Is AI Spending Translating Into Profits for Companies?

Yes, but not everywhere, and certainly not equally.

There is a tendency with every major technological cycle to gravitate toward one of two extremes. Either the technology is going to change everything immediately, or the enormous amount of spending proves we are in a bubble.

I don’t believe either conclusion is particularly useful.

AI is already producing meaningful economic returns for some companies. We can see it in cloud computing, digital advertising, software development, semiconductors and data-center infrastructure.

But for much of corporate America, AI adoption is running well ahead of AI profitability.

That distinction matters.

Spending Is Easy. Generating a Return Is Harder.

Companies are spending aggressively on chips, data centers, cloud capacity, models and implementation. That money is being spent today.

The return comes later—and only if AI solves a high-value business problem.

The companies seeing the clearest benefits generally have some combination of:

• Massive existing distribution
• Large proprietary data sets
• High-value processes that can be automated
• Existing businesses where relatively small efficiency gains translate into billions of dollars
• The ability to deploy AI across the enterprise rather than through isolated experiments

That is why some of the largest technology companies are already seeing tangible benefits.

Meta Is a Good Example

Meta is not simply spending money on AI in hopes of creating a business someday. AI is being incorporated directly into an enormously profitable business that already exists.

AI-powered advertising systems can improve recommendations, ad targeting, campaign automation and conversion. If those improvements make advertising more effective, advertisers have an incentive to spend more.

In the second quarter of 2026, Meta’s revenue increased 28% year over year, while advertising revenue increased 27%.

That does not mean AI was responsible for all of that growth. It clearly wasn’t.

But AI is increasingly embedded in the engine that drives Meta’s advertising business. This is an important distinction: Meta doesn’t necessarily need AI to create an entirely new revenue stream. It can generate enormous value simply by making its existing revenue machine more effective.

At the same time, investors shouldn’t ignore the cost. Meta spent more than $31 billion on capital expenditures during the quarter, and free cash flow fell to just $784 million. AI may be improving the core business while simultaneously requiring enormous investment.

Both things can be true.

The Infrastructure Companies Are Benefiting First

The most obvious beneficiaries remain the companies selling the picks and shovels.

AI requires extraordinary amounts of computing power. That means demand for:

• Semiconductors
• Cloud infrastructure
• Networking equipment
• Data centers
• Power generation and transmission
• Cooling systems
• Storage and memory

This is one reason cloud growth has accelerated dramatically. The economic logic is straightforward: before companies can make money using AI, somebody has to provide the infrastructure that allows them to use it. Those infrastructure providers are monetizing the AI boom today. For everyone else, the calculation is more complicated.

Productivity Is Not the Same Thing as Profitability

This may be the single most important distinction for investors.

McKinsey’s 2026 global AI survey found that 80% of respondents said AI had improved their individual productivity. Yet only 37% said AI had contributed positively to their organization’s EBIT (Earnings Before Interest and Taxes).

Even more revealing, only about 6% of respondents qualified as AI high performers, meaning AI was contributing at least 5% of EBIT and was having a significant financial impact. That is an enormous gap. An employee saving five hours per week sounds impressive. But what happens to those five hours? If the employee produces more revenue, handles more customers, allows the company to avoid hiring additional workers or enables the company to reduce costs, there is an economic benefit.

If the employee simply has five additional hours available but the company’s cost structure doesn’t change and revenue doesn’t increase, the productivity improvement may never meaningfully reach the income statement.

AI can make people more productive without making the company materially more profitable. That is the issue investors should be watching.

AI Has to Change the Economics of the Business

Consider a few examples.

A company can install an AI customer-service chatbot, but if it maintains exactly the same customer-service headcount, where is the financial return? A marketing department can use AI to produce ten times as much content, but if that content doesn’t generate more qualified leads or sales, what has actually changed? A financial-services company can use AI to summarize meetings and prepare reports faster, but unless that allows employees to serve more clients, improve retention, reduce costs or generate additional revenue, the economic benefit may be relatively small.

On the other hand, if a software company uses AI coding tools and can develop products faster with fewer incremental hires, that can materially change margins.

There are already signs of this happening. McKinsey found that nearly one-third of surveyed companies had decided not to purchase at least one software product or feature because they believed they could build it internally using AI coding tools.

That is a real economic consequence.

Then There Is the Capital-Spending Question

This is where the AI debate becomes more interesting for investors. The largest technology companies are spending extraordinary amounts of money building AI infrastructure. The numbers are enormous, and the spending is occurring before we know precisely how large the eventual profit pool will become. That doesn’t mean the spending is irrational. Some of the greatest investments in business history required enormous upfront capital before the economic returns became obvious.

But investors should ask a basic question:

What return will ultimately be earned on all of this capital?

Revenue growth alone doesn’t answer that question. Neither does AI adoption. Ultimately, we need to see incremental operating income, free cash flow and attractive returns on invested capital. That will separate successful AI investments from expensive technology projects.

The Next Phase of AI Will Be About ROI

We have spent the past several years asking which companies are using AI. That question is becoming less relevant because eventually nearly every major company will use it.

The more important questions are becoming:

• Is AI increasing revenue?
• Is it reducing labor or other operating costs?
• Is it allowing the company to grow without adding expenses at the same rate?
• Is it improving margins?
• And ultimately, is the return greater than the cost of the investment?

That is where I believe the market’s attention will increasingly shift.

The AI revolution does not need every company to immediately generate enormous profits for the investment thesis to work. General-purpose technologies historically take time to work their way through organizations and ultimately change productivity.

But investors also shouldn’t assume that every dollar labeled “AI spending” will generate an attractive return.

There will be enormous winners. There will also be enormous amounts of wasted capital.

The challenge is distinguishing between the two. So rather than asking, “Is this company using AI?” I believe investors and business owners should be asking a much more important question: “What measurable profit driver is AI improving—and can I see it in the numbers?”

That is ultimately where the AI story has to go.

Palumbo Wealth Management (PWM) is a registered investment advisor. Advisory servics are only offered to clients or prospective clients where PWM and its representatives are properly licensed or exempt from licensure. For additional information, please visit our website at www.palumbowm.com.

The information provided is for educational and informational purposes only and does not constitute investment advice and it should not be relied on as such. It should not be considered a solicitation to buy or an offer to sell a security. It does not take into account any investor’s particular investment objectives, strategies, tax status, or investment horizon. You should consult your attorney or tax advisor.

The views expressed in this commentary are subject to change based on market and other conditions. These documents may contain certain statements that may be deemed forward‐looking statements. Please note that any such statements are not guarantees of any future performance and actual results or developments may differ materially from those projected. Any projections, market outlooks, or estimates are based upon certain assumptions and should not be construed as indicative of actual events that will occur.

All information has been obtained from sources believed to be dependable, but its accuracy is not guaranteed. There is no representation or warranty as to the current accuracy, reliability, or completeness of, nor liability for, decisions based on such information and it should not be relied on as such.

All information has been obtained from sources believed to be dependable, but its accuracy is not guaranteed. There is no representation or warranty as to the current accuracy, reliability, or completeness of, nor liability for, decisions based on such information, and it should not be relied on as such.

The views expressed in this commentary are subject to change based on the market and other conditions. These documents may contain certain statements that may be deemed forward‐looking statements. Please note that no such statements are guarantees of any future performance, and actual results or developments may differ materially from those projected. Any projections, market outlooks, or estimates are based upon certain assumptions and should not be construed as indicative of actual events that will occur.

Past performance is no guarantee of future returns.

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By: Adam