US President Donald Trump has imposed a 50% tariff on a wide range of goods imported from Canada, in retaliation for what he called “unequal treatment” of US cars, dairy and alcohol.
The BBC spoke to Canadians in Montreal from across the country about their concerns over the new tariffs.
Airbus SE (EADSY) Discusses Business Updates and Outlook Across Key Segments July 21, 2026 12:30 PM EDT
Company Participants
Jean-Christophe Henoux – Head of Investor Relations & Financial Communication Guillaume Faury – CEO & Executive Director Thomas Toepfer – Chief Financial Officer Lars Wagner – Chief Executive Officer of Commercial Aircraft business Airbus Michael Schoellhorn – Chief Executive Officer Matthieu Louvot – Chief Executive Officer
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Conference Call Participants
David Perry – JPMorgan Chase & Co, Research Division Ross Law – Morgan Stanley, Research Division Douglas Harned – Bernstein Institutional Services LLC, Research Division Samuel Burgess – Goldman Sachs Group, Inc., Research Division Kenneth Herbert – RBC Capital Markets, Research Division Ian Douglas-Pennant – UBS Investment Bank, Research Division Chloe Lemarie – Jefferies LLC, Research Division Sash Tusa – Agency Partners LLP Charles Armitage – Citigroup Inc., Research Division Herve Drouet – CIC CIB, Research Division
Presentation
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Jean-Christophe Henoux Head of Investor Relations & Financial Communication
Good afternoon, ladies and gentlemen. Very warm welcome to the 2026 Airbus Business Update. It’s fantastic to see so many familiar faces in the room. On behalf of Airbus top management, we are delighted to host you today in London. This event is also broadcasted live. So good morning to the participants connected from the U.S. Good afternoon or good evening to all of us from around the world.
Before we start, let me go through a few practicalities and starting with safety first. We’ve talked to the hotel management earlier today, and there is no fire alarm test scheduled. So if you hear the fire alarm, please follow the staff towards the nearest exit and let’s assemble outside of the hotel in front of the main entrance.
I also kindly ask you to pay attention to the camera in case you walk around during the session because the event again is broadcasted. During the presentation, but also during the
Synergy has agreed to buy all the energy from Neoen’s Narrogin wind farm, in move which has paved the way for construction to begin on the massive renewable project.
Kaylee Hottle, a deaf actress best known for playing Jia in two “Godzilla” films, has died at age 18 following a car accident early Tuesday morning in Maryland, according to her father, Joshua Hottle, who confirmed her death to TMZ.
Joshua Hottle said his daughter was involved in a serious car accident, and that officials contacted him shortly afterward to inform him that her heart had stopped while she was being transported to the hospital. He shared the news of her death publicly in a nearly 23-minute social media livestream, during which he explained in American Sign Language that he needed to fly from Texas to Maryland to claim her body.
A rising star from a multi-generational deaf family
Hottle, an Atlanta, Georgia, native, came from a multi-generational deaf family and began her acting career in commercials as a young child. She first gained public attention at age 9 through a public service announcement for Glide, a live video messaging app widely used within the deaf and hard-of-hearing community.
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Breakout role in the Godzilla franchise
Hottle’s most prominent acting role came in 2021, when she portrayed Jia in “Godzilla vs. Kong,” playing a teenager who communicates with the giant ape King Kong through sign language while living on Skull Island alongside Rebecca Hall’s character, Dr. Ilene Andrews. The role introduced Hottle to a global audience and highlighted representation for deaf performers within a major Hollywood blockbuster franchise.
She went on to reprise the role of Jia in the franchise’s 2024 sequel, “Godzilla x Kong: The New Empire,” further establishing her presence within the long-running Monsterverse film series. Beyond her work in the Godzilla films, Hottle also appeared in the “Magnum P.I.” reboot series, playing a character named Joon in a Season 4 episode.
A short but meaningful career
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Hottle’s acting career, though brief given her young age, carried significant cultural weight, particularly within the deaf community, given the relative rarity of prominent deaf actors cast in major studio blockbuster films. Her portrayal of Jia was widely noted at the time of the film’s release for bringing authentic representation to a character whose primary mode of communication was sign language, a casting choice that resonated with audiences advocating for greater inclusion of deaf and hard-of-hearing performers in mainstream entertainment.
A family in mourning
In his emotional livestream following news of his daughter’s death, Joshua Hottle appeared visibly distraught as he relayed the circumstances surrounding the accident and his daughter’s passing to viewers, sharing the news directly with his and Kaylee’s broader community through American Sign Language given the family’s deep ties to the deaf community.
Part of a difficult stretch of entertainment industry losses
At just 18 years old, Hottle’s death marks a particularly tragic loss given the promise her early career had already demonstrated. Her performances in the Godzilla franchise placed her among a relatively small group of young deaf actors to achieve significant visibility in major studio productions, and her death has prompted an outpouring of grief from those following her career and her family’s public statements in the hours since the news broke.
Details regarding funeral or memorial arrangements for Hottle had not been publicly announced as of the time of this report. Her father indicated he was traveling to Maryland to claim her body following the accident, suggesting that additional information about services honoring her life and career may be shared by the family in the coming days. As news of her death continues to spread across social media and entertainment news outlets, tributes from fans, colleagues in the deaf community and others touched by her work in film and television are expected to continue in the days ahead, remembering Hottle both for her groundbreaking on-screen representation and for the promise of a career that ended far too soon.
Shares of Aehr Test Systems surged 25.70%, or $19.88, to $97.24 Tuesday, extending a remarkable rally that has seen the small-cap semiconductor testing company’s stock climb hundreds of percentage points this year on the strength of accelerating demand tied to artificial intelligence chip production.
Tuesday’s gains continue a volatile but overwhelmingly upward stretch for the stock following the company’s blowout fiscal fourth-quarter earnings report released July 14, which sent shares surging as much as 44% in a single session at the time, marking Aehr’s best single-day gain since July 2021. The stock has now climbed roughly 320% to 420% so far in 2026, depending on the measurement window, pushing the company’s market capitalization to approximately $2.7 billion.
A quarter that swung from loss to profit
Aehr’s fiscal 2026 fourth quarter, which ended May 29, delivered results that comfortably exceeded Wall Street expectations across nearly every key metric. The company reported net revenue of $18.8 million, up 33% year over year, alongside adjusted net income of $3.6 million, or $0.11 per share, a dramatic swing from a loss of $0.2 million, or $0.01 per share, in the same quarter a year earlier. Wall Street analysts had projected an adjusted loss of roughly $0.01 per share heading into the report, making the actual results a significant beat.
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Aehr, which manufactures machines used to test semiconductors under intense conditions in order to identify defects before chips reach production, saw record quarterly bookings of $60.7 million, more than five times the bookings recorded in the same quarter a year earlier. Including bookings that occurred after the quarter’s official close, the company’s effective backlog reached $100.6 million, giving Aehr substantial visibility into future revenue.
CEO points to accelerating AI-driven demand
Aehr CEO Gayn Erickson attributed the company’s strong results directly to surging demand tied to artificial intelligence applications. “Demand from AI-related applications continued to accelerate,” Erickson said following the earnings release.
Erickson also expressed confidence in the company’s broader multiyear growth trajectory. “With multiple customers entering or expanding production, a record backlog, and additional opportunities under discussion, we believe Aehr is well positioned for multiple years of strong revenue growth,” Erickson said.
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Aggressive growth guidance for the year ahead
Beyond the strong quarterly results, Aehr’s forward guidance for fiscal 2027 further fueled investor enthusiasm. Management projected revenue growth of 160% to 200%, targeting total revenue between $130 million and $150 million, dramatically above the roughly $85 million Wall Street had been forecasting heading into the report. The company also guided toward adjusted net margins of between 18% and 22% for the coming fiscal year, reflecting management’s expectation that improving operating leverage will continue translating into stronger profitability as revenue scales.
Company leadership specifically highlighted AI processors, silicon photonics and memory chips as key growth drivers expected to power continued demand for Aehr’s testing solutions in the year ahead.
Diversifying beyond AI into automotive and power semiconductors
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Beyond its core AI-related testing business, Aehr has continued expanding its footprint within the electric vehicle and power semiconductor markets. The company reported more than $8 million in new silicon carbide burn-in orders tied to electric vehicle programs in China, along with an order from a top global automaker, underscoring Aehr’s growing role supporting power semiconductor testing needs across the automotive sector.
Aehr has also continued receiving follow-on orders for its FOX-XP burn-in systems from customers in the silicon photonics space, directly tying the company to the broader boom in AI optical interconnect technology and hyperscale data center infrastructure buildouts. Additional follow-on orders from a major silicon photonics networking customer and a data center optical transceiver supplier were reported earlier this month, with deliveries from those orders expected within six months.
A stock defined by extreme volatility
Even amid its dramatic overall gains this year, Aehr’s stock has been characterized by exceptionally sharp day-to-day swings, a pattern common among smaller-cap companies closely tied to the broader AI infrastructure investment narrative. In the days surrounding its earnings report, shares moved as much as 34.23% higher in a single session, and later swung between an intraday high of $110.20 and a closing price of $87.79 on the same trading day, reflecting the kind of wide, fast-moving price action that has attracted significant attention from momentum-focused traders throughout the stock’s recent run.
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A balance sheet strengthened by a recent capital raise
Aehr’s financial position has also improved considerably in recent weeks, with the company reporting $116.5 million in cash following a recent equity raise, providing additional balance-sheet flexibility as it works to scale production capacity to meet its ambitious fiscal 2027 growth targets.
Despite the overwhelmingly positive recent trajectory, some caution has emerged around insider trading activity, with reports indicating that company insiders sold approximately $20.2 million worth of shares over the trailing three months, with no corresponding insider purchases reported during that same period, a dynamic some investors have flagged as worth monitoring even amid the stock’s dramatic rally.
With Aehr’s stock continuing to climb toward its June 15 record high of $126.62, investors are likely to continue closely watching for additional order announcements tied to AI processors, silicon photonics and power semiconductor testing demand as the company works to execute on its aggressive fiscal 2027 growth targets. Given the stock’s history of sharp, rapid price swings in both directions, Aehr is likely to remain one of the more closely watched high-volatility names within the broader AI infrastructure and semiconductor testing space in the weeks ahead.
Separate research from charity Christians Against Poverty found about 35% of adults in the UK worry about their finances every day.
As the VAT announcement will save households about £45 a year, “the fear of juggling budgets that simply don’t balance remains”, says Juliette Flachm, Acting Head of Policy and Public Affair.
“With incomes failing to keep pace with the high cost of essentials, many of the people we see are left facing impossible decisions.”
JRF’s chief economist Chris Belfield said: “Andy Burnham starts his time as prime minister at a time when the cost-of-living crisis has never been more widely felt.
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“Government policy can work. We need greater intervention to control rental prices, make energy affordable and improve the adequacy of Universal Credit so everyone can afford the essentials.”
A government spokesperson said: “We’re determined to turn the tide on poverty after years of rising hardship. Our recent statistics show that effort is beginning to make a difference – household incomes have risen 5% in real terms, food bank usage has fallen, and food insecurity is down.
“Work is underway to tackle the cost-of-living pressures through measures such as increasing the National Minimum Wage, removing the two-child limit, implementing the first ever sustained above inflation increase to Universal Credit, and launching the £1bn Crisis and Resilience Fund which will act as a genuine safety net for those in financial crisis.”
The figures come from the Joseph Rowntree Foundation’s poverty tracker, which surveys about 4,000 people from households in the lowest 40% of incomes.
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The charity noted that food inflation averaged 4.1% between May 2025 and May 2026, compared to 3.6% for overall inflation, which has greater impact on lower-income households because they spend more of their income on food.
But it also noted that the number of poorer households that couldn’t afford to keep their homes warm has fallen by half a million in two years, after the government reduced average household energy bills by about £150 a year through changes to green levies and support like the warm homes discount.
I know I said I’d likely stop writing these big letters, but I just couldn’t help myself this quarter. So much is happening, and I wanted to jot my thoughts down as much for myself as anything else. And also to crow about a big win we had.
Quickly on the returns. We had a big quarter, with YTD returns up to 15.91% vs 9.3% for the S&P (my main target benchmark) and 16.96% for the USRT (USRT) (again not really relevant comp these days but including for historical continuity). Since inception we are up to 236.3%, vs 181.29% for the S&P and 89.84% for the USRT. And we did it with no semiconductor exposure (and thus we have avoided the momentum bloodbath since Q2 ended), and a fairly good sized short book to boot.
I will lead with the star of the show this quarter, which was Uniqure (QURE), a stock I mentioned first in late 2025 I believe. As a reminder this is a biotech that has developed a promising treatment for Huntington’s disease, a relatively rare, 100% fatal neurodegenerative disease. It published results in September, the stock skyrocketed to ~$70, then in November the FDA changed tack on what seems to have been previously agreed to guidance accepting an external control group for an accelerated approval and the stock crashed down into the $20s (where I first bought). Then in March, the FDA fully refused to even consider Qure (QURE)’s accelerated application, saying Qure needed to run a full phase 3, and the stock crashed down to as low as $9/share, below cash balances.
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I doubled down near these lows, believing that if the drug worked (and no one really seems to think it doesn’t), that worst case you waited out the phase 3 (which Qure had cash to complete), and best case the FDA could change its mind either via personnel change, when additional data came out (they have year 4 data slated for September), or Qure could monetize via approvals abroad (which they are pursuing).
In an absolute whirlwind of a few months, the former FDA leadership was canned after what they did to Qure and several other promising disease treatments, and the new FDA interim leaders have allowed Qure to proceed with a filing for accelerated approval, with the stock now trading around $40s/share.
I will be honest and admit I didn’t think it would happen this quickly, but what a ride! Sadly for me I subscribe to some levels of risk/concentration management and sold some of my position after the initial pop from the lows around $10. But we still have a large position here. I was a bit worried about competition but after Roche (RHHBY) pulled its latest trial I am increasingly convinced that drugs which lower wild type Huntingtins protein across the whole brain or body, which essentially all the major competitors do, are problematic1. This then makes Qure’s approach of selective targeting of the striatum all the more strategic, and I think there is still significant upside from here if Qure can get full approval.
All that said, Qure is not our biggest position right now, that honor goes to Gitlab (GTLB), which has done quite well since we bought earlier this year.
Gitlab crashed significantly from fall of 2025 to today along with basically all other software businesses on a fear that LLMs would replace them all.
The basic thesis here is that as AI dramatically increases the velocity of code production, code control, review and approval (which Git sits at the center of), becomes even more critical than it ever was. The code repos also offer a very natural place to serve up coding agents – most easily visible in Microsoft (MSFT) pushing its Copilot agent through competitor Github.
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The growth is already visible in Gitlab’s usage, with code pushes up nearly 50% YoY. Gitlab doesn’t get paid on usage (yet)2, but its a really good sign when people are using your platform a lot more generally speaking.
I believe Gitlab is well positioned to monetize this growth itself, or that it would present an incredibly strategic acquisition opportunity for one of the major AI labs or companies. The market cap is a mere ~$5.5B (and $4.2 ev after cash), a drop in the bucket against the trillion dollar plus valuations in play elsewhere. Gitlab serves a whopping 50% of the F100, and would be a really valuable distribution tool. Microsoft already bought major competitor Git Hub, so there is precedent here as well. One of the firm’s trying to produce an AI model that is struggling with adoption I think would find a company like Gitlab very tempting, such as Meta (META) or SpaceX (SPCX).
Stepping back, the investment book feels about as good as it has since covid times, there are many interesting firms trading at attractive valuations, and I feel fairly good about returns continuing to be strong from here despite significant economic uncertainty.
Macro Musings
And speaking of uncertainty, I am growing more concerned about our two big macro risks, the reclosure of the Strait of Hormuz, and the AI boom. In order to keep this letter brief I won’t spend too much time on Hormuz – but if a deal is not reached soon and the strait remains closed it looks like oil inventories could hit crisis levels in 1-3 months. I suspect/hope something will get done as Trump seems to be aware of this, although unfortunately it may involve paying off Iran or conceding Iranian control of the strait, an effective strategic defeat for the US.
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The AI boom is a bit less binary, and therefore there is more to discuss. I believe the AI space is getting overheated, and as the scale has continued to ramp up I am worried that the impact of a bust is approaching a level that may cause a downturn.
The numbers involved here are absolutely staggering, and simply put, there does not appear to be any way that a reasonable return on the investment is earned barring the achievement of AGI within the next few years.
I have written about this several times before, but to repeat, at today’s level of investment (~$700 billion/year), there needs to be ~$1 trillion in end AI annual revenue (from the model cos / providers) by 2029, and that figure would ramp to nearly $4 trillion by 2036 assuming capex stays constant. Here is a link to a quick tweet summary of the math if you are interested3.
What is crazy to me is that many estimates have AI capex increasing significantly in 2027, and some even have it approaching $2 trillion by 2030! Obviously as the capex grows the required revenues also grow.
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The tech industry is simply not prepared for their formerly asset light, high margin golden children to turn into low margin commodity capital intensive industrial companies. Almost no one in the industry has the heuristics or experience for this. I cannot tell you how many times I see supposedly knowledgeable Silicon Valley people talking about inference gross margins with no reference to capital investment or D&A – this is like talking about the marginal cost of running an oil well but ignoring the cost to drill it! Or its like asking – ‘is building apartments profitable’, and someone responding ‘ yes, the rental operating margins are very high’. The answer is absolutely and completely irrelevant on its own without reference to a return on capital invested & the cost to build the apartments.
Amusingly, the one group of tech people who viscerally understand this, the management team’s of the memory companies (a business famous for its boom/bust cycles), have opted into a strategy that seems to capitalize on this knowledge by riding the wave and maximizing their own profits, damage to the overall ecosystem be damned. This is, I suspect, the optimal strategy here, although if they push too hard they may incentivize the hyperscalers to enter into the memory game as well. I rather liked my friend Andrew Walker’s observation relating to Micron (MU) and its total capital investment vs Google (GOOGL). Micron has only spent ~$125 billion in capex in its entire history (or at least since 1992, if ChatGPT is accurate). Or alternatively, its book value is $73 billion – this is perhaps a more realistic assessment of the current ‘replacement cost’, if you will. Google is going to spend $185 billion this year. How hard would it be for Google to spin up a memory division? Or Amazon (AMZN). Perhaps more likely is Apple (AAPL) or someone stands up a new player in China to secure and permanently commodify the memory supply chain so critical to their products.
Obviously such a thing would not be easy, but it would not be impossible, and if memory profits were to stay elevated it may happen. It also incentivizes chip designs and model utilization that would be less reliant upon memory as well – human ingenuity is a powerful thing, and I do not like betting against it long term.
More likely though I would guess the whole thing crashes down, and the memory executives know this is likely to occur before too many new entrants come into the space. They are also probably aware of China’s rapid ramp of memory capacity via the growth of CXMT (now almost as large as Micron in terms of capacity! ) & YMTC, and the likely terrible price wars and margin pressure to come in several years from China’s entry into this market. China has successfully commoditized every other electronics sector they have entered, and have moved up the value chain into autos. I don’t see why memory should be any different.
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How Much Longer
The big question is, how much longer can this AI capex boom last? It is hard to say, but I think the canary in the coal mine will be when model co revenues slow down. Given their epic growth thus far this year, it wouldn’t surprise me if this happens soon, but honestly I have no idea. It is notable that in the last few days we have seen the release of GPT 5.6, a new Meta Spark model, and Grok 4.5, and all 3 release put significant emphasis on their lower costs and price points. Not to mention a new open weights model out of China that is competitive with Fable and GPT 5.6 trained at what was supposedly a fraction of the cost.
These releases with an emphasis on cost mark a pretty big change from earlier releases which were really only focused on performance, and is potentially a dangerous sign of things to come for model providers.
It could even indicate that the model cos are seeing corporate users become price sensitive in real time, which would presage revenue growth beginning to slow down. Broadly speaking my read on the narrative is that frontier AI users are now actively working to rein in spend. However this may be counterbalanced or even overwhelmed by continuing diffusion throughout the broader corporate ecosystem. At some point though that diffusion completes and reality begins to set in.
A little rough AI generated summary of this concept – since diffusion is rapidly completing, the key unknown is where token intensity shakes out. It will peak or at least level off at some point, the question is simply when.
The adoption of AI in corporate America has been incredible – I don’t think any technology has ever diffused quite so quickly. McKinsey and BCG have some surveys on this subject – McKinsey estimates 88% of employees surveyed said their company was using AI, back in 2025. BCG had a survey with 72% of respondents (all corporate employees), saying they were regular AI users, over a year ago in June of 2025.4 We are likely approaching effective full employee diffusion, with recent revenue growth driven by more complex workflows and agent usage ((aka each user spending more)).
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This rapid diffusion has been great for AI revenues, but also means that the end of the adoption cycle is going to come much faster than previous technologies, and that the crash could be all the more violent because of how compressed the cycle is.
We will have to wait for the Q2 financial leaks to see the latest. But the model cos will need to approach $300-400B of revenues in a year, and ~$1 trillion by 2030, to justify all the AI capex investment. They are growing quite quickly today, but would need to accelerate further to hit these lofty targets.
If revenue growth slows and/or the capex spend slows down, it could well take down the entire US economy given the size of the AI sector in the public markets5, and how important public markets are as a percentage of household net worth today.
From Bloomberg and Barclays (BCS). Stocks are at an all time high as a percentage of HH networth.
The stock market is also near a record on the cyclically adjusted PE measure, second only to the dotcom bubble.
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CAPE) of US stocks from 1900 to 2026, highlighting extreme valuation peaks in the late 1920s, 2000, and 2020s compared to the long‑term mean.” contenteditable=”false” width=”936″ height=”657″ loading=”lazy” srcset=”https://static.seekingalpha.com/uploads/2026/7/21/saupload_73d77e1a7dec04ff4cc10aa8425a897c.png?io=w750 750w,https://static.seekingalpha.com/uploads/2026/7/21/saupload_73d77e1a7dec04ff4cc10aa8425a897c.png?io=w640 640w,https://static.seekingalpha.com/uploads/2026/7/21/saupload_73d77e1a7dec04ff4cc10aa8425a897c.png?io=w480 480w,https://static.seekingalpha.com/uploads/2026/7/21/saupload_73d77e1a7dec04ff4cc10aa8425a897c.png?io=w320 320w,https://static.seekingalpha.com/uploads/2026/7/21/saupload_73d77e1a7dec04ff4cc10aa8425a897c.png?io=w240 240w” sizes=”(max-width: 767px) calc(100vw – 36px), (max-width: 1023px) calc(100vw – 180px), 552px”>
The CAPE P/E uses inflation adjusted earnings over the last 10 years, in this way it can capture potential earnings bubbles and price bubbles. Today’s absolute P/E is not as high relative to prior figures, but the massive recent spike in earnings means the CAPE is much higher.
And setting aside the stock market, at this point a fairly large chunk of GDP is directly & indirectly tied to data center and power investments at this point. Even the automakers are re-orienting their battery operations around datacenters!
All that said, it is hard to predict with much certainty what is going to happen with the overall economy. While I am relatively confident the AI boom turns into a bust at some point, I do not know when, and I am not 100% sure it will cause a US recession, and even if it does it is very hard to know how bad that might be. Ideally it would be a shallow, concentrated one a la 2000.
There is some risk though of a broader, deeper crisis though, as one of the biggest differences this cycle is the asset & debt heavy nature of much of the investment, at least in the neocloud and datacenter space. Debt distress is much more likely to cause a longer, more painful crisis than equity. However much of this issuance appears to be backstopped by the still fairly good credit hyperscalers, so I am hopeful that a downturn wouldn’t lead to a full blown financial crisis (but I wouldn’t rule it out, especially the longer the boom goes!).
Fin
As always, thanks for reading. Despite the macro uncertainty I feel good about our portfolio, our stocks are quite cheap & may even benefit from a rotation out of momentum into value. And we have a significant short book that would hopefully offset a broader economic downturn.
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Stay safe out there.
Thanks for reading Warden Capital!
Hawkins Entrekin
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References
1 To get a bit further into the weeds but not quite all the way, regular huntingtins protein, or wtHTT, plays a critical role in other parts of the brain in particular, and there is good biological reason to believe that suppressing it across the brain could cause long term problems. My view here is supported by competitive trials which show a trend of higher dosage actually causing worse results, and more advanced patients doing worse, but promising results early in time and patient disease stage. That said this opinion is loosely held, there are still many unknown variables in all of these trials. But at the end of the day Qure’s AMT-130 is the only treatment which seems to show any real long term efficacy in slowing disease progression.
2 Technically this isn’t quite true, there are some ancillary services Gitlab charges per task on, but the vast majority of revenues are seat based for Gitlab. Gitlab’s new coding harness (which allows you to use any underlying model), does have usage based cost but its still a very small share of revenues.
3 The assumptions here are actually fairly conservative (to the benefit of semis bulls), when I dug a little deeper the math actually was much worse because the share of datacenter spend going to chips has continued to increase, which means the useful life estimate I had in there was overall too high. This means required revenues would actually be significantly larger. The main offset to this is that Google is a good sized share of the AI spend, and one could argue that their spending need not have an economic return. As Google faces an existential risk to its search business, and so their investment may simply be something they must do to preserve that business, even if it doesn’t actually generate much if any incremental new profits or revenues. The useful life estimates would add ~50% to the required revenues, while Google is about ~22-25% of total capex in the space, so crudely my figures here are a net ~25% conservative. So one year of current AI capex needs ~10 years of $400b / year in revenues to pay it back.
4 The same survey recently came out for 2026 but didn’t give a comparable all employee figure, instead breaking it down by position. But its like roughly the figure is now at 83-85% – there is not much growth left to be had here.
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5 I have seen estimates as high as close to 50% of the stock market. The AI trade has drawn in pretty much the entire utility sector and a large swath of even the industrials space as companies reorient their offerings around the data center boom.
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