TheChek News Flow

Investors typically look to emerging markets for diversification from their U.S. holdings. But these days, holding the most popular emerging market investments amounts to doubling down on the artificial-intelligence themes driving U.S. markets.

The Magnificent Seven have nothing on emerging markets’ semiconductor trio. Taiwan Semiconductor, Samsung Electronics, and SK Hynix account for 30% of the MSCI Emerging Markets index, which is up 22% this year—double the gain of the S&P 500.

The broad emerging markets index is an even bigger bet on the wider tech scene, with information technology accounting for half the allocation. There’s also country concentration: Some 70% of the index is invested in China, Korea, and Taiwan.

Investors looking for diversification in the event AI doesn’t live up to its promises can find hedges within emerging markets, but they need to go beyond the index.

While Rory Green, head of China research at TS Lombard, sees emerging markets as well positioned for geopolitical and technology trends and likes their growth potential over the longer term, he warns that the backdrop for the rest of the year is trickier, given the run-up in South Korea’s and Taiwan’s stock markets and the strong growth coming out of the U.S.

South Korea is especially vulnerable, due to leveraged exchange-traded funds and a retail investor base that has been driving up to 60% of the market’s moves—an uncomfortably high level, says Charles de Boissezon, global head of equity strategy at Société Générale.

Another risk: Some Chinese chip makers are going public soon, with ChangXin Memory Technologies beginning to take orders for what is expected to be a $4 billion-plus offering on China’s domestic Shanghai Stock Exchange. Their debuts could poke holes in the idea of a memory shortage, a theme that has driven South Korean stocks higher, Green says.

As fund managers trim some of their tech winners, many are taking a closer look at laggards. Young Jae Lee, an emerging markets fund manager at Pictet, sees the 30% of the index outside of Taiwan, South Korea, or China as more representative of the diversification opportunity that has drawn investors to emerging markets. Countries like Brazil, India, and even parts of Africa are home to growing working populations that drive increased income and consumption.

A burgeoning middle class buying cars, financial products, and other services is a good way to hedge against AI overconcentration, says Lee, who is also a co-manager on Pictet’s recently launched Emerging Markets Rising Economies ETF.

Valuations in Brazil are sitting near historic trough levels even as its banks, telecoms, and other companies churn out stable earnings and high dividend yields, Lee says. The country’s fall presidential election looms, but he sees a status quo situation if populist President Luiz Inácio Lula da Silva is re-elected.

In China, the domestic A-shares market and the CSI 300 index have outperformed the broader MSCI China index, which has fewer of the AI, industrial, and other companies getting the bulk of Beijing’s support. Any pullback in the A-shares market is likely a buying opportunity, with Green expecting Beijing to come in and buy stocks if the market falls 10% or more.

But over the next couple months, he sees a better opportunity in the lagging MSCI China index, which is dominated by internet giants and consumer-oriented companies. Valuations on internet giants and some of the country’s biggest consumer businesses are sitting near Covid-era lows. That is drawing the likes of Tom Harvey, senior equity specialist at Aberdeen Investments, who has taken some gains from AI-related stocks and put them in consumer companies—including in China, where he thinks the worst is behind these companies.

Green also sees a possible catalyst ahead: Tencent Holdings is expected to launch an AI-embedded version of its ubiquitous WeChat app—used by some one billion people—possibly appealing to investors who had dismissed such companies as too slow on AI.

AI fatigue may make what was old hot again in emerging markets. If so, looking beyond the iShares MSCI Emerging Markets ETF or the Vanguard Emerging Markets Stock Index fund, which track the broad index, may be the way to go.

SpaceX shares fell back to Earth following their blockbuster initial public offering. But Elon Musk’s rocket company is also dragging down T-Mobile US and its wireless and broadband rivals due to worries that SpaceX’s Starlink will be a formidable foe in the high-speed internet business. Those fears are overdone—and T-Mobile’s stock is now looking like a good bargain.

T-Mobile has fallen slightly since SpaceX’s IPO in mid-June and is down 8% this year, partly due to worries about competition from Starlink. Shares of Verizon Communications and AT&T, as well as cable companies Comcast and Charter Communications, have all slid since SpaceX went public. But T-Mobile has the best chance of bouncing back.

Morgan Stanley’s Sean Diffley said in a report in early July that “the perceived risk of Starlink Mobile disrupting the U.S. wireless industry is greater than the actual risk in the next one to two years.” He said the big three wireless carriers have improved their speeds and customer satisfaction rates over the past several years. He added that T-Mobile is his best idea in telecom/cable, arguing that the company “offers the fastest growth” along with the “strongest spectrum position.”

Diffley thinks concerns about SpaceX are a classic case of Wall Street overreacting. “The market is increasingly concerned that Starlink is going to make a more aggressive push in mobile,” he wrote, adding that “the fear of the unknown has led many to shoot first and ask questions later in telecom.”

BofA Securities’ Michael Funk also dismissed fears about SpaceX, writing in a recent report that “T-Mobile is least exposed to the competitive threat” from low Earth orbit internet services like Starlink. “T-Mobile wireless has 50% share of households in urban markets such as LA and NYC and only 24% share in rural markets,” he wrote, adding that a service like Starlink “seems to work best in rural and underserved environments.”

Funk has a $220 price target on T-Mobile while Diffley has a $230 price target. That actually makes them a little less bullish than many of their peers. The average price target according to FactSet is just over $251, 33% higher than T-Mobile’s current price.

That seems reasonable given the stock’s valuation. T-Mobile is trading for 14 times earnings estimates for 2026, a price-to-earnings ratio that’s barely above its five-year low of 13 and well below its five-year average forward multiple of nearly 20.

While that’s a premium to the multiples of eight and 8.5 for Verizon and AT&T, T-Mobile is worth it given that its long-term projected earnings growth rate is nearly 16% a year on average compared with long-term growth forecasts of just 7.4% for Verizon and 8.8% for AT&T.

T-Mobile even pays a decent dividend that yields 2.2%. Sure, that’s a lot lower than the yields of 5.2% for Ma Bell and 6.7% for Verizon, two income stalwarts. But T-Mobile’s dividend, in conjunction with its above average earnings growth and overdone fears about SpaceX, makes the stock, with its signature magenta logo, look pretty in pink.

An FDA hearing in late July may lead to a peptides boom. What consumers and investors need to know.

An FDA advisory panel will hold hearings in late July on whether to let compounding pharmacies produce and sell more peptides.

FDA staff scientists said in a recent report that the bulk of criteria weigh against placing the substances on a list for permitted use.

Health Secretary Robert F. Kennedy Jr. supports regulating more peptide production to shift demand away from the black market.

Many Americans would love a drug that makes them fitter, sharper, and more attractive. The peptides industry aims to oblige, and sales may soon be off to the races, courtesy of the Trump Administration and its chief peptides backer, Health Secretary Robert F. Kennedy Jr.

Peptides are short-chain amino acids that are formulated into drugs. Insulin is a peptide. So are GLP-1s like Ozempic. Legions of other peptides are on the market in the “wellness” industry, promoted for everything from athletic performance to skin care, mental focus, and “romantic connection”—the latter pitched by a startup called Feel Peptides.

Compounding pharmacies make some peptides, but many are manufactured without much oversight with ingredients mainly sourced from China. They’ve soared in popularity online, often sold to consumers without a prescription, designated for “research use.”

The FDA may soon step into that gray market, allowing compounding pharmacies to produce and sell more peptides. An FDA advisory panel is scheduled to hold hearings in late July on whether to recommend seven substances for inclusion on a list of approved bulk ingredients that compounders may use to create peptide drugs.

Several popular peptides are under review. BPC-157, for instance, is the poster child for muscle and tissue repair. Others include TB-500, popularly paired with BPC-157 in a “wolverine stack” to recover from workout injuries, and MOTs-C, marketed for metabolism benefits.

Five more peptides are up for review by early next year. The FDA panel is evaluating each peptide for uses—like BPC-157 for ulcerative colitis—that don’t necessarily match up with what they’re known for online.

Kennedy has has said he’s a “big fan” of peptides and indicated he wants the FDA to regulate more of their production. The advisory panel review “begins to restore regulated access and will immediately begin shifting demand away from the black market,” he said on X.

The advisory panel includes several physicians involved in peptides. At least six doctors on the panel are involved in peptides therapy and some have posted content about the drugs, according to their disclosures and websites.

The FDA isn’t obligated to take the panel’s recommendations, an FDA spokesperson said. “All committee members underwent the same ethics review and vetting process required of all FDA advisory committee members,” the spokesperson added.

Peptides are contentious in the medical community. A dearth of clinical trial data in humans has long raised concerns. The FDA restricted compounders from selling certain peptides in 2023, citing safety risks. In a report made public in the past week, FDA staff scientists said the bulk of criteria “weigh against” placing the substances on a list for permitted use in compounded drugs.

Wall Street, for its part, sees a potentially large growth market. Needham analysts estimate an addressable market for non-GLP-1 peptides of $34 billion, up from around $3 billion in annual sales now, assuming FDA permission and other factors fall into place. Investment bank Leerink Partners sees a $2.2 billion market for telehealth companies, based on sales projections of the first seven peptides under review.

The biggest publicly traded beneficiary could be Hims & Hers Health. The telehealth company bought a peptides manufacturing facility last year. Leerink analyst Michael Cherny estimates Hims could capture 20% of the $2.2 billion market. “The Hims chassis should be well-positioned to maximize peptide sales,” Cherny says.

Hims says over half the questions it received before its recent earnings call were on peptides. The company doesn’t have to be “first to market,” CEO Andrew Dudum told investors, but it aims to be “the best.”

For now, Hims remains a play on GLP-1s. The stock started taking off in March after the company struck a deal with Novo Nordisk to sell its branded GLP-1s like Ozempic and Wegovy. Shares got another boost Wednesday after Canaccord Genuity and Bank of America raised price targets, citing an improving outlook for branded GLP-1s.

Most analysts see the stock fully valued. Its average rating is a Hold with a target of $29, below recent prices around $38.

Needham analyst Ryan MacDonald has a rare Buy on Hims, but he pegs the fair value at $35. He views recent updates from FDA as mixed, but thinks it’s “more likely than not” the agency will permit the peptides, he told Barron’s.

Wall Street’s caution on Hims reflects another unknown: whether peptides sold for unapproved uses will make the leap from the medical fringes to mainstream consumer adoption.

While there’s some clinical evidence for peptides, claimed health benefits tend to rely on preclinical or animal studies and research conducted outside the U.S.—lacking the kind of rigorous studies the FDA requires to approve a drug. Unlike FDA-approved medications, compounded drugs don’t go through the same process in which clinical data is reviewed for safety and efficacy.

The peptides up for FDA review “are in general lacking most or all of that information,” says Peter Lurie, a former FDA official and head of the Center for Science in the Public Interest. The FDA’s move on peptides could undermine the clinical trial process, he adds, while consumers waste money on products that are ineffective.

While the science is unsettled, scores of companies are gearing up to sell peptides. Privately-held telehealth company Noom recently bought a compounding pharmacy and plans to expand into peptides. “Noom believes that peptide-based therapies should move out of the unregulated gray market and into a legitimate, clinically responsible framework,” the company said in a statement.

Gyms may also add peptides to their menus of massages and other add-ons. A gym charging $100 for a monthly membership, for example, could make an additional $100 a month from the same customer with peptides, says Jon Lensing, co-founder and CEO of OpenLoop Health, a telehealth infrastructure company. “It’s a significant revenue bump with an already existing audience they control,” he says.

Several physicians on the FDA’s peptides committee work at longevity clinics and have posted content about peptides. Gabriel Alizaidy describes himself as a “peptide and hormone” educator on LinkedIn and offers consultations for peptide protocols. Asare Christian, another panel member, has posted content called Unlocking Your Potential with Peptide Therapy.

Haleem Mohammed, also on the panel, is chief medical officer for a network of clinics called Gameday Men’s Health, which markets peptide and vitamin injections on its website.

The three panel members didn’t reply to a request for comment.

Proponents argue there’s ample evidence for taking certain peptides. Lee Rosebush, an attorney and co-founder of a nonprofit, the American Academy of Peptide Medicine, has challenged FDA restrictions on peptide compounding. He plans to present at the advisory meeting, telling Barron’s, he looks forward “to providing additional clinical information…that shows that safe access to these peptides is possible.”

Some investors, after taking peptides themselves, are betting on them financially.

Venture capitalist Brian Sugar started taking GLP-1s for weight loss and then tried BPC-157 tablets. The experience was eye-opening, he says, and he saw mass-market potential in peptides more broadly. He’s since invested $1.5 million in Feel Peptides through his firm, Sugar Capital.

“It was very clear to me, after this experience that I went through, that GLP-1 was, as I call it, the amuse-bouche of what’s going to be happening,” he says.

Other investors say they’d like to see more clinical data before investing in wellness peptides. Joe Horsman, a Ph.D. biochemist and investor at venture capital firm Madrona, has backed biotech companies developing peptide therapies. But Horsman says low clinical evidence for many peptides in the wellness space remains a challenge. “I’d love to see some safety data before we say, ‘Go nuts, people.’ ”

Electricity-hungry data centers play right into Williams’ wheelhouse, making its stock a buy.

In 2006, Alaska Sen. Ted Stevens famously oversimplified the internet as “a series of tubes.” That may have been a gross misunderstanding of what was cutting-edge technology at the time, but today a series of tubes, i.e., pipelines, are helping to power the latest advancements—to the benefit of their stocks.

Midstream operator Williams Cos., an energy middleman whose pipelines act as toll roads, handles roughly one-third of all the natural gas in the U.S. every day, connecting it from where it’s produced to where it’s used. It’s one of the latest beneficiaries of artificial intelligence, as the company helps to provide some of the juice that increasingly electricity-hungry data centers require. That demand, along with the broader growth in electricity needs in the U.S., means the company has a plausible line of sight to robust profits for years to come.

“Williams has articulated an expectation for potentially 10% earnings growth through the end of the decade and even beyond; eight to 10 years is sort of the time frame,” says Ben Cook, portfolio manager of the Hennessy Midstream fund, which owns the shares. “That’s not hard and fast guidance, but a company’s ability to project double-digit earnings growth into the end of the decade is pretty unique.”

Most analysts are on board, too. The consensus calls for Williams’ earnings per share to climb 12.5% this year to a record $2.36, followed by more than 7% next year. Likewise, Wall Street sees gross margins ballooning to over 80% for 2026, and then remaining in the high-70% range.

Not many companies can do what Williams does. It has created a “durable competitive moat rooted in regulatory and permitting complexity that is difficult to replicate,” says Ian Owens, associate portfolio manager at Bahl & Gaynor, which owns the shares. He cites assets like the Transcontinental Gas Pipe Line, which spans more than 10,000 miles over multiple states. “Fixed-fee contracts with investment-grade counterparties provide cash flow predictability, enabling the company to fund both shareholder returns and growth capex from contracted revenues,” Owens says.

Fixed-fee is another way of saying Williams gets paid for the use of its pipes whether or not natural gas is flowing through them. That means that unlike other energy companies, it’s less susceptible to commodity price swings, and it knows it has enough money coming in to cover necessary investments.

Some of those are around AI. The company has “a differentiated integrated power platform,” as Owens puts it, “which has positioned the company as the first mover” in on-site energy generation—sometimes called “behind-the-meter”—solutions for data centers. Big Tech companies like Facebook parent Meta Platforms, which works with Williams, are more than happy to pay for systems that allow them to bypass the grid and avoid problems like blackouts. The company’s data-center contracts can be a decade or longer in duration, adding some certainty to Williams’ income.

This week a group led by Blackstone said it would invest $5.34 billion in Williams to fund five major power-infrastructure projects, in exchange for a 49% noncontrolling equity interest in the projects. Overall, the company has a multibillion-dollar backlog spanning more than a dozen projects.

Cook notes that Williams’ triple-B investment-grade rating gives him confidence that its balance sheet and steady cash flows are adequate to cover the investments it’s making in the business. Nor, he says, do you have to be an AI believer, since export capacity for liquefied natural gas (LNG) is expected to roughly double in less than 10 years. (That growth comes after the U.S. went from almost zero LNG exports in 2016 to becoming the world’s largest supplier.)

Of course none of this has gone unnoticed, and Williams shares have gained about 25% year to date, easily ahead of the broader market and even the tech darlings tracked by the Roundhill Magnificent Seven ETF, which has underperformed since the start of 2026. The stock trades at a little under 30 times next year’s earnings.

Still, Williams can boast “sector-leading growth expectations” with minimal risk in terms of natural gas’s price—steady earnings power that many investors feel is worth paying up for, according to Owens. The stock has been a consistent winner as well, soaring some 170% over the past five years.

The company may have another catalyst if it acquires integrated natural-gas player Momentum Midstream from private-equity firm EnCap Flatrock Midstream. The “industrial logic for the acquisition is there as Haynesville represents a significant source of U.S. natural gas growth,” notes Truist analyst Gabe Daoud, who says the shares should trade to $84, corresponding to upside of about 12% from current prices, should the deal go through—depending on the financing details. Williams pays a dividend of 52 cents per share, or about 2.8%.

If investors think Williams has overpaid for any final deal, of course, they could sour on the shares. Likewise, although the stock is more insulated from natural-gas prices than other players, it’s not totally immune to them—and the same is true when it comes to the AI trade. Then there’s the fact that its valuation requires strong and consistent execution over time.

Yet Williams’ executives have been good stewards of capital in the past, as the company’s current balance sheet and capital position show. If the stock does sell off on debt-related concerns around a deal, the weakness would likely be temporary. And the long-term bull case for natural gas—for both regular power generation needs and AI projects—seems supportive of the commodity’s price.

“It’s a pretty straightforward story,” says Cook. “It’s one of the few companies with an irreplicable asset footprint in the U.S., a management team we think is navigating the current environment pretty well…and a strong balance sheet. That combination makes for an attractive investment.”

the software opportunities based on the Barron's piece (Adam Levine, July 17, 2026):

Thesis: AI is eating software's golden gross margins (70–90%) as agents and consumption-pricing erode seat-based subscriptions. Selling has stopped being indiscriminate — the market is now sorting winners from the buried. Hardware won first (PHLX Semis +108% YoY), but the profit eventually shifts up to the application layer.

ALREADY WINNING — AI tailwind, but pricey (fwd P/E 37–148x) The data + cyber names that AI needs. Own the proprietary-data and security layers that fuel agents.

THERE'S STILL HOPE — the actual value plays Cheap, deeply embedded incumbents that can adapt if leadership sacrifices margin and cuts S&M.

PERMANENTLY CHALLENGED — avoid No lock-in, disruptable by cheap AI. ADBE (a $70 Creative seat vs a $20 ChatGPT), DOCU, and point solutions ASAN / MNDY. CHEG (~$0.78) flagged as the market's first AI casualty.

Bottom line: Winners already priced richly; the real bargains sit in the "Still Hope" bucket — MSFT, SAP, CRM — where cheap multiples meet enough embeddedness to survive the transition.

AI is eating away at software’s superpower: profit-rich recurring revenue. The good news? Companies—and investors—are starting to adapt.

Over the past year, no industry has come under greater scrutiny than software. The once unstoppable cloud business model is facing new threats from artificial intelligence. Former highfliers like Salesforce and Adobe are being forced to prove their relevance. Their stocks get hammered with every rumor and announcement from AI labs. Despite a spring rebound, the closely followed iShares Expanded Tech-Software Sector exchange-traded fund is still down 15% over the past year.

But software isn’t going away, and there are companies that will survive and thrive through the AI transformation. After a year of mostly indiscriminate selling, investors are becoming more selective, recognizing there is nuance within software when it comes to AI.

So far, despite the shock of software’s selloff, the pattern that’s playing out is consistent with prior technology inflections, in which hardware wins first. We see that today in AI, with chips and cloud stocks soaring; The PHLX Semiconductor Index is up 108% in the past year.

This wave of spending also forces a trade-off: Higher capital expenditures on hardware means there’s less money available in IT budgets for software purchases. That reality came into sharp focus this past week when IBM released disappointing results that seemed to stun investors.

“In the last few weeks of June, we saw clients shift their quarterly capex spend toward servers, storage, and memory purchases to secure supply-constrained infrastructure ahead of expected price increases,” CEO Arvind Krishna said in a letter to shareholders.

Customers bought fewer IBM mainframe computers than anticipated, and less associated software. The stock fell 25% on the announcement. The good news is that other software stocks held tight—evidence of software’s next, more discriminating phase.

Eventually infrastructure—even the AI models themselves—will become commoditized and the so-called application layer, i.e., software, will take over in importance and profit. The process will take years, but some existing software players will be among the winners.

As investors make their peace with software’s future, they’ll need to rethink what software means in an AI-first world. Lots of AI-native start-ups have gotten a head start on doing exactly that. They’re unencumbered by legacy baggage, from existing sources of revenue to bloated costs and code. But technology disruption doesn’t entail wholesale replacement—see Walmart’s e-commerce success, Microsoft’s cloud prowess, and JPMorgan Chase’s fintech bona fides.

The Software Apocalypse

The cloud software model that emerged over the past two decades has been wildly successful. Its user-based subscriptions were a good deal for customers thanks to continuous software updates and lower internal IT expenses. It was an even better deal for the cloud providers themselves, which saw recurring revenue and big profits. The marginal cost to the vendor for each new user is low. Consequently, gross profit margin is very high—somewhere between 70% and 90%. For comparison, Apple, one of the best-run companies in the world, has gross margins below 50%.

In 2011, venture capitalist Marc Andreessen observed that “software is eating the world,” and he was right.

Through the 2010s, VC and private-credit investments flowed into the sector, eclipsing other industries. These software start-ups—many of which are now giant public companies—typically saw high sales growth, coupled with mounting free cash flow.

But AI has thrown a wrench into the machine, putting the outsize growth and cash generation at risk. Now it’s AI that’s eating software.

In the enterprise, AI’s earliest use case has been writing software, which is leading customers to make their own custom applications. In its latest earnings call, software company Palantir Technologies claimed it had replaced its customer-relations management vendor with an internally developed application. This may be a particularly appealing path for smaller companies that see large software packages as overkill.

But the bigger threat may be agents, which can use AI models to accomplish a complex series of tasks from a simple conversational prompt. Bots already outnumber people on the internet, and if trends continue, there will soon be far more agents on enterprise networks than humans. Machines replacing humans is a worst-case scenario for companies that charge by the person.

Moreover, as these agents continue to develop, they will begin to supplant more software functions, and make customers wonder why they are paying for subscriptions at all. The good news for tech investors is that software companies are already transitioning to hybrid sales models that include revenue based on AI consumption. The bad news is that consumption models carry a lower gross margin, depriving software of its profit-generating superpower.

Investors frequently talk about the “software industry” as a monolith tracked by a broad index like the iShares Expanded Tech-Software Sector ETF, which holds stocks in over 100 companies. But underneath the “software” rubric lies a lot of variability. For some software providers, the AI inflection is a boost for their business.

There are mountains of data that go into making AI models, but the key to effective implementation is the proprietary data that lives on enterprise networks. It’s what fuels agent work, and it can be used to refine AI models for bespoke purposes. Software companies that help AI work with data look to be winners.

Oracle and its industry-leading database software would be the primary example, but the company is busy transforming itself into a cloud giant, and that has overtaken the core software story. The cleaner story is Snowflake, which provides a platform for enterprises to warehouse their cloud data, and combines everything into “data lakes” that are ready for agents to use. Moreover, Snowflake already has a consumption-based revenue model and the lower gross margin that comes with it—66% for the latest one-year period.

Snowflake stock is up 88% in the past three months, as investors begin the process of differentiating software vendors.

Then there’s Palantir Technologies, perhaps the longest-running AI winner in software. The company makes structured data lakes for its customers, and builds custom applications on top of them. Despite some recent weakness for the stock, Palantir is bringing value to the data estates of enterprises. It’s offering the increasingly important operating layer that links people, AI models, and enterprise data. Its 84% gross margin shows software profits and AI aren’t incompatible.

Datadog is another example. The firm’s software allows customers to automate the monitoring of their information technology, which includes agents and other AI infrastructure. Like Palantir, Datadog avoids user-based pricing, and still gets an 80% gross margin.

AI also creates a favorable environment for cybersecurity companies because the technology enables traditional attacks to be carried out at a scale and speed that humans can’t match.

Enterprises are beginning to recognize the need for beefed-up protection. Last week, Microsoft used AI to patch more than 500 vulnerabilities to its own software, smashing the previous month’s record.

Most companies, though, will need help. CrowdStrike Holdings and Palo Alto Networks offer the broadest security platform and continue to make acquisitions to fill holes in their AI security portfolios. Their stocks are up 95% and 112%, respectively, over the past three months. They’ll continue to thrive as the AI threat grows.

Meanwhile, agents themselves have become an attack surface, with entirely new sorts of exploits, like prompt injections. It means enterprises will have to authenticate who—and what—they want running on their networks—and issue permissions and restrictions. That fits in with Okta’s wheelhouse. Its shares have risen 105% over the past three months.

The AI success for data and cyber companies comes with a trade-off for investors. The stocks are all pricey. Adjusting for share-based compensation, they trade at multiples of expected earnings ranging from 37 to 148.

Investors can find better deals elsewhere in software.

At the center of the software apocalypse are the full-featured cloud applications that still rely on the seat-based subscription model. This includes offerings from Microsoft, SAP, Salesforce, and other cloud natives like Atlassian, Workday, and ServiceNow. The stocks in this group are where investors can find the best value.

SAP trades at 18 estimated earnings for the next 12 months, well below the S&P 500 index’s multiple. At 20 times, Microsoft trades roughly in line with the large-cap index, after years of fetching a substantial premium. Salesforce has a forward price/earnings ratio of just 12, after starting the year at 20. In June, the stock was down 14 trading days in a row.

Executives at these firms will have to reread Clayton Christensen’s The Innovators’ Dilemma and Andy Grove’s Only the Paranoid Survive and live the lessons therein.

“Business success contains the seeds of its own destruction,” Grove wrote in his 1996 book.

AI is what Grove would have referred to as a “strategic inflection point,” which are “full-scale changes in the way business is conducted, so that simply adopting new technology or fighting the competition as you used to may be insufficient,” he said. “A strategic inflection point can be deadly when unattended to. Companies that begin a decline as a result of its changes rarely recover their previous greatness.”

The CEOs of these adapters have to rethink their value propositions and pricing models for this new world and be willing to sacrifice software’s golden gross margin. The offset will come from cutting operating expenses, especially in sales and marketing, typically the largest expense. Winners will be determined by strategy and flexibility, which in the end comes down to leadership. Business as usual won’t do.

The companies that have the best chance of success are the ones deeply embedded in their customers’ business processes, namely Microsoft and SAP. Much of the unique data produced by enterprises live inside Microsoft and SAP software, which remain crucial links between people and machines—not something AI will change. Their applications will be hard to dislodge, especially in government and highly regulated industries with strict requirements.

Microsoft also has AI servers for rent in the cloud and owns about a quarter of OpenAI, so it has other ways of offsetting losses in the company’s business software. SAP is less dependent on per-user licenses than other vendors, accounting for less than 40% of its sales, according to the company.

Salesforce, one of the first cloud software firms, is AI’s greatest wild card. Once the disrupter, it is now on the cutting table.

Salesforce seems willing to try anything, and disrupt everything. It has its own agents for sale under the Agentforce banner that deliberately cannibalize its own offerings. Annual recurring revenue for these agents remains relatively small, $1.2 billion at last count, but that has tripled from the year before. Salesforce had $43 billion in total sales in the past 12 months.

Salesforce has implemented more flexible pricing, combining subscriptions with consumption-based plans. It has been willing to put its apps into OpenAI’s ChatGPT, helping the start-up to get between Salesforce and its customers. It made an $8 billion acquisition of Informatica last year to bring itself closer to the data infrastructure group described above. Informatica provides $1.1 billion in annual recurring revenue at last count.

Maybe most dramatically, Salesforce has released a “headless” version of its software, with no human interface. It is meant for agents from any vendor to operate, cutting people out the picture entirely.

Salesforce is showing the kind of hustle that every software firm will need to survive in the AI age. It’s no guarantee of success, though—it’s the bare minimum. When Microsoft began preparing for the mobile revolution in the mid-1990s, it seemed to have every advantage—cash flow, technology, and strong brand recognition. It released mobile operating systems for the next two decades, and they were all failures. Windows was once the dominant operating system in the world; now it’s in third place behind Alphabet’s Android and Apple’s iOS.

“Coping with the relentless onslaught of technology change was akin to trying to climb a mudslide raging down a hill,” Christensen wrote in the Innovator’s Dilemma. “You have to scramble with everything you’ve got to stay on top of it, and if you ever once stop to catch your breath, you get buried.”

Some software companies are destined to get buried. Picking the ones that can adapt will be profitable for investors.

For some software makers, even hustle might not be enough. For companies in the creative field, AI represents unstoppable disruption. In the same way that software once revolutionized publishing and design, AI is changing the tools used by creative industries to make everything from Hollywood films to the fliers in bodega windows.

Unlike at Microsoft and SAP, Adobe’s customers aren’t locked in. They have other choices that are less expensive. One seat of Adobe Creative Suite costs $70 a month, much of which is now replaceable by a $20 ChatGPT account that can produce art at great scale and speed.

Adobe’s profitability demonstrates its many years of success and impressive pricing power. Its gross margin was 89% over the past 12 months. But AI changes the equation. On a five-designer team, four can now use AI. If only one buys Adobe’s software, Adobe’s take-home pay falls precipitously.

AI is making life difficult for other more focused software makers, as well. So-called point solutions like Asana, Monday.com, and Docusign make tailored software that solve a small set of problems. AI offers credible alternatives in each area. Homework help and educational site Chegg may be the best example. The firm identified the AI threat in 2023, shortly after ChatGPT’s initial launch. With a stock that now trades at 78 cents, Chegg may have been the market’s first AI casualty. It won’t be the last.

Software investors have focused on the frontier AI labs—primarily OpenAI and Anthropic—as the source of the threat, and with good reason. Though their cloud computing expenses are astronomical, sales are growing rapidly, and they’re likely to be public before long.

But we are already seeing a c onvergence in AI model capabilities, and there seems to be a new best product every few weeks. The top models from six different labs, including Chinese Zhipu AI, are clustered near the top of benchmark rankings. There is a range of pricing, with Zhipu and Elon Musk’s SpaceX charging much less than OpenAI and Anthropic. For the AI model makers, it isn’t a great sign to see pricing battles this early in their development.

Intelligence is destined to be commoditized, and that’s when software built on top of the models will begin to rise. Today’s AI is mostly about chatbots and coding agents, but it won’t stop there. A host of well-funded AI start-ups are rethinking what software means in the AI age, and in the end, they will be the biggest challenge to today’s incumbents.

**TTN Note: CONTEXT: The proposal appears to be the Trump administration’s revived framework for voluntary federal pre-release engagement with developers of powerful AI models, particularly where models could create cyber or national-security risks. Bessent’s role matters because Treasury has focused on spillovers to financial infrastructure and payment systems, widening AI policy beyond the usual technology and national-security agencies. The plan reportedly followed delays and industry pushback against an earlier version, making Bessent’s involvement a signal of stronger White House coordination rather than a purely advisory Treasury role. (washingtonpost.com)