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August 26, 2025

Surviving (and Thriving) in the AI Economy

After a huge recovery from April lows, some investors are getting nervous about AI again. AI-related stocks have run into several bad headlines in recent weeks, which have challenged investor confidence.

As we told you when AI wobbled earlier this year, it’s critical to see (and invest) beyond the mainstream media headlines.

Investors dumped Meta Platforms (META) after it was reported to have initiated an AI hiring freeze. (Shares of META are now only down a few percentage points from their mid-August all-time highs, but reports of the pause led to selling pressure after they surfaced.)

Long-term investors need to understand: AI is not a fad. The changes taking place in the economy right now, as a direct result of innovations in AI, are real, profound and enduring.

There will no doubt be all kinds of noise, mixed signals and volatility along the way—and certain stocks may get overextended from time to time.

We urge investors to maintain a long-term view of the AI opportunity set and brace themselves for wide-ranging impacts.

The objective of this note is to explain what we perceive as the likeliest and most significant long-term impacts of AI on the economy and markets—and the steps investors can take now to prepare for them.  

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Zuck’s AI bonanza

META confirmed it is pausing hiring in its AI division but attributed it to “basic organizational planning” as CEO Mark Zuckerberg and his team figure out how to create “a solid structure for our new superintelligence efforts.”

The pause follows an extremely aggressive hiring spree by META in recent months. To bring on top AI talent, the company has offered unprecedented pay packages on par with the some of the most highly paid professional athletes.

The “scale back” was in fact short-lived. Days after the story broke, reports surfaced that META poached yet another Apple (AAPL) AI executive.

Frank Chu is the sixth AAPL employee META has hired. He will report to his prior boss, Apple (AAPL) engineer Ruoming Pang, who earlier snagged a deal worth more than $200 million. This consists mostly of stock, with numerous conditions and performance hurdles attached.

In some cases, META has purchased entire businesses, just to bring people into the organization. The new Chief AI officer Alexandr Wang was obtained after META took a 49% stake in his start-up Scale AI at a reported $14.3 billion valuation.

Among the youngest self-made billionaires in the world, Wang was born in 1997 in Los Alamos, New Mexico to two immigrant physicists from China who worked at the famous Los Alamos National Laboratory, where the atomic bomb was invented.

When Zuck wanted to bring on AI-focused venture capitalists Nat Friedman and Dan Gross in July, he simply shelled out a few billion dollars to buy out minority investors in their VC funds.

Given the extreme lengths META has gone this summer to assemble its AI dream team, we struggle to read too much negativity into its recent hiring pause. It makes perfect sense that they would want to take a deep breath and figure out who does what.

DeepSeek 2.0?

The market’s latest AI jitters are reminiscent of the DeepSeek episode from earlier this year, when AI-related stocks sold off as some investors were rattled by a narrative of declining demand for AI equipment.

With leading AI stocks like NVIDIA (NVDA) delivering impressive sales growth in the months that followed, that bout of negativity now appears quite misguided. As we told subscribers at the time, efficiency breakthroughs would likely spur demand for AI chips and gear, rather than suppress it.

Nonetheless, many AI stocks do currently have rich valuations that reflect ambitious expectations for future growth.

Whenever expectations are high and the outlook uncertain, there will be always be volatility and setbacks. And not every perceived AI play will succeed in the end. Long-term investors need to be prepared.

Nobody can say for sure how the AI story will unfold. What we do know is that AI is advancing at an extraordinary pace, and trillions of dollars are being deployed across industries to accelerate its trajectory.

We cannot predict in detail what will happen. But we can—and must—try to understand the big picture and do our best to act accordingly.

How far we’ve come

Just a year or two ago, talk of AI sounded like a preview to a science fiction movie. But now we are seeing and interacting with AI in real time. AI’s role in our lives is deepening everyday.

The NVDA stock chart tells the story.

NVDA is the key hardware provider powering the AI revolution. Without the breakthroughs of founder Jensen Huang and NVDA, arguably none of this would be happening.

If we merely rewind a couple of years to early 2023, NVDA was basically just another tech stock. It was primarily a maker of chips—Graphic Processing Units or GPUs—that support graphics-intensive video games on personal computers.

NVDA’s data center business—which sells the majority of GPUs that are used for AI supercomputing in the cloud—was just about to take off.

Over the next two years, NVDA went from a respected tech stock to the world’s most valuable business and the first $4 trillion market cap company.

After a short-lived downturn early in 2025 related to the misperceived DeepSeek threat, NVDA is back to all-time highs.  

NVDA vs. S&P 500

(Total Return - Last 3 Years)

Technological revolutions are exciting. This makes it is easy to lapse into hyperbole and for investors to develop exaggerated expectations.

Radical change is also unnerving. This makes it easy to lapse into denial and to underestimate what’s in store.

In behavioral economics, there is a concept called the status quo bias. Many people are uncomfortable with change, so they gravitate to narratives that perceptions of change are overblown.

Anchoring to key impacts

Like many other investors, we have been thinking hard about the long-term implications of AI and how to best position our Model Portfolios as AI reshapes the global economy.

Having grown up during the late 1990s tech bubble, we understand the risk of getting carried away with hype. But we also do not want the scars from that era to blind us to the realities ahead.

We do not have a crystal ball, but we do believe there are identifiable impacts that investors can rely on and use as guideposts.

Below, we describe what we believe are four major impacts of AI on the economy and markets. We later explain actionable steps that investors can take to protect themselves and take advantage of these potentially enormous shifts.

(1) Capital will replace labor

At its core, AI substitutes human brains with computer hardware.

AI breaks down all knowledge and information into “tokens.” These are comparable to atoms in the physical world. Tokens, which can be a word or syllable, are the smallest chunk of text that an AI model will process.

When people speak about the growth of AI, they will often describe it in terms of the number of tokens generated. The more tokens AI models produce, the more work they are doing.

The human brain remains an impressive piece of equipment, but it has many limitations. It can be trained and enhanced through processes known as education and experience, which play out over decades and can cost hundreds of thousands of dollars.

But there is a limit to how quickly and competently even the finest human brains can process information. In many cases, GPUs housed in AI data centers can process information much more quickly and at lower cost.

With each passing day, as investments are made, models are trained and the underlying technology improves, the information processing ability of AI grows.

In the context of business, AI tools perform tasks that were previously the responsibility of human employees. These range from the most complex cognitive activities to the most mundane.

The end of jobs?

At the far end of the spectrum, there are credible people who believe AI will basically replace jobs as we know them altogether. Elon Musk, whose own Grok AI model is at the frontier of AI computing capability, is one of them.

It's hard to say exactly what that moment is, but there will come a point where no job is needed….  You can have a job if you want to have a job — sort of personal satisfaction — but the AI will be able to do everything. - Elon Musk (11/3/2023)

Offsetting the idea that jobs will disappear altogether is the idea that wealth and prosperity will create new jobs.

What we are fundamentally describing when it comes to AI and jobs are productivity gains.

Productivity is the total amount of economic output per worker. AI will allow human beings to produce more with fewer people involved.

AI is of course not the first productivity-enhancing technology that humanity has encountered that has changed the complexion of the work force.

Prior to the Industrial Revolution, the vast majority of people around the world were farmers. Advances in technology meant fewer human beings were then needed to produce the agricultural output required for collective survival.

Today, only about 1% of the U.S. work force reports to a farm.

Just fifty years ago, the United States employed about 17 million people in the manufacturing sector. Today, that number stands at about 13 million people.

This represent about a 25% decline, even though the U.S. population has grown by more than 50% since then.

U.S. Manufacturing Employment

(Last 50 Years)

Automation and globalization have driven vast productivity gains in the manufacturing sector over the past fifty years. This has disproportionately impacted regions that relied on manufacturing-related industries.

But unemployment rates today stand around 4%, which is generally seen as full employment. While manufacturing jobs have plunged, over 80% of jobs now are in the service sector, versus about 66% fifty years ago.

U.S. Service Sector Employment

(Last 50 Years)

These service sector jobs—including millions of clerical and sales roles but also more skilled positions like computer programmers and paralegals—will now potentially follow the same path of manufacturing jobs.

As AI gets smarter, it will potentially reduce demand for even highly complicated jobs, like doctors and lawyers. We will probably still need doctors and lawyers—but AI will help them get more done every day, so perhaps not as many.

As AI-infused robotics advances, it will potentially take out more manual jobs, from drivers to cashiers.

The critical issue is whether prosperity created from AI-driven productivity gains will spur new job creation at a pace that keeps up with job losses.

It is quite possible that AI will kill jobs more quickly than it creates them. Investors should certainly prepare themselves for this scenario, which we will address in more depth later.

(2) Certain businesses will become more profitable

Like any productivity wave, AI will likely on balance be good for owners of business enterprise. But the rewards will be uneven.

Businesses have two ways to increase profits. They can grow their revenues, and they can reduce their costs. Companies have the opportunity to take advantage of AI in both ways.

NVDA has led the way over the past two to three years, but many companies have already been huge beneficiaries of the AI theme, whether based on actual or anticipated profit growth or some combination of the two.

Markets are discounting mechanisms. Stock prices don’t just respond to profit growth; they anticipate it well before it materializes (even if in some cases it never does).

There is no question that AI will drive profit growth across many companies.

The big challenge investors now face is two-fold: (1) identifying stocks which will indeed see AI-driven profit growth, and (2) identifying stocks where this growth has not already been priced into the shares through elevated earnings multiples.

(3) Certain businesses will become less profitable

As AI changes the way the economy functions, many businesses may find themselves on the short end of the stick.

On the revenue side, AI will create new areas of growth that will potentially shift spending away from other areas. Some businesses may find themselves chasing smaller addressable markets.

On the cost side, AI will create efficiencies that will allow companies to become more price competitive. This could lead to potentially severe profit margin pressure among companies that are unable to implement AI as well as competitors.

(4) More electricity will be consumed

While many future impacts of AI remain unclear, one change to the economy that seems inevitable is that much more electricity will be consumed.

What AI is capable of doing seems limitless, but AI itself has two basic requirements… GPUs and the energy needed to power them.

Projections vary widely, but there is widespread agreement that after decades of more or less flat U.S. electricity consumption (thanks to energy efficiency gains), we are now at an inflection point.

The National Electrical Manufacturers Association (NEMA) projects 2% annual growth in U.S. electricity consumption per year over the next 25 years. This will be driven primarily by AI data centers and electric vehicles (which are linked to AI via self-driving cars).

Source: NEMA

Electrification is an AI-related investment theme that will have impacts across a wide range of industries as the world ramps up its ability to generate and transmit electricity.

AI will likely become more energy-efficient over time, but this will only drive down the cost of AI token generation and thereby stimulate more demand for AI.

NVDA’s Jensen Huang recently praised President Trump for his understanding of how intertwined electrical energy production is with U.S. success in AI. Meanwhile, Sam Altman, founder of OpenAI, has described electricity as the limiting factor on AI growth.

I think it's hard to overstate how important energy is to the future here. Eventually chips network gear that will be made by robots and will make that very efficient and will make that cheaper and cheaper, but an electron is an electron. Eventually the cost of intelligence, the cost of AI will converge to the cost of energy and it'll be how much you can have. - Sam Altman (5/8/2025)

In terms of the impact of AI on the economy, we need to consider not just what AI will do but what AI requires to do it. In addition to lots of GPUs and data centers, AI needs an enormous amount of electricity and related infrastructure.

An AI roadmap for investors

We may not know what AI will look like 5, 10 or 25 years from now, but we have a directional sense of the changes ahead.

There will be productivity gains (potentially vast), there could be negative impacts on labor markets (potentially vast), and there will be disparate outcomes across companies and industries.

Below, we highlight four actionable steps investors can take both to protect themselves from potentially negative consequences of AI-related change and to take advantage of upside opportunities.

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