, it is not currently accessible to public-market investors. Even so, its influence is hard to ignore. By normalizing frequent, low-cost launches and deploying thousands of satellites through its Starlink network, SpaceX has effectively forced the rest of the industry to respond.

That response is taking shape through a small number of emerging players. Rocket Lab (RKLB) has positioned itself as a specialist in smaller, more flexible launches and space systems, while AST SpaceMobile (ASTS) is working to build a satellite-based communications layer designed to connect directly with everyday mobile devices. These companies are still early in their development and are not yet consistently profitable, but their progress shows how rapidly the space market is evolving beyond a single dominant player.

What matters for investors is not simply who launches rockets but what those launches enable.

Satellites now form a critical layer of economic and security infrastructure, connecting data, monitoring the planet, supporting defense systems, and extending digital networks far beyond traditional ground-based limits.

This evolution helps explain why space is drawing growing attention from both commercial customers and governments. Space has become a strategic asset, and reliability has become the defining feature. These systems are expected to work continuously, often in environments where failure carries significant consequences.
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Key Takeaway
The space economy isn’t about rockets—it’s about reliability.
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And that is where companies such as L3Harris Technologies (LHX), Northrop Grumman (NOC), and General Dynamics (GD) come into the picture. These firms aren’t just building planes and ships; they are deeply involved in satellites, secure communications, missile-warning systems, and the digital backbone that keeps both civilian and national systems functioning.

How Our Portfolio Already Touches Space

Our exposure to the space economy is not limited to any one company or theme. In addition to defense firms such as LHX, NOC, and GD, several companies we own for clients play supporting roles behind the scenes. Communications providers such as AT&T (T) and Verizon Communications (VZ) help integrate satellite connectivity into everyday networks, while industrial companies like Cummins (CMI) and Emerson Electric (EMR) supply the power systems, controls, and automation that keep mission-critical infrastructure running.

Taken together, these holdings reflect an important reality: space today is less about exploration and more about dependable infrastructure underpinning everyday activity.

When we talk about investing in space, we’re not talking about speculation on distant planets. We’re talking about investing in the systems that modern life increasingly depends on, often most visible only when they fail, or when, unexpectedly, they work perfectly hundreds of miles from shore.

Uber: When Labels Start to Break

Not too long ago, while reviewing sector weightings within the S&P 500, I noticed something that caught my attention. Uber Technologies (UBER) was one of the largest holdings within the industrial sector, alongside traditional names such as Caterpillar (CAT), Union Pacific (UNP), and Boeing (BA).

At first glance, that feels counterintuitive. Many of us consider Uber to be a ride-sharing company or perhaps a technology company. Both descriptions are accurate, but they don’t fully capture what the business has become.

Uber isn’t simply matching riders with drivers. It is coordinating logistics, routing, pricing, and real-time demand across massive networks. In that sense, Uber increasingly behaves less like a consumer app and more like a transportation and logistics platform. The classification wasn’t about what Uber looks like on a smartphone screen. It was about the role it plays in the economy.

That realization stuck with me because it reflects a broader shift underway. Traditional sector labels are becoming less reliable as guideposts. Businesses are no longer defined solely by what they sell but by the systems they operate and the problems they solve. Software, data, and connectivity are reorganizing parts of the economy that were once firmly physical and industrial.

Uber’s partnership with Kroger (KR), which we own for clients, is a good example. Years ago, the idea of a ride-sharing platform working closely with a grocery chain might have seemed like an odd pairing. Today, it makes more sense. The relationship is less about transportation and more about logistics, fulfillment, and last-mile delivery, areas where coordination and infrastructure matter more than labels.

We do not own Uber for clients, and this observation is not a recommendation. Rather, it serves as a signal. When businesses begin to blur traditional boundaries, whether industrial, technological, or consumer, it often reflects deeper changes in how the economy functions. Paying attention to those signals can be just as important as studying financial statements or valuation metrics.

The common thread in these examples is not the companies themselves but the way change tends to reveal itself. Often it shows up first through small, practical signals—how people move, communicate, manage power, or address long-standing problems—well before those shifts are fully reflected in economic data.

Vertiv and Sterling: Following the Infrastructure Trail

In the summer of 2024, a longtime client mentioned a company to me that wasn’t fully on my radar: Vertiv Holdings (VRT). Jerry is a no-nonsense individual, an accountant by training, someone who has ridden Harley-Davidsons for years, and pilots airplanes. He has never struck me as speculative or prone to chasing trends. In fact, this was one of the first times I can remember him introducing a company to me rather than the other way around.

That prompted a closer look.

At the time, I was familiar with Vertiv only in a general sense and had not formed a clear investment thesis. As I looked more closely, one detail stood out. Vertiv was formerly part of Emerson Electric, a company we have owned for clients for many years. Within Emerson, the business operated as Emerson Network Power, supplying power management and cooling systems for mission-critical environments. To me, lineage mattered. Emerson has been around since the 1800s, and its culture has long emphasized engineering, reliability, and industrial discipline.

The timing of this discovery was important. As interest in artificial intelligence accelerated, it became increasingly clear that AI was not just a software story. It was and still is a power and infrastructure story. Data centers require enormous amounts of electricity, cooling, and redundancy. Chips and algorithms cannot function without stable systems underneath them.

That line of thinking led from power to physical infrastructure and eventually to Sterling Infrastructure (STRL), which we also own for clients. Sterling specializes in the groundwork required before digital infrastructure can operate, including site development, civil engineering, and transportation projects that support large-scale industrial and data-center construction.

During my analysis of Sterling, one development in particular stood out. Sterling acquired CEC Facilities Group, a specialty electrical and mechanical contractor based in Texas. CEC designs, installs, and maintains electrical infrastructure for mission-critical facilities, including semiconductor plants, data centers, and advanced manufacturing sites. The acquisition expanded Sterling’s capabilities beyond earthmoving and site preparation into the electrical systems that ultimately bring these facilities to life.

For us, Vertiv and Sterling represent a way to participate in the growth of AI and data centers without focusing solely on chips or software. They sit lower in the stack, closer to the physical systems that must function reliably for everything above them to work. These are not headline companies, but they operate in areas where failure is not an option and where demand tends to persist once infrastructure is in place.

Eli Lilly: When the Mechanism Changes

Healthcare often evolves gradually until one shift changes the direction of an entire field. Over the past several years, one such shift has taken place around metabolic disease and weight management.

America’s struggle with weight is not new. For decades, we have cycled through workout programs and food trends, from Jane Fonda aerobics to The Atkins Diet and countless variations in between. While many of these approaches worked for individuals, they shared a common assumption: that sustained weight loss depended primarily on long-term human discipline. And while discipline matters, biology, habit, and metabolism consistently proved stronger than good intentions. Despite decades of effort, the United States entered the 2020s more overweight and more diabetic than ever.

What appears to be changing is not motivation but mechanism. New GLP-1-based therapies shift the burden away from willpower and toward biology, directly targeting appetite signaling and metabolic regulation. When outcomes rely less on daily compliance and more on physiological response, adoption and durability can look very different from prior weight-loss cycles.

In August 2025, we initiated a position in Eli Lilly and Company (LLY) and exited our position in Medtronic (MDT). This was not a judgment on the value of medical devices nor a claim that weight-loss drugs represent a permanent solution to obesity. Rather, it reflected our view that momentum in healthcare had shifted toward the treatment of metabolic diseases, and that Lilly had been an early and effective leader in that area.

This is not a certainty or a cure-all. Long-term adherence, side effects, insurance coverage, regulatory scrutiny, and competition will shape outcomes, and adoption may evolve unevenly over time. As with other themes in this letter, the decision was not about chasing headlines but about recognizing when a long-standing problem begins to be addressed in a meaningfully different way and adjusting the portfolio accordingly.

Meta: Scale, Resilience, and Invisible Infrastructure

Several years ago, I heard a statistic on a podcast that made me pull over the car so I could rewind it and write it down. The number was simple but startling: roughly 3.5 billion people use a Meta Platforms (META) application each month.

Put differently, a large portion of the world’s Internet-connected population interacts with Facebook, Instagram, WhatsApp, or Messenger on a regular basis. You don’t need much more context than that to appreciate the scale.

That scale became more tangible for us during Hurricane Ian here in Naples. In the aftermath of the storm, traditional text messaging was unreliable. Cellular networks were strained, and communication was inconsistent. What did work, however, was Meta’s WhatsApp. Messages went through when standard texts did not. One reason is that WhatsApp is designed to operate efficiently on limited data, which can make it more resilient when networks are degraded. In moments like that, the distinction between a social app and critical communications infrastructure blurs.

This is part of what makes Meta interesting to study. While the company is still primarily an advertising business in terms of revenue, much of what it’s building increasingly resembles infrastructure. Meta is involved in undersea fiber-optic cables that help move data across continents, and it continues to invest in data centers, artificial intelligence, and large-scale computing systems. These are not consumer-facing features, but they are essential to keeping global networks functioning.

Power has become a limiting factor in that buildout. To support its next generation of data centers, Meta has entered into nuclear-energy agreements with companies including Oklo, Vistra, and TerraPower. These arrangements are intended to provide large amounts of reliable, clean electricity over the coming decade. The takeaway is not the specific technology but the signal it sends. Computing at this scale requires long-term, dependable energy sources, not just incremental efficiency gains.

We own Meta for clients, but not because it is a social media company. We view it as a business operating at the intersection of communications, data, and infrastructure—areas where reliability and scale increasingly matter. As with other examples in this letter, these systems tend to fade into the background, becoming most visible only when conditions are stressed.

Reliability in a Changing Economy

Over the past several months, I’ve described familiar businesses and technologies in slightly different ways: Apple as a modern-day consumer staple, Google Search as a modern utility, artificial intelligence as the next iteration of the Internet, and Uber as part of the industrial economy. More recently, we’ve discussed how power and energy infrastructure have become critical bottlenecks behind data centers and AI systems. These descriptions aren’t meant to suggest that the rules of investing have changed but rather that the economy itself continues to evolve.

It’s understandable to feel uneasy whenever phrases like “new economy” enter the conversation. Many investors remember hearing similar language during the late 1990s, when technology enthusiasm ran ahead of earnings, cash flow, and reality. We’re mindful of that history. Our approach today is not to chase novelty but to participate by investing in companies we believe share many of the same characteristics we’ve always favored: scale, strong balance sheets, durable business models, and, in many cases, consistent dividend payments.

What has changed is not the discipline but the backdrop. Technology is increasingly embedded in how the global economy functions, how people communicate, how goods move, how power is generated and consumed, and how systems remain reliable during stress. By focusing on companies that are, in our opinion, integral to those systems rather than on speculative ideas built on hope alone, we believe it is both prudent and necessary to participate in these long-term trends.

As always, we’re here to help you navigate what’s next. If your financial situation has changed—or if you have questions about your investment portfolio—please don’t hesitate to call us at (800) 843-7273.

Warm Regards,

Matthew A. Young
President and Chief Executive Officer

January 2026 Client Letter

A look at the forces shaping markets beneath the headlines.

January has a way of pulling our attention forward. Investors start asking what the year ahead might bring and whether the decisions they carried into the new year still make sense. After a year filled with fast-moving headlines and changing narratives, that reaction is understandable.

What can be easier to miss is where progress comes from. In investing, the most important work rarely happens at moments of clarity. It tends to occur during periods that feel uneven or unresolved, when progress is being made before results are obvious.

I was reminded of that recently in a personal way. Two years ago, I routinely finished Peloton rides near the top of my age group. A couple of minor injuries last year forced me to step back and rebuild. Improvement did not come from pushing harder. It came from consistency, recovery, patience, and showing up day after day, even when the gains were hard to see.

Investing often works the same way. Periods that feel least productive on the surface are often the ones laying the groundwork for future success.

This perspective shapes how I think about a new year. Rather than focusing on predictions or short-term market calls, I find it useful to think about positioning and the forces shaping outcomes before they become widely recognized.

What follows is not a forecast for 2026; it is a framework for thinking about risk, opportunity, and portfolio construction within a much longer game.

Why We Think Long-Term—Even When the Calendar Says Otherwise

Before talking about 2026 specifically, it helps to explain how I think about investing more broadly. I do not spend much time fixated on one-year outcomes. My approach has always been continuous and long term, not neatly segmented into calendar boxes. Businesses do not operate on twelve-month scorecards, and successful long-term investing rarely does either.

Markets, however, are often judged on a much shorter horizon. Investors often measure success or failure over quarters and calendar years. One of the largest assets most of us own is our home. If the real estate market weakens and the estimated value declines, does that alone prompt a sale? Of course not. Most homeowners do not even check the value regularly, and when they do, short-term fluctuations are largely irrelevant unless a move is imminent.

A portfolio of stocks deserves the same perspective. A declining stock price does not automatically signal a problem. There are times when fundamentals change and selling makes sense. More often, price declines reflect shifts in sentiment rather than deterioration in business value. In those moments, lower prices can represent opportunity rather than failure.

Warren Buffett has long described stocks as ownership stakes in real businesses, not trading vehicles judged by daily price movements. Seen through that lens, short-term volatility matters far less than long-term earning power, balance-sheet strength, and competitive position.

I also recognize the reality investors live with. Markets are visible every day, and performance is easy to track in real time. Even so, January has become a moment when people naturally step back and ask what comes next. With that context in mind, it’s worth thinking about how the past year unfolded and what may feel different as we move ahead.

A Year Where Headlines May Carry Less Weight

March and April of last year delivered a dense stretch of headline pressure. Questions around tariffs, currency movements, and speculation about Federal Reserve independence arrived almost at the same time. It was not just the issues themselves that mattered but how tightly they were clustered.

What made that period challenging was not only what investors were reacting to but also how little time there was to digest one development before the next arrived. Markets often struggle most when several unknowns overlap.

The headline environment in 2026 may feel different. The early phase of a new administration brought a fast pace of policy announcements and frequent recalibration. That pace appears to have begun to slow. Headlines will not disappear, but fewer major unknowns may be competing for attention all at once.

Not all headlines carry the same weight. Some events are dramatic without being destabilizing. Others introduce uncertainty that lingers. Markets tend to care less about the volume of news and more about whether outcomes can be reasonably assessed.

History suggests that when uncertainty shifts from unknown to understood, markets adapt. Even significant developments become more manageable once they are absorbed and priced. In those moments, headlines lose their power not because they matter less but because their implications are clearer.

This does not suggest a calm year or an absence of surprises. It simply reflects how markets typically work. Not every headline deserves the same attention, and some developments, despite their significance, ultimately ease pressure rather than add to it.

Venezuela, Energy, and a Different Kind of Headline

One recent development involving Venezuela is a good reminder that not all headlines have the same implications for markets.

For years investors have heard that the United States is energy independent. There is truth to that, but it doesn’t tell the whole story. The U.S. produces large amounts of light, sweet crude oil. Many of the nation’s largest refineries, particularly along the Gulf Coast, were built decades ago to process a different product entirely: heavier, sour crude.

Venezuela is one of the most efficient sources of that type of crude. When access was restricted, U.S. refiners had to adjust. Heavier crude was sourced from farther away, often at higher cost and with less efficiency. The result was not an oil shortage but a system that operated with more friction.

Recent U.S. action in Venezuela has the potential to change that dynamic. If it leads to renewed access and investment, it could improve supply reliability, support refinery margins, and allow the refining system to operate more smoothly. In practical terms, that matters for energy companies, fuel costs, and inflation.

This is where the distinction between dramatic and destabilizing becomes relevant. Events that improve access, logistics, or efficiency can be constructive even when they dominate headlines. Lower energy input costs may ease pressure on consumer prices. That, in turn, can give the Federal Reserve more flexibility as it evaluates future policy decisions.

From a portfolio perspective, this is not about politics or short-term speculation. It is about understanding how energy markets function, how infrastructure constraints affect profitability, and how changes in supply chains ripple through the broader economy.
Not every geopolitical event increases uncertainty. Some, once understood, reduce it.

A Reasonably Supportive Environment for Stocks

Rather than trying to forecast where markets might land, I find it more useful to focus on the conditions businesses are operating in and how those conditions are evolving.

Economic growth has slowed from its post-pandemic pace, but it has not stalled. Employment is easing without showing clear signs of stress, and companies continue to invest even with a higher cost of capital. Inflation pressures have moderated, which should provide policymakers more flexibility than they had a year ago.

That flexibility matters. If interest rates continue to move lower, financial conditions gradually become less restrictive. Balance sheets improve. Refinancing becomes easier. Cash flow stabilizes. None of this guarantees strong market returns, but it does tend to create a more workable environment for businesses over time.

There is also more discussion around margin expansion. After several years of rising costs, some of the biggest headwinds are starting to settle. Wage growth has moderated. Supply chains are more predictable. Input costs, while still elevated in certain areas, are better understood. Businesses do not need perfect conditions. They need clarity.

At the same time, many companies spent the past few years investing heavily in productivity. Automation, software, and infrastructure upgrades were not optional. They were necessary to stay competitive. The return on those investments rarely shows up immediately in reported earnings, but over time, they can improve efficiency and support margins.

Taken together, steady growth, easing inflation pressures, improving visibility, and years of productivity investment do not eliminate risk. Markets rarely move in straight lines. But when these building blocks behave, equities have often had room to work over time.

A Quiet Support: The 65‑Year‑Old Consumer

Much of the conversation around the U.S. consumer today centers on strain. Housing costs are elevated. Insurance premiums have risen. Everyday expenses feel more noticeable. These pressures are real, but they do not describe every part of the economy equally.

One of the quieter sources of support comes from demographics. More Americans are turning 65 than at any point in the country’s history, and that trend is expected to continue for several more years. Many in this group are entering retirement with meaningful savings, home equity, and steady sources of income, including pensions and Social Security.

Spending patterns tend to change at this stage of life, but they do not disappear. Travel, leisure, healthcare services, and experiences often move higher on the priority list. Just as important, spending does not stop at the individual level. Financially secure retirees often help support adult children and grandchildren, whether through childcare, education expenses, or assistance with housing.

The result is a consumer landscape that is more nuanced than broad averages suggest. While some households remain under pressure, others continue to draw on savings accumulated over decades. Demand does not vanish. It shifts.

This does not eliminate the risk of a slowdown, nor does it suggest that all consumers are thriving. It helps explain why economic resilience has persisted even as concern about the consumer remains widespread.

The Fourth Industrial Revolution, Hiding in Plain Sight

When most people think of an industrial revolution, they picture railroads, factories, pipelines, and power plants. Steel, energy, and heavy machinery come to mind. These were visible transformations, easy to recognize even as they were taking shape.

The current one looks different.

Much of today’s industrial change is happening behind fences, inside data centers, and within existing infrastructure. It is being driven by artificial intelligence, robotics, and compute-intensive systems that require enormous amounts of power, cooling, and physical support.
Because the outputs are digital, it is easy to underestimate the scale of what is being built.

That is where this revolution hides.

Before a single AI model runs, land must be prepared, equipment moved, and power secured. This is not a virtual process. It is a construction and infrastructure effort unfolding in real time.

Companies like Caterpillar supply the equipment needed to prepare sites and build large-scale facilities. Emerson Electric provides automation and control systems that manage complex industrial and energy environments where precision matters more than speed. Cummins sits at the intersection of legacy and transition, supplying power solutions while adapting to cleaner and more flexible energy systems.

Even regulated utilities, often viewed as slow moving, have become central participants. Companies such as Duke Energy, NextEra Energy, and Southern Company are increasingly essential partners in supplying reliable electricity to a more energy-intensive economy.
What makes this phase of investment notable is not just its scale but its durability. These projects are not one-time events. They require ongoing maintenance, upgrades, and expansion. The infrastructure supporting this cycle is being built to last, and demand tends to build on itself over time.

Many of the businesses involved share another characteristic that often receives less attention during periods of rapid technological change. They generate cash flow and return capital to shareholders. Dividends may not dominate the conversation around artificial intelligence or data centers, but over time they can remain a meaningful contributor to total return, particularly when paired with sustained reinvestment and long-term demand.

This is often how major economic shifts unfold: not all at once, and oftentimes not in the places people expect to look.

Beyond the Acronyms: A Market of Stocks, Not Seven Names

One of the more interesting market developments last year was not what dominated the headlines but what contradicted them.

Much of the recent investing narrative has centered on the idea that a small group of mega cap technology companies is the stock market. Acronyms simplify complex realities, and over time, that simplification can harden into assumption. The assumption, in this case, is that if those few names are driving returns, everything else must be standing still.

That was not what actually happened.

Five of the seven companies most often cited as market leaders underperformed the broader market last year. I do not view that as a warning sign or a loss of leadership. Stocks move in cycles. Even exceptional businesses pause, consolidate, or simply hand the baton to others for a time.

What mattered more was what that pause revealed.

It showed that markets still reward execution beyond the most crowded trades. Performance broadened across industries and business models, often in places receiving far less attention. The stock market, as it turns out, remained a market of stocks.

That distinction matters. When investors become overly focused on a narrow set of names or narratives, decision-making can become distorted and opportunity easier to miss. Over time, durable returns tend to come not from guessing which acronym will dominate next but from owning a diversified collection of businesses with different drivers, cycles, and sources of revenue.

That dynamic may become more visible in the year ahead. Markets rarely move forward on a single track. Leadership rotates. Capital flows adjust. New contributors emerge. When that happens, diversification stops feeling theoretical and starts feeling practical.

Why These Themes Matter—and Why Time Still Matters More

Taken individually, none of these themes is revolutionary. Headlines ebb and flow. Economic conditions shift. Demographics evolve. Infrastructure gets built. Leadership rotates. These are familiar features of markets over time.

What matters is how they come together.

Periods when economic growth remains intact, cost pressures ease, productivity improves, and participation broadens tend to reward discipline more than drama. They are rarely obvious in real time. Progress often appears uneven, and leadership seldom moves in a straight line.

The temptation, especially after an eventful year, is to focus on what might happen next. In our experience, the more durable advantage comes from being positioned thoughtfully before outcomes become clear.

That perspective shapes how we approach portfolio construction. Rather than trying to predict short-term moves or react to every new narrative, we focus on owning a diversified collection of durable businesses. Companies with real cash flow. Balance sheets that can absorb change. Competitive positions that allow them to adapt as conditions evolve.

Time remains an underappreciated part of that equation. It allows productivity investments to compound. It allows margins to normalize. It allows businesses with durable cash flows to raise dividends year after year, contributing to total return in ways that are easy to overlook in any single calendar year. It also allows cycles to play out and leadership to rotate without forcing constant decisions.

None of this eliminates uncertainty. Markets will always test patience. Headlines will continue to demand attention, and periods of volatility are inevitable. Over time, however, investors who stay focused on fundamentals, diversification, and a long-term horizon tend to be better positioned to participate in progress without reacting to every headline along the way.

That is the mindset we bring into 2026. Not as a forecast but as a framework. One that recognizes change without chasing it and opportunity without overstating it.

As always, we’re here to help you navigate what’s next. If your financial situation has changed—or if you have questions about your investment portfolio—please don’t hesitate to call us at (800) 843-7273.

Warm Regards, 

Matthew A. Young
President and Chief Executive Officer

December 2025 Client Letter

Recently, as I sat in my office, it occurred to me this was the first time in roughly two decades when I didn’t make it back to Rhode Island during the summer—and the first in which I didn’t take a single flight. A few factors contributed, but the primary reason was the unusually large number of meaningful market and policy developments throughout the year. Coupled with April’s stock market volatility, it was a demanding period, and whenever I considered stepping away, something important seemed to be unfolding.

2025 was memorable. It wasn’t calm or predictable, but it was certainly active. We spent much of the year navigating confusion around tariffs, which for many investors became a major disruptor. The range of predictions surrounding their economic impact was wide, and April alone brought headlines warning of everything from earnings slowdowns to potential recession. At the same time, there were open questions about the tax bill, ongoing speculation about when the Federal Reserve might cut interest rates, and concerns about whether corporate profitability could hold up through all the noise.

Yet despite the early uncertainty, markets moved higher, AI optimism accelerated, and many companies continued to execute well. If anything, the year reinforced two familiar takeaways. Headlines don’t always unfold into the dramatic outcomes they seem to foreshadow in real time. And market declines are part of the normal rhythm of investing.

Understanding Market Volatility

For investors, it’s helpful to remember that market declines are not an exception. To put this in context, let’s look at how often the S&P 500 typically experiences drawdowns of various sizes.

The market’s path upward has never been a straight line. Even in strong years like 2025, the S&P 500 experienced plenty of pullbacks. The index reached new highs 36 times this year but also logged 27 trading days with declines of -1% or worse. These figures are broadly consistent with long-term averages.

Since 1928, the S&P 500 has averaged about 29 days per year with losses greater than -1, and roughly 45% of all trading days over that period have been down days.

Single-day drops are common, and from time to time those daily declines accumulate into larger moves. Since 1928, investors have lived through roughly 35 market corrections (declines of 10% or more) and 22 bear markets (declines of 20% or more), including several in just the past two decades. Yet through all those episodes, long-term market progress continued.

History shows that volatility is not unusual. It is the cost of long-term returns.

Warren Buffett has a way of simplifying complex market behavior better than almost anyone. When asked whether investors should worry about corrections, he offered a perspective that still applies today:

“If you worry about corrections, you shouldn’t own stocks… The point is to buy something that you like at a price you like and then hold it for 20 years.”

Buffett’s broader message is clear. Meaningful investing requires a tolerance for temporary discomfort.

When Clients Ask About an “AI Bubble”

Several clients have expressed concerns about a potential “AI bubble.” It’s a fair question, given the speed at which AI-related companies have grown and the amount of capital flowing into the theme.

It’s important to emphasize that being thoughtful about portfolio concentration does not mean avoiding what I believe are exceptional businesses. Many leading AI companies generate meaningful earnings and serve expanding end-markets. They continue to drive a major technological transformation. Such strength does not eliminate volatility, but it does help differentiate today from earlier periods when enthusiasm ran ahead of business fundamentals.

At the same time, prudent portfolio construction often means not relying too heavily on any single sector, no matter how promising it appears. We look to balance our technology and AI exposure with areas that tend to behave differently when growth stocks face turbulence. Examples include:

• consumer staples such as Costco, Kroger, Coca-Cola, and Walmart
• healthcare companies like Eli Lilly, Johnson & Johnson, and AbbVie
• utilities including Southern Company, Duke Energy, and NextEra

These companies generate cash flows influenced by different economic drivers than major AI-related firms and have historically helped moderate portfolio volatility when higher-valuation sectors come under pressure.

The goal is not to abandon AI exposure. Rather, it is to ensure that no single trend, regardless of its potential, dominates portfolio outcomes. Balanced diversification should allow investors to participate in innovation while maintaining stability across a range of market environments.

Investing in 2026: Key Themes

1. Earnings Still Drive Markets

As we look ahead to 2026, it’s worth reinforcing a simple and important principle. Over time, earnings, not headlines, drive stock prices. Even with the attention surrounding tariffs, inflation, interest-rate debates, and shifting political narratives, corporate profitability remains the foundation of long-term market value.

Companies with durable cash flows, pricing power, recurring revenue, and strong balance sheets continue to anchor our investment approach. In 2025, despite the shifting headlines, earnings broadly held up. And that mattered more than any single news item. We expect the same dynamic next year. Fundamentally strong businesses should continue to lead.

2. AI is Also an Industrial Story

When most people hear the term physical AI, they think of autonomous systems such as robots, drones, and self-driving vehicles that operate by sensing, reasoning, and acting in the physical world. This branch of AI is already reshaping logistics, manufacturing, transportation, and service industries.

But there is a second dimension that is now receiving significant attention: the infrastructure required to make all of this possible. Behind every autonomous robot or vehicle is a tremendous amount of computing power and data flow—and that energy must come from somewhere.

Developing and deploying AI at scale requires an extensive buildout of real-world infrastructure, including:

• power generation and transmission
• data center capacity with cooling systems
• specialized industrial equipment and construction services

Demand for this infrastructure continues to grow as AI models become more computationally intensive. Each new generation of models requires more processing power, and physical AI systems including robots, drones, and autonomous vehicles layer additional demand on top.

In that sense, AI is both a digital and industrial revolution. The software advances quickly, but it depends on a foundation of engineering and construction. Companies tied to data-center development, chip production, and industrial services may benefit for years as AI adoption accelerates.

AI is not only a software breakthrough; it is a hardware and infrastructure story as well. That remains an important part of our investment focus heading into 2026 and beyond. The long-term winners may not only be the companies creating AI models but also the businesses building the physical world required to run them.

3. The Energy System Becomes the New Bottleneck

As AI adoption accelerates and the economy becomes more electrified, the U.S. energy system is facing pressures that were not widely appreciated even a few years ago. AI growth, manufacturing reshoring, electric transportation, and continued economic expansion are bringing a major issue into focus. The country faces real constraints in power generation, transmission capacity, and grid infrastructure.

Forecasts across the utility industry point to a meaningful rise in electricity demand, driven by developments such as:

• AI data centers
• industrial activity returning to the U.S.
• electric vehicles and charging networks
• semiconductor fabrication and other energy-intensive facilities

These needs are often concentrated in regions where grid capacity is already limited, increasing the urgency for additional infrastructure. Utilities, natural-gas producers, grid engineers, and renewable-power developers all stand to play a role in addressing these constraints. Companies able to expand capacity, enhance reliability, or deliver power more efficiently may see long-term tailwinds.

This theme is not about predicting shortages or crises. It reflects a structural reality. The grid must expand and modernize to support a more digital and electrified economy. As this buildout continues, the businesses enabling it may benefit in the years ahead. In many ways, the energy system is becoming the new bottleneck and an emerging investment opportunity.

Balance Remains a Reliable Guide for Investors

Across all of these themes, one message remains constant: diversification is one of the most practical ways to manage volatility and risk while still participating in long-term growth. The themes discussed above share an important point. Markets evolve, leadership shifts, and no single trend works in every environment.

AI will continue to be an important part of the market, but it should not be the only part of a portfolio. Our approach includes diversification not only across equity sectors but also across:

• cash via money-market funds
• corporate bonds, Treasuries, and other fixed-income
• precious metals through gold and silver ETFs
• defensive, dividend-oriented companies
• growth leaders benefiting from long-term innovation

The goal is not to avoid volatility. It is to manage it thoughtfully. By combining innovative areas such as AI with durable, income-producing, and defensive assets, we aim to support a steadier and more balanced investment experience over time.

As always, we’re here to help you navigate what’s next. If your financial situation has changed—or if you have questions about your investment portfolio—please don’t hesitate to call us at (800) 843-7273.

Enjoy your holidays and Happy New Year!

Matthew A. Young
President and Chief Executive Officer

October 2025 Client Letter

Last month, I wrote about Apple as a modern-day consumer staple, a company whose products have become integral to everyday life. The iPhone helps us communicate, navigate, research, shop, and stay connected in ways that are second nature.

If Apple is a modern consumer staple, then Alphabet, the parent company of Google, could be viewed as a modern utility. A utility typically provides an essential public service; operates at scale; and faces little viable competition because of its infrastructure, data, or network effects. By these measures, Google meets many of the same criteria.

Google Search has become the front door to the Internet for billions of people—an essential digital service much like electricity or water in the physical world. It is so deeply woven into daily routines—search, email, maps, documents, and video—that many of us could not function productively online without it. With an estimated 80–90 percent share of global search, Google has become not just a household name but also a pillar of the world’s information infrastructure.

Beyond Search, YouTube and YouTube TV have become part of everyday routines for millions of households. And this time of year, for us football fans, YouTube TV’s NFL Sunday Ticket is as close as it gets to a weekend fixture.

Google’s reach extends beyond screens. Through Waymo, its autonomous ride division, the company is operating services in Phoenix, San Francisco, Los Angeles, and Austin—reportedly completing around 250,000 paid rides per week in spring 2025. In March, Waymo logged over 700,000 monthly trips, more than 50 times its 2023 volume. The service has recently expanded to Atlanta (via Uber) and plans to launch in Miami and Washington, D.C., by 2026. Autonomous mobility adoption is accelerating, and Google is among the central participants.

Inside Google’s research labs lies an important frontier: the Willow quantum-chip project. Though still in its early stages, Willow represents Google’s effort to move beyond the limits of classical computing. Traditional computers operate on bits, ones, and zeros that must test possibilities one at a time, often brute-forcing through countless paths to reach an answer. Quantum computers, by contrast, use qubits that can exist in multiple states simultaneously, a phenomenon known as superposition. This allows them to explore many paths at once rather than sequentially.

If quantum computing becomes commercially viable, the shift could break through the boundaries of Moore’s Law. Tasks like predictive analytics, pharmaceutical research, and complex simulations could be performed not just faster but in entirely new ways. That is why Google is investing in this field, not merely to stay ahead in AI but to help shape the next computing paradigm.

While Google holds structural advantages, potential challenges exist. Governments continue to evaluate large tech platforms for competition and data practices, and emerging AI models could eventually introduce new forms of search or user interaction. However, most competitors currently lack the scale of data, infrastructure, and capital that underpin Google’s existing advantage. For now, its information backlog and technological depth are competitive strengths.

Financially, Google has been a profitable company. In its most recent quarter, Alphabet reported approximately $95 billion in cash and marketable securities and total debt of about $14 billion. Over the past 12 months, the company generated roughly $73 billion in free cash flow—often described as “owner’s cash,” since it represents what remains after funding operations and capital investments. Free cash flow can be used to pay dividends, repurchase shares, or reinvest in the business. In 2024, Alphabet reported net income of approximately $100 billion, placing it among the highest earners in U.S. public companies. The company also initiated a modest dividend in June 2024, something investors may overlook because of its long-standing tech label.

Some analysts and investors—the late Charlie Munger among them—have described Google as one of the most durable and wide-moat businesses ever built. Munger stated, “I’ve probably never seen such a wide moat,” when referring to Google’s competitive advantage. Whether or not one agrees, few dispute the scale of its global reach, the resilience of its recurring revenue, and the strength of its balance sheet.

Ultimately, Google’s expansive digital footprint depends on physical infrastructure including power, construction, energy systems, and the industrial networks that support them. The companies behind that infrastructure help form the foundation on which the digital world is built.

The Backbone of AI: Building the Physical Foundations

In the California Gold Rush era, not every prospector struck gold. Yet those who supplied the tools—Levi Strauss with durable work pants, Samuel Brannan with picks and pans—often built steadier fortunes. In investing terms, these were the original “picks and shovels” plays: the companies that prospered by enabling others to chase opportunity.

Today’s artificial-intelligence boom has its own version. Over the past year, we’ve discussed companies such as NVIDIA, Microsoft, and Broadcom—the first-order picks and shovels of the digital age. They design the chips, run the data centers, and provide the cloud platforms that make AI possible.

But major innovation waves often depend on a quieter group: those that build the physical foundation beneath the technology. These are the second-order picks and shovels. The companies that enable the enablers. They generate the power, build the infrastructure, and manage the systems that keep the digital economy running. In many ways, these industrial leaders form the physical backbone that supports the AI-driven world.

Several of our industrial holdings illustrate this theme:

Caterpillar (CAT): Caterpillar supplies the heavy machinery and backup-generation systems that prepare and power massive data-center projects. Its equipment shapes the ground on which digital infrastructure stands. Caterpillar’s dividend legacy, which includes three decades of annual dividend growth, has helped make this a reliable industrial company.

Cummins (CMI): Known for its engines and generators, Cummins is also building its future around cleaner power—hydrogen, battery systems, and integrated microgrid solutions. The company’s nearly 20-year history of annual dividend increases underscores a culture of consistency even as it adapts to energy transition trends.

Emerson Electric (EMR): Emerson offers advanced automation, process control, and power-management technologies used across data centers, utilities, and manufacturing. Its history of dividend growth reflects both financial discipline and steady cash generation. Emerson’s combination of engineering depth and shareholder reliability have made it a reliable industrial holding.

Sterling Infrastructure (STRL): Sterling specializes in site development, civil engineering, and transportation projects that support industrial growth and data-center expansion—essential groundwork before the first chip is installed. While Sterling does not currently pay a dividend, its existing work backlog and focus on high-return projects continue to drive long-term growth potential.

With its recent $505-million agreement to acquire CEC Facilities Group, Sterling is now adding electrical and mechanical services to its capabilities. CEC’s expertise in designing and maintaining power systems for semiconductors, data centers, and advanced manufacturing should complement Sterling’s civil infrastructure platform. The deal is anticipated to strengthen Sterling’s presence across the full project lifecycle, accelerate delivery timelines, and enhance cross-selling opportunities.   

Vertiv (VRT): Vertiv provides power and cooling systems that keep hyperscale data centers operating around the clock. As AI workloads surge, Vertiv’s precision-cooling and backup-power technologies have become essential to maintaining uptime. While its dividend yield is modest, the company’s reinvestment strategy supports growth in the expanding data-center market. 

Williams Companies (WMB): Williams operates one of the largest natural-gas pipeline networks in North America, supplying the cleaner energy that powers both industry and data centers. Its infrastructure supports consistent cash flow and an attractive dividend yield, positioning it as both a traditional income holding and an enabler of the AI-era energy build-out. 

While these companies don’t design semiconductors or run AI models, they build and maintain the systems that help make those innovations possible. Collectively, they offer a blend of dividend income and participation in the digital era.

Microgrids: The Emerging Industrial Layer

An emerging concept in industrial energy, the microgrid is a localized, self-contained system that can operate independently from the main grid. Microgrids integrate multiple energy sources, including solar, battery storage, and traditional generators, to provide reliable, efficient power for campuses, hospitals, military bases, and, increasingly, data centers.

While many data centers aim to incorporate renewable energy, the current reality is that wind and solar can meet only a fraction of their enormous power needs. Modern hyperscale data centers consume between 50 and 100 megawatts of electricity, roughly the same amount used by 80,000 U.S. homes. That level of demand makes full reliance on renewables impractical. For example, generating just 10 megawatts from solar would require about 25,000 panels spread across 40 to 50 acres—nearly 35 football fields—and only produces power when the sun is shining. Wind faces similar challenges, operating intermittently and requiring dozens of large turbines to deliver continuous output. 

For this reason, most data centers are turning to hybrid microgrids that blend renewables with natural-gas or diesel generation, battery storage, and traditional grid connections. These systems provide the flexibility and reliability needed for 24/7 operation while still incorporating cleaner energy where possible. 

As AI adoption accelerates, uptime and energy continuity have become critical. Microgrids offer resilience against outages, grid congestion, and volatile energy costs—an increasingly important advantage as demand for computing power expands.

Several of our holdings play direct or supporting roles in this evolving space. Cummins and Caterpillar produce advanced generators and energy-storage systems tailored for microgrid environments. Emerson Electric supplies the automation and controls that synchronize distributed power sources. Vertiv designs the power-distribution and backup systems that make microgrids viable for high-density data centers. Williams Companies provides the natural-gas infrastructure that fuels the generation side of these systems.

Microgrids represent an important step in the modernization of industrial America. They combine technology, energy efficiency, and reliability. While not yet mainstream, they are gaining momentum in sectors where power stability and cost management are essential. For long-term investors, the companies developing these systems are helping power the next phase of digital growth, one built on resilient, intelligent energy.

Perspective and Patience: Navigating the AI Spending Boom

Amazon founder Jeff Bezos recently described the current wave of AI investment as a “bubble that will pay off.” As summarized by Bloomberg, Bezos noted that, while capital is flowing quickly and sometimes ahead of fundamentals, the resulting innovation could lay the groundwork for long-term gains.

According to Bloomberg’s report:

• Bezos said the surge in AI spending resembles an “industrial bubble” that may lead to some failed investments but ultimately leave society better off.
• He noted that investors often struggle to distinguish between good and bad ideas in periods of technological excitement, with companies being funded before they have a product.
• He emphasized taking the long view, arguing that once the dust settles, the societal benefits from AI could be enormous. 

Brian Wesbury, chief economist at First Trust Advisors, offered his own perspective in an October 3 post on X: 

I don’t disagree with Bezos at all. The problem is how few people remember 1999. The fiber that Worldcom laid changed everything, but Worldcom went bankrupt. The Palm Pilot was the precursor of the iPhone, but 3Com went bankrupt. Yes, the future is bright, but markets have priced in that brightness awfully early. It’s possible that investors will have patience at these bubble prices to wait for the benefits (profits) of our current push into AI to show up. And, it is possible that the Fed will keep cutting rates and printing money and holding up asset prices with new money. But what that does is juice inflation. And inflation reduces the value of those future profits. Bubbles can persist for a long time, but they are still bubbles.

Wesbury’s message is worth considering. Innovation cycles rarely move in straight lines. Excitement can run ahead of earnings, just as it did during the dot-com era. But the technologies born from these periods—fiber optics then, AI infrastructure now—can still transform industries long after early investors lose enthusiasm. 

For investors, perspective and patience remain important. Markets may overshoot expectations in the short term, but innovation often compounds in the background. There can be opportunity staying invested in durable businesses and the infrastructure positioned to outlast the initial wave of excitement.

Staying Grounded: The Importance of Diversification

As long-term investors, our goal isn’t to time bubbles or chase every trend. It’s to combine innovation exposure with quality, income, and discipline. Many of the companies we own share a common foundation: strong balance sheets, consistent dividends, and tangible assets that can help smooth the path through periods of market volatility.

We believe diversification remains as relevant as ever, both within the equity portfolio and across asset classes. In addition to stocks, we continue to value the role of cash reserves, fixed income, and precious metals as long-term hedges against uncertainty.

The AI era is reshaping industries, but it still depends on physical power, machinery, and engineering. The modern digital gold rush will have winners and casualties, but those supplying the tools—the modern picks and shovels—may deliver progress for years to come.

As always, we’re here to help you navigate what’s next. If your financial situation has changed—or if you have questions about your investment portfolio—please don’t hesitate to call us at (800) 843-7273.

Warm Regards,

Matthew A. Young
President and Chief Executive Officer

September 2025 Client Letter

Last month, I drove my son to Gainesville to begin his junior year at the University of Florida. Moving into the fraternity house began with an introduction to a black box mounted beside the front door. It was a newly installed contactless entry system powered by near field communication (NFC). The brotherhood simply tap their phones near the reader to gain entry.

NFC lets devices talk to each other within a few centimeters. It’s the same technology behind tap-to-pay cards and mobile wallets. The setup offers secure, fast access without physical keys or shareable codes.

Later that night, we grabbed dinner at BJ’s, which uses a QR-based payment system. Scan the code at the table, view the bill, and pay via mobile wallet. No waiting for the server, no paper receipts.

Conveniences like these are nudging me toward a wallet-less lifestyle. I sometimes carry a minimalist wallet, but increasingly prefer my iPhone for secure, hassle-free payments.

While iPhones have been around for years, I’m still struck by all their applications. Navigation, payments, communication, reservations, entertainment, news, research, weather reports, and coupon clipping. All indispensables.

I don’t view Apple as a tech company. I see it as a modern consumer staple. Some push back on that comparison, but I ask: Would you rather go a week without toothpaste or without your iPhone? Personally, I’d manage without toothpaste. A week without my iPhone? That’s a logistical meltdown. For me, the device is command central.

We rely on our phones to connect with countless services, often without a second thought about the infrastructure making it all possible. That invisible layer is one of the main areas where today’s digital revolution is unfolding. And at the center of it all are data centers.

Digital Mines: The Role of Data Centers in the Data Economy

Data is increasingly seen as the raw material of the digital economy. Much like gold was for industrial economies. While gold fueled wealth creation in past centuries, data now powers innovation, automation, and decision-making across nearly every sector.

Often described as “mining the new gold,” data centers are where the value of information is unlocked. These facilities store, process, and transmit the data behind everything we do online. From email and streaming to navigation and shopping. Data centers comprise servers, networking gear, and systems for power and cooling. Think of them as digital factories where data is refined and distributed.

If data is the new gold, then data centers are the mines. From contactless entry systems to mobile payments, we interact with data-rich technologies constantly. Behind every tap, scan, or swipe is an infrastructure built to keep that data secure, accessible, and flowing.

Mapping the Mines: Types of Data Centers and Who Runs Them

There are several types of data centers, each playing a distinct role in the digital ecosystem:

• Hyperscale centers are operated by tech giants like Amazon Web Services, Google Cloud, Microsoft Azure, Meta (with Prometheus coming online in 2026 and Hyperion under development), and Oracle Cloud Infrastructure. These facilities support millions of users and vast computing workloads.
• Enterprise centers are owned by individual companies for internal operations. JPMorgan Chase uses them to support secure financial transactions, Walmart to manage logistics and inventory, and Coca-Cola to oversee global supply chain and marketing data.
• Colocation centers allow businesses to rent space from third-party providers such as Equinix and Digital Realty, offering flexibility without the need to build and maintain their own infrastructure.
• Edge centers are located closer to end users to reduce latency and improve response times, which are critical for applications like autonomous vehicles and real-time analytics.
• Cloud-based centers may appear virtual to users but rely on physical infrastructure. This is the model many small businesses use to store and access our files, email, and internal systems.

Artificial intelligence is accelerating demand for data centers. Machine learning models require massive computing power and storage, creating a feedback loop: more data leads to better models, which in turn require more infrastructure. This dynamic has sparked a surge in investment across the data center landscape.

For investors, understanding the role of data centers is increasingly important. These facilities aren’t just technical assets. They’re central to the growth of AI, cloud computing, and digital services. As demand continues to rise, companies that build, power, and support data centers may offer long-term investment opportunities.

Foundational Players in the Data Center Ecosystem

With data centers playing a foundational role in the digital economy, several companies are generally recognized for their strategic contributions to building and supporting the infrastructure behind it:

• Alphabet (Google)
  Alphabet has earmarked $75 billion for AI-ready data centers, scaling aggressively with a focus on energy-efficient infrastructure and custom silicon (TPUs). This investment supports its shift from ad-centric to platform-centric revenue, potentially positioning Alphabet as a leader in cloud and AI infrastructure.

• Amazon (AWS)
  Amazon Web Services operates one of the world’s largest hyperscale data center networks. With over $150 billion invested in infrastructure, AWS is partnering with NVIDIA on liquid cooling for AI workloads, an indicator of its commitment to next-generation efficiency.

• Broadcom
  Often overlooked, Broadcom plays an important role in digital infrastructure. Its networking chips move vast amounts of data quickly and efficiently, enabling large-scale AI systems. As data center traffic grows, Broadcom’s expertise in routing and switching makes it an enabler of modern computer environments. Its technology is embedded in many of the world’s largest cloud and enterprise data centers.

• Dell Technologies
  Dell builds the hardware behind private cloud, edge computing, and AI workloads. It helps enterprise clients modernize without starting from scratch, offering scalable systems and leading in liquid cooling. Liquid cooling technology is increasingly responsible for managing heat in high-performance AI systems. Dell’s latest servers can reduce cooling energy costs by up to 60%, making data centers more efficient. While not a hyperscaler, Dell’s infrastructure is widely used across enterprise environments.

• Meta
  Meta is investing $65 billion in hyperscale and edge data centers to support AI and augmented reality / virtual reality platforms. Its use of immersion cooling reflects the intensity of its computer needs and its long-term bet on spatial computing.

• NVIDIA
  NVIDIA has evolved from a chipmaker into a full-stack systems company helping power the AI revolution. Its GB200 NVL72 platform, built on the Blackwell architecture, delivers rack-scale performance with advanced liquid cooling for trillion-parameter AI models. NVIDIA’s infrastructure strategy now includes reference designs for “AI factories,” integrating computer, cooling, and power systems into unified, simulation-ready environments.

Building the Foundation: Companies Powering Data Center Infrastructure

While companies like Amazon, Alphabet, and NVIDIA lead the computer and platform layers of digital infrastructure, others play important roles in building and enabling the systems that support them:

• Sterling Infrastructure
  Sterling specializes in site development for data centers, including excavation, grading, and utility installation. In March 2024, its subsidiary Plateau Excavation secured a $100 million contract for a data center project in the southeastern U.S., spanning 280 acres and involving 125,000 linear feet of underground infrastructure. This award reflects strong demand from hyperscale clients expanding capacity for AI and cloud workloads.

  Sterling offers exposure to the physical buildout of digital infrastructure, which is a less crowded but necessary corner of the market. Its E-Infrastructure segment accounts for over 65% of its backlog, with data-center-related activity growing 60% year over year in early 2025. Sterling’s ability to deliver complex, mission-critical projects on time appears to have made it a trusted partner for hyperscale developers.

• Vertiv Holdings
  Vertiv provides the power infrastructure essential for AI data centers, where rack-level energy demands now exceed 300 kilowatts. It is pioneering 800 VDC architectures, aligned with NVIDIA’s AI roadmap, to deliver power more efficiently while reducing copper use and thermal losses.

  Vertiv’s portfolio includes DC busways, converters, backup systems, battery storage, and microgrid solutions that help reduce reliance on utilities. It also leads in direct-to-chip and immersion liquid cooling, which is critical for managing heat in high-performance AI environments. Its MegaMod CoolChip modular systems integrate cooling and power, enabling hyperscale deployments up to 50% faster than traditional builds.

  As density and energy needs rise, Vertiv’s end-to-end infrastructure, from grid to chip, positions it as an important component in the evolving architecture of AI infrastructure.

AI Valuations: Hype, Reality, and Risk

In mid-August, OpenAI CEO Sam Altman stirred debate with candid remarks to Bloomberg about investor enthusiasm for artificial intelligence. When asked whether we’re in an AI bubble, Altman replied, “Are we in a phase where investors as a whole are overexcited about AI? My opinion is yes.” He likened the current mood to the dot-com era, noting that “when bubbles happen, smart people get overexcited about a kernel of truth.”

Altman emphasized that AI is indeed that kernel. A transformative technology he called “the most important thing to happen in a very long time.” At the same time, he acknowledged that some startup valuations are irrational and warned that “someone will lose a phenomenal amount of money.”

These comments came as OpenAI was negotiating a secondary share sale valuing the company at $500 billion despite being just a few years old. Altman’s remarks appear to strike a balance: cautioning against investor exuberance while reaffirming his belief in AI’s long-term significance.

Why Today’s AI Market Looks Different

While Altman’s warning is worth noting, today’s environment appears to differ from the dot-com era. In 2000, the Federal Reserve tightened financial conditions, raising interest rates five times as valuations peaked. Today, we’re seeing the opposite. Rate cuts have begun. An easing could provide a tailwind for both the economy and equity markets.

Meanwhile, the AI spending continues, helping to fuel GDP, corporate earnings, and stock prices. Businesses and investors are directing tens of billions toward AI infrastructure, software, and applications.

We’ve just wrapped up a better-than-expected earnings season for Q2, and from what I can tell, Q3 looks positive as well. I believe when paired with a Federal Reserve in rate-cutting mode, the combination of earnings growth and AI investment creates a potentially favorable backdrop for equities. A bubble may eventually form, but it doesn’t appear to be on our doorstep today. If spending slows, earnings soften, and the Fed reverses course, then conditions would most likely shift. But for now, fundamentals seem to remain supportive.

As always, we’re here to help you navigate what’s next. If your financial situation has changed or if you have questions about your investment portfolio, please don’t hesitate to call us at (800) 843-7273.

 Warm Regards, 

Matthew A. Young 
President and Chief Executive Officer

August 2025 Client Letter

In an age of constant media churn, politics often dominates the news headlines. For investors, this sometimes makes it challenging to separate fact from opinion or find a clear, nonpartisan view of what’s really happening. Many are understandably frustrated when one network reports a story one way, only to hear a completely different take on another. This kind of polarization can make it harder to invest with confidence.

A prime example of this dynamic was on display with the release of the July U.S. jobs report.

The numbers were disappointing: only 73,000 jobs were added, well below the consensus estimate of 100,000. Worse, job gains for May and June were revised down by a combined 258,000, bringing the three-month average to just 35,000, a level that historically signals economic trouble.

Politically, the left suggested immigration policy as a factor, citing a sharp drop in the number of foreign-born workers in the labor force. Meanwhile, the right questioned the reliability of the data itself. President Trump even dismissed the head of the Bureau of Labor Statistics, alleging bias in the reporting.

Yet amid the finger-pointing, one critical factor may be slipping under the radar. The disruptor might not be immigration or data reliability, but instead artificial intelligence. The July employment report may be less about policy and more about a technological shift that’s transforming how work gets done.

AI Shaking up the Labor Market

Artificial intelligence is reshaping how companies operate, and it appears to me that the ripple effects are beginning to show in the labor market.

At the Cisco AI Summit this past January, Goldman Sachs (GS) CEO David Solomon revealed that artificial intelligence can now draft 95% of an IPO filing, specifically the Form S-1, in just minutes. An initial public offering (IPO) is when a private company offers shares to the public for the first time, transitioning to public ownership and raising capital for growth. What once required a team of six bankers working over two weeks now takes only a few minutes of machine time. “The last 5% now matters because the rest is now a commodity,” Solomon said. While he referenced six bankers, it’s reasonable to assume that figure excludes junior staff and support teams, likely bringing the total headcount even higher.

Microsoft: Scaling Without Hiring

This kind of efficiency isn’t isolated. Microsoft (MSFT) recently reported that revenue grew 18% year-over-year with no increase in headcount. The company has publicly stated it has no appetite to grow its finance team at the same pace as before, despite the business becoming more complex. AI is allowing Microsoft to scale its operations, streamline inefficiencies, and empower employees to do more with less.

The Crazy Efficient Revolution Behind Palantir’s Growth

Palantir Technologies (PLTR), a software platform company announced its earnings in early August. During the call, CEO Alex Karp shared a bold vision:

We’re planning to grow our revenue while decreasing our number of people. This is a crazy efficient revolution. The goal is to get 10 times revenue and have 3,600 people. We have 4,100 now.

Some analysts now forecast that Palantir could become a trillion-dollar company within the next few years. That kind of valuation is rare. What’s even rarer is the path Palantir is taking to get there: massive growth with a shrinking workforce. It’s difficult to find historical parallels for a company with such lofty expectations and such a lean operational model.

Amazon’s Robotic Workforce Surges Past One Million 

In its march toward large-scale automation, Amazon (AMZN) recently surpassed one million robots deployed across its global warehouses, up from 750,000 just a year ago. With AI now orchestrating robot movement in real time, Amazon’s fulfillment network continues to evolve as one of the most advanced logistical systems in the world. Meanwhile, Walmart (WMT), the world’s largest private employer, is undergoing restructuring. Walmart is cutting jobs and streamlining operations with AI tools. I wonder whether Walmart still sees value in holding the title of “largest employer” in an increasingly automated economy.

Lemonade: A Tech-Driven Approach to Insurance

Lemonade (LMND) is a relatively new player in the insurance industry. The company is aiming to disrupt traditional models through artificial intelligence by using AI-powered bots, which are software programs designed to perform tasks automatically without human intervention. These bots handle everything from onboarding to claims processing, often in seconds, delivering a faster and more transparent experience for policyholders. This tech-first approach allows the company to scale efficiently with fewer employees than legacy insurers. While still small in market cap (around $4 billion), Lemonade has expanded into renters, homeowners, pet, and auto insurance, and it is gaining attention for its innovative model and improving financials.

A Contrasting Strategy: Meta’s Bold Bet on AI Talent

While many companies are trimming staff and leaning on AI to drive efficiency, Meta (META), formerly known as Facebook, is taking a different approach.

Instead of mass hiring or layoffs, Meta is selectively recruiting elite AI engineers and offering them compensation packages that resemble NBA-sized contracts. Some engineers reportedly receive multi-year deals worth hundreds of thousands in base salary, with total packages reaching into the nine-figure range when stock and bonuses are included. These aren’t broad hiring waves. They’re strategic talent acquisitions, aimed at building Meta’s Superintelligence Lab and securing its place at the forefront of AI innovation.

This strategy fits squarely into the narrative: AI is not just replacing jobs; it is reshaping the value of work itself. In a labor market where efficiency is often a priority, Meta is betting that investing in the best minds will yield exponential returns. It’s a reminder that AI isn’t just a cost-cutting tool; it’s a lever for transformation.

AI: Bull Case, Bear Case, or Middle Ground?

Artificial intelligence is positioned to reshape the global economy, but how that transformation unfolds remains uncertain.

The bull case envisions a super cycle that unlocks massive efficiency gains across industries. Agentic AI, a term describing systems capable of making decisions with minimal human input, could automate not just repetitive tasks but complex cognitive work, giving workers a virtual team of assistants working around the clock. This could accelerate innovation in fields such as drug development, sciences, and logistics, potentially lifting global growth and living standards.

The bear case warns of a “jobs apocalypse.” Unlike past technological revolutions that replaced physical labor, AI is replacing cognitive labor—threatening jobs in customer service, analysis, and creative fields. If high-paying jobs disappear faster than new ones emerge, consumer spending could decline, triggering deflation or a slowdown in the economy.

The reality may lie somewhere in between. AI agents, which are software programs designed to act autonomously with other systems, are still evolving, and their limitations could slow adoption, giving the economy time to adapt. Governments may intervene to protect jobs or regulate AI’s reach. And new industries we can’t yet imagine may emerge, creating fresh opportunities and roles.

Navigating Disruption: What AI Could Mean for Your Portfolio

So, what does this mean for investors? A balanced approach that plays both offense and defense may be prudent.

On the offensive side, foundational AI players like Alphabet (GOOGL), Amazon, Broadcom (AVGO), Meta, Microsoft, Nvidia (NVDA), and Oracle (ORCL) offer exposure to the infrastructure driving the AI revolution. These firms have the scale, capital, and networks to lead the AI transformation. They’re building the platforms, chips, and data centers necessary to power the future.

On the defensive side, maintain exposure to sectors less likely to be disrupted by AI. Industries such as utilities, energy, and infrastructure—represented by companies including Chevron (CVX), Exxon Mobil (XOM), Kinder Morgan (KMI), Southern Company (SO), Union Pacific (UNP), and Valero Energy (VLO)—provide essential services that AI is unlikely to replace. These firms also offer exposure to real assets, which can be valuable in times of market volatility.

In short, investing in an era of disruption can include a balance of innovation with resilience. It’s about positioning portfolios to benefit from technological breakthroughs while staying grounded in the fundamentals that support the economy.

As always, we’re here to help you navigate what’s next. If your financial situation has changed—or if you have questions about your investment portfolio—please don’t hesitate to call us at (800) 843-7273.

Warm regards,

Matthew A. Young  
President and Chief Executive Officer

July 2025 Client Letter

With two teenage boys at home—one back from the University of Florida and the other heading into his senior year of high school—mealtime is a high-volume operation in our kitchen. The amount of protein they go through is astonishing.

Years ago, my mom gave us an Instant Pot—a gift we didn’t know we needed. It’s become a kitchen essential, cranking out chicken, farro, soups, oatmeal, and hard-boiled eggs in a fraction of the time it used to take.

But the Instant Pot hasn’t been the only regular fixture on our kitchen island. Sharing the space is my wife’s iPad. It used to be there for browsing recipe blogs and cooking websites. These days, though, it’s usually open to a simple AI chat window.

If she wants to know how long to cook black beans, she just asks—and in seconds, gets a clear, direct answer. No ads, no pop-ups, no scrolling through endless paragraphs. Just the information she needs, right when she needs it.

When I asked why she prefers the AI assistant, her answer was simple and telling: “I just want the answer—fast. I don’t have time to click through a dozen links when I’m trying to feed you people.”

The AI Market is Becoming an Economic Powerhouse

For decades, we’ve relied on traditional search engines. They help us find information, but often require time and effort to sort through. Today, that model is being replaced by something more intuitive: answer engines.

This shift is a big one. Instead of wading through a maze of content, we now just ask—and get a direct, personalized response. Often, it comes with helpful follow-up questions or even remembered preferences. It’s a move from searching for information to simply having a conversation.

Why does this matter? First, it cuts down friction and speeds up decisions. No more digging through SEO-heavy websites just to find a cook time or a definition. Second, adoption is happening fast. ChatGPT surpassed 400 million weekly users in early 2025. Bain & Company estimates the market for AI products and services could hit $990 billion by 2027.

And third, these tools are getting better with time. They remember context and adjust as they go. Ask once about cooking chicken, and the next time they’ll help with steak—tailored to the cut, your appliance, and even your preferred doneness.

Search Engines Catalog the Web. Answer Engines Work for You.

We’re moving from searching to solving—trading endless clicks for direct, personalized answers. When we planned a family trip to London, we used an AI travel tool that not only built the itinerary but nailed a recommendation for a Sunday roast at Blacklock’s. People don’t want to search—they want answers. And there’s no going back.

It started with dinner at home. Now it plans our travel. The same AI powering everyday choices is reshaping entire industries—changing how businesses operate and how people decide.

The Companies Powering AI—and the Ones Putting It to Work

The rise of answer engines is shifting how people interact with the digital world. Companies including NVIDIA and Broadcom are building the chips and systems that make real-time AI possible. Amazon, Google, IBM, and Oracle are creating the cloud infrastructure where these models—trained to understand language, spot patterns, and generate responses—live and evolve. Apple and Meta are weaving AI into everyday life, from messaging to media. And, traditional companies including Kinder Morgan, Lowe’s, and McDonald’s are using AI to streamline supply chains, personalize marketing, and improve customer service. 

We feel your portfolio is positioned to reflect this shift with exposure to both the foundational technologies powering AI and the established brands adapting to it.

Smarter Infrastructure: Kinder Morgan’s AI Advantage

Let’s look at how this plays out in the real world—starting with energy infrastructure.

Kinder Morgan is one of the largest energy infrastructure companies in North America, operating over 50,000 miles of pipelines that move natural gas and other products from major production hubs like the Permian Basin to key markets. Now, Kinder Morgan is enhancing its operations with help from Palantir Technologies.

Palantir Technologies builds advanced data platforms that turn complex, siloed data into real-time, actionable insights. Its Foundry platform is used across sectors from energy to defense to streamline operations, improve forecasting, and enhance efficiency. 

Kinder Morgan’s use of Palantir’s Foundry platform shows how traditional infrastructure companies are using artificial intelligence to modernize operations. According to a Palantir case study, tasks that once took two to three hours of manual data compilation now yield actionable insights in just minutes. The company now has a real-time view of its natural gas storage and delivery network, with time-stamped points across the system—not just at the endpoints. 

This improvement isn’t just about speed—it’s about smarter decision-making. With predictive analytics, Kinder Morgan can schedule maintenance when volumes are low, identify inefficiencies, and optimize gas across the network. The result: greater uptime and more reliable deliveries.

For income-focused investors, Kinder has raised its dividend for seven straight years and currently yields about 4.1%. Looking ahead, demand from data centers and rising energy use could provide strong tailwinds.

The AI Factory: A Digital Assembly Line

Dell Technologies and Lowe’s are partnering to bring cutting-edge AI into retail, aiming to improve efficiency and customer service across more than 1,700 Lowe’s stores as well as corporate offices.

In May 2025, Dell introduced upgrades to its AI Factory with NVIDIA, a platform designed to help businesses of all sizes put artificial intelligence to work in practical, scalable ways. Think of the AI Factory as a modern digital assembly line for intelligence—combining powerful servers, smart software, and expert services to turn data into real-time decisions. 

This progress builds on a long-standing collaboration between Dell and NVIDIA, which took a leap forward in May 2024 with the launch of the enhanced AI Factory. The initiative brings together Dell’s infrastructure and services with NVIDIA’s AI software and accelerated computing to help businesses deploy AI more efficiently and effectively.

At Lowe’s, AI is being used to optimize inventory through models that analyze purchasing patterns, improve asset protection, and alert associates in real time to assist customers in-store. Dell’s technological infrastructure enables real-time data processing and advanced analytics, such as computer vision, directly at the store level.

The collaboration with Dell is part of Lowe’s broader “Total Home Strategy” and reflects how AI is reshaping even traditional sectors like home improvement retail. It also shows Dell’s growing role as an enabler of business-ready AI across industries.

Lowe’s has a 63-year track record of dividend growth, with a 15% annualized increase over the past five years.

McDonald’s & AI: Fast Food, Smarter Systems

In an evolving market landscape, companies that adapt and innovate tend to stand out. As one of the world’s most recognizable brands, McDonald’s is modernizing its operations and customer experience through strategic investments in technology, particularly artificial intelligence.

Through a partnership with Google Cloud, McDonald’s is deploying edge computing and AI tools across thousands of restaurants to optimize staffing, kitchen, performance, and service. Digital menu boards now adjust automatically based on time of day, weather, and customer behavior—boosting upselling opportunities. In the kitchen, AI sensors monitor equipment performance for fryers and McFlurry machines to predict maintenance needs and reduce downtime. AI also supports smarter workforce scheduling and inventory management through demand forecasting. Customer-facing innovations are evolving too—from voice AI in the drive-thru to computer vision that verifies order accuracy before it reaches the customer. 

McDonald’s has raised its dividend for 48 consecutive years and currently yields around 2.43%. 

Investing in the Age of Intelligence

Whether it’s helping get dinner on the table or driving efficiency at companies like Kinder Morgan, Lowe’s, and McDonald’s, AI is no longer a futuristic idea. It’s a practical tool reshaping how we live, work, and invest. What began as a shift in how we search for answers is now transforming entire industries.

As investors, we’re focused on identifying companies that aren’t just reacting to change—but leading it. From core enablers like NVIDIA and Broadcom to established brands adapting fast, we believe there are growing opportunities. And while no investment is without risk, exposure to this digital transformation positions your portfolio to potentially benefit from the next wave of innovation. 

As always, we’re here to help you navigate what’s next. If your financial situation has changed—or if you have questions about your investment portfolio—please don’t hesitate to call us at (800) 843-7273.

Warm regards,

Matthew A. Young
President and Chief Executive Officer