As we approach the midway point of earnings season, data continues to be strong. As of this writing, 40% of S&P 500 companies have reported earnings. The beat ratio is an astounding 86%, with an 11.7% surprise to the upside:
These early results support the base case that this will be the best earnings season in years. It’s further reflected in the current year-over-year earnings growth blend of actuals and estimates – now at 15.8%:
Most importantly, an even steeper upturn could be ahead considering how the actual year-over-year earnings growth for companies is an average of 25.4%.
Fantastic earnings growth aside, what's even better is the money businesses keep – the net profit. The current quarterly net profit margin estimate is 13.4%:
That figure would mark the highest reading since FactSet began tracking in 2009.
This strength isn’t from a sector or two. It’s broad. Six sectors reported quarterly net profit margins above their five-year averages:
Bear-istas like to claim that profitability exists only in the information technology sector. The above data clearly shows that to be a fallacy.
Also, analysts believe this is just the beginning. This year’s net profit margin expectations for Q2 through Q4 are 14.1%, 14.6%, and 14.6%, respectively:
Energy
Positive fundamentals aside, let’s be realistic and anticipate an upcoming supply shock in petroleum products, jet fuel, and diesel. It’s likely there will be a material shortage globally.
But for now, the markets (especially the U.S. market) appear to be comfortable with these risks. That’s most likely because global oil shortages won’t affect the U.S. too much:
Our increasing energy independence puts us to the far right on the above chart, whereas countries dependent on jet fuel imports will experience more volatility.
AI
Let’s shift to the enormous capital expenditures taking place on the AI infrastructure and software build-out. The question of whether the current spending is justified is being answered as Wall Street is now understanding how this massive new investment wave will pay off for corporations and investors.
The notable example is Anthropic, an AI safety and research company structured as a public benefit corporation (PBC).
Anthropic develops high-end large language models (like the Claude series). As a PBC, they structure themselves to prioritize humanity over profits. Because of this, they're distinguished by their safety-first approach and use a unique constitutional AI framework to ensure their models remain helpful while also harmless.
Of course, this adds costs.
For instance, Anthropic’s most powerful recent AI model, Mythos, was released only to a small group of trusted partners, and each one was given $100 million in credits to find bugs in their systems and patch them before attackers could.
This balance of security and intelligence advancement is what’s currently setting Anthropic apart. Furthermore, most current AI models are chatbots. You ask a question, the bot answers. Mythos is called an agentic model that’s able to do a lot more.
You can give it a goal and it will plan out the required steps, write the code, test it, and fix the mistakes until the job is done. The increased care, testing, and thus cost, that Anthropic requires of itself may lead to slower product releases and slower revenue growth.
Instead, the way it’s played out through April is enterprises and investors are now seeing a proof of concept via Anthropic’s Mythos. AI isn’t merely a tool, it’s an efficiency increasing digital worker.
The narrative is switching. The current $600 billion in CapEx is a prepayment for the world’s future labor force. It shifts the return on investment to an almost automated gross domestic product growth.
But don't take our word for it, just look at Anthropic’s annual revenue forecast, which has soared at a rate that’s never been seen. The company’s forecasted revenue run rate was $9 billion at the end of 2025. In four months it’s soared to over $30 billion:
This is the most aggressive revenue spike in the history of software. It took Salesforce 20 years to reach that milestone and Anthropic did it in less than three.
This focus on safety, humanity, and business enterprise applications, even at their own cost, is beginning to pay off. It’s seen in the divergence of revenue growth between Anthropic and its “biggest competitor” OpenAI.
As Anthropic continues to gain momentum and market share, others are falling behind. Last week revealed OpenAI is missing its revenue targets for the first time.
In Cornerstone’s opinion, one is viewed as a fun chatbot while the other is a more trusted and secured business application. This is further illustrated in how much of Anthropic’s $30 billion run rate growth comes from eight of the Fortune 10 companies. These behemoths are embedding Claude into critical workloads.
AI is no longer a side project. It’s beginning to become the core engine of business operations.
Institutional Money Flows
This business transition helps explain the redeployment of investor capital and the nearly vertical move higher of companies needed for the continued AI infrastructure build-out. Wall Street has once again rationalized the massive spending.
This proof of concept is why we continually said AI infrastructure was a build-out story, not a stock story. It’s becoming clearer every day as recent institutional inflows show the theme hasn’t faded, but is spreading.
Capital is pushing past the digital layer and now further into the physical world that makes the digital layer possible. The redeployment of investor capital caused the V-shaped shift in the trusty Big Money Index (BMI), a 25-day moving average of netted institutional activity provided by our friends at MoneyFlows.
The BMI read 41% on April 2, and it’s now at 67.4%:
This 26.4% climb in 18 trading sessions is one of the sharpest changes since 1990.
The reversal occurred as panic quickly turned to conviction with a focus on fundamentals and the early signs of a positive AI ROI. As these two datasets converged, buyers stepped up.
Since April 2, 74% of all “big money” signals have been buys:
The transition is so dramatic, it revealed incredible buyer conviction, like on April 17:
Stocks saw 178 inflows and just three outflows, putting it in the 99.27th percentile in the data. Capital is gushing in.
Digging further, the collection of companies receiving these inflows shows a clear picture that’s consistent with our industrial, materials, and infrastructure thesis. It’s gaining additional momentum and strength.
Capital isn't just flowing into chips anymore. It’s hitting the full industrial chain that allows chips to exist at scale.
For example, power and grid names are showing up in force like GE Vernova and Cummins:
Construction-related firms like Caterpillar are involved in the physical structures:
Rail and logistics have begun to attract capital inflows as steel, copper, and equipment must be transported to where it's being installed, benefitting CSX:
Critical raw materials companies have also seen institutional love, like Nucor:
Lastly, the energy and fuels necessary to power the AI infrastructure build-out from companies like Cameco, which will provide the uranium to power new nuclear datacenters that hyperscalers are building:
Each of these layers creates the physical stack necessary to scale AI:
These are the companies and sectors that will continue to benefit the most from capital expenditures. And contrary to the doomsayers, the spending isn’t nearly done. It’s just beginning in some cases.
ROI is now being proven. That strengthens the physical capital investment thesis moving forward. It's clear the market is now pricing AI as a hardware, power, and construction story. Everything that feeds, powers, cools, builds, and moves the AI stack forward is what is getting bought. This theme isn't narrowing, it's broadening.
Institutional capital is clearly pricing infrastructure as a multi-sector, multi-year, CapEx-heavy reality. It’s not merely yesterday's semiconductor trade.
While many continue to be anchored to the last cycle and playbook, those who follow the money (i.e., the minority) have already moved on to buy steel, power, uranium, and rare earths. That’s the side “big money” is actually on.
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#GE Vernova, Cummins, Eaton, Caterpillar, and CSX are owned in Cornerstone client accounts.
#Cummins and MP are owned by Daniel Milan personally.
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