The Daily Spark

Cleanview data shows that Texas alone accounts for roughly 100 GW of planned data center capacity, more than the next two states, Virginia and Utah, combined, see chart below. Virginia, by contrast, still leads on operating capacity at 17 GW.

The tailwinds behind the US economy are not just AI spending, the industrial renaissance and the One Big Beautiful Bill.

Tariff refunds have now joined the list, see chart below. Not only are tariff refunds boosting corporate earnings, they are also boosting GDP growth.

The Atlanta Fed's GDPNow currently points to 4.3% growth this quarter, of which we estimate roughly 0.2 percentage points come from tariff refunds.

The bottom line is that the US economy continues to be supported by a growing set of tailwinds.

The July employment report does not change that. The headline decline was driven by a 50,000 drop in local government education, reflecting school-calendar seasonals, and a 40,000 decline in leisure and hospitality as the World Cup boost rolled off. Adjusting for these two quirks in the data gives underlying job growth of close to 70,000, broadly in line with what the consensus had expected before the release.

In addition, jobless claims around 200,000 and the number of job openings rising in the past six months also point to a strong labor market.

In short, the market is underestimating how strong growth is right now. As a result, rates will stay higher for longer.

AI-related issuance already accounts for nearly 40% of longer-duration IG corporate bond supply, and the financing needs are only getting larger. We estimate the AI ecosystem could fundamentally support more than $2 trillion of additional IG debt, while public IG markets may be able to absorb less than $1 trillion of that amount through 2030 because of concentration and ratings constraints.

That gap creates a significant opportunity for private IG. We expect more than $1 trillion of financing could migrate toward private placements, infrastructure debt, asset-backed facilities, equipment financings and project-level structures — often with collateral, contractual support and structural protections that are unavailable in unsecured public bonds.

Read more in our 2026 Midyear Credit Outlook.

Spider-Man and The Odyssey have lifted weekly box office grosses to a record high, see chart below.

Consensus earnings expectations still imply remarkably little disruption from AI. Of more than 200 publicly traded software and white-collar services companies we track, only 10 are currently expected to experience both revenue and EBITDA declines over the next two years. That suggests markets may be pricing in the possibility of AI disruption without yet fully incorporating its potential impact on earnings and margins.

We think about that AI pressure through three channels: direct replacement, where AI performs the same task at a lower cost; labor displacement, where AI reduces the number of employees, contractors or users supporting a business model; and execution risk, where AI-native competitors innovate faster and take market share. As adoption accelerates, these are the channels we are watching for signs that AI disruption is beginning to show up in fundamentals.

Read more in our 2026 Midyear Credit Outlook.

Europe and the US face the same AI displacement. Only the US gets what offsets it: the startup formation, the capex and the hiring that comes from building the technology rather than only absorbing it.

The widening unemployment gap between France and the US is starting to look like the price of being on the wrong side of that asymmetry.

Chipmakers and health care sectors have converged to identical forward P/E ratios for the first time in years, see chart below.

The S&P 493 is spending heavily on AI. But it is not showing up in profit margins, see the first chart below.

Looking at the individual sectors of the S&P 500 outside tech shows that the picture is flat, cyclical or worse, see charts 2, 3 and 4.

Health care margins have halved since 2015; consumer staples are stuck near 6% and consumer discretionary near 8%; energy and materials have given back most of their 2022-23 gains; real estate is going sideways; and the only genuine improvements look like an ordinary cyclical recovery rather than a technology-driven step change.

The bottom line is that the AI capex boom is so far only showing up in the sellers' margins, not the buyers'.

This is important because the longer it takes the S&P 493 to generate ROI, the bigger the downside risks to an economy and a market this concentrated in the AI trade.

For more, see here.

Banks provide less than one-fifth of nonfinancial corporate debt, down from half in the 1970s.

What replaced banks is not one thing but many: syndicated and public markets for the largest borrowers, and private capital for everything that needs certainty of execution, customized structures, or longer duration than a bank balance sheet can comfortably hold.

The bottom line is that the financial system has shifted from short-dated deposit funding toward long-dated institutional capital, matched more closely to the assets it finances.

A wider lender base means borrowers have more places to go, which is good for growth and financial stability. Credit risk now sits with long-duration investors who chose the exposure and are funded to hold it through a cycle, rather than on leveraged, deposit-funded bank balance sheets.

In business, profit margins are frequently higher for the owner of the end-customer relationship.

But that is not the case for AI. In AI, profit margins are higher the further you get from the end user, see chart below.

This is important because it means the AI boom's profits are currently being funded by investors rather than earned from customers. The upstream margins are real, but they are paid for out of capital raised by the layer losing money, not out of cash generated by end demand. That makes the 41% contingent on the -59% continuing to be financeable.

The bottom line is that the most profitable part of the AI value chain depends on the least profitable part continuing to grow revenue or raise capital. Capital can bridge the gap for a while, but not indefinitely. And therein lies the risk: will the ROI show up for AI's end customers fast enough to sustain the spending that is generating those upstream margins?