I found GitHub repos­i­to­ries that were spread­ing mal­ware. I asked AI what to do about it, but it gave me noth­ing use­ful. So I opened a dis­cus­sion on GitHub. Someone replied. It was the ex­act same text the AI had given me. I called it out and the com­ment was deleted. Then an­other per­son replied. It was the same AI an­swer again.

I worked as a de­vel­oper at a com­pany. I asked the busi­ness owner a ques­tion about a busi­ness task. He sent me a ChatGPT screen­shot with the an­swer. I replied that it had noth­ing to do with my ques­tion and every­thing there was wrong. A minute later he sent me an­other ChatGPT screen­shot. He did­n’t even read the AI’s an­swer. He just took a screen­shot and for­warded it to me.

Recently some­one mes­saged me on Reddit about my post. I replied. They wrote again, I replied again. After a few mes­sages I re­al­ized I was talk­ing to an AI agent.

I’m tired of talk­ing to AI.I want to talk to real peo­ple.But even when I talk to peo­ple, they for­ward my ques­tions to AI and send me the AI’s an­swer.

I also pub­lish all new notes on Telegram and Bluesky.

These days, a typ­i­cal Google Search feels like an ob­sta­cle course. Type out ‘upcoming PC games 2026’ and your gaze has to swerve around a chunky AI overview which re­cy­cles the work of hu­man writ­ers in a bid to kneecap ef­forts to click away from Google. It’s a bleak state of af­fairs for what was once the pre­mier dis­cov­ery tool for the in­ter­net, and as such many users are look­ing for al­ter­na­tive search en­gines.

DuckDuckGo has been one ma­jor win­ner of this Google Search aban­don­ment. Just for a start, vis­its to its AI-free search page noai.duck­duckgo.com be­tween May 20 to May 25 are said to have in­creased by 22.7% on av­er­age week-on-week, with the fig­ures peak­ing May 24 at 27.7%.

The DuckDuckGo mo­bile app saw in­stalls spike in the US by 18.1% on av­er­age com­pared to the pre­vi­ous week. TechCrunch re­ported this growth was sus­tained over six days, peak­ing at 30.5% on May 25. An even greater num­ber of iOS users hit down­load on the app though, with in­stalls see­ing an av­er­age week-on-week growth of 33% and a peak of 69.9%.

This all fol­lows Google CEO Sundar Pichai claim­ing last week that, “People love [Search’s AI Mode].” DuckDuckGo CEO Gabriel Weinberg crit­i­cised Google’s all-in-on-AI ap­proach to Search, telling Paul Thurrott, “Google is force-feed­ing AI with no way to opt out. As a re­sult, their re­sults are get­ting worse, not bet­ter. We want to be the place that puts users in charge and al­lows them to de­cide how much or how lit­tle AI they want.”

To be clear, Google is­n’t about to lose its Search crown; DuckDuckGo rep­re­sents about 2% of the search en­gine mar­ket in the US—Google still en­joyed about 85% as of last month.

DuckDuckGo also of­fers AI prod­ucts such as duck.ai, which al­lows users to chat pri­vately with a num­ber of ma­jor LLMs such as GPT-5 mini and Claude Haiku 4.5. Given that Google re­ported its rev­enue from search grew by 19% dur­ing Q1 2026—apparently thanks to its “AI ex­pe­ri­ences like AI Mode and AI Overviews”—it would­n’t make much busi­ness sense for any com­pany to com­pletely ex­ile it­self from the AI in­dus­try at this mo­ment in time.

However, DuckDuckGo has en­deav­oured to pri­ori­tise user choice and pri­vacy. Weinberg said ear­lier this week, “Everything you do in DuckDuckGo is pri­vate, we don’t col­lect search his­to­ries or chats, and noth­ing is used for AI train­ing.”

Keep up to date with the most im­por­tant sto­ries and the best deals, as picked by the PC Gamer team.

According to chief com­mu­ni­ca­tions of­fi­cer Kamyl Bazbaz, DuckDuckGo’s own AI overviews re­main pop­u­lar—though so does the op­tion to fil­ter out AI-generated im­ages from search re­sults. He said, “People just want a choice.” Amen to that.

Jess has been writ­ing about games for over ten years, spend­ing a sig­nif­i­cant chunk of that time work­ing on print pub­li­ca­tions PLAY and Official PlayStation Magazine. When she’s not in­ves­ti­gat­ing all things hard­ware here, she’s ei­ther con­struct­ing a pas­sion­ate de­fence of a 7/10 game, day­dream­ing about her de­but novel, or feel­ing wist­ful about the last time she chased some nerds around a field with an over­sized foam sword.

Today, Last.fm be­gins a new chap­ter as an in­de­pen­dent com­pany. Ownership has changed,

but the prod­uct you use every day has not.

Your ac­count, your lis­ten­ing his­tory, and your data re­main ex­actly where they are. The team

build­ing Last.fm is the same. The ser­vice con­tin­ues as nor­mal.

What stays the same

Your Pro sub­scrip­tion and billing (if you’re a mem­ber)

The peo­ple be­hind the prod­uct

We’ll share more about what comes next in the weeks ahead. For now, every­thing works

ex­actly as it did yes­ter­day.

Same ser­vice. Same team. New chap­ter. Thanks for be­ing part of it.

Last.fm is now op­er­at­ing as an in­de­pen­dent com­pany fol­low­ing a change in own­er­ship.

No. The ser­vice con­tin­ues as nor­mal.

Is Last.fm be­ing ac­quired by an­other com­pany?

No. Last.fm is now op­er­at­ing in­de­pen­dently.

The team build­ing and op­er­at­ing Last.fm re­mains in place.

What does in­de­pen­dence mean for users?

It means we can fo­cus fully on build­ing lis­ten­ing in­sights and com­mu­nity fea­tures for mu­sic fans.

You’ll see con­tin­ued, steady im­prove­ments over time.

Is my ac­count or lis­ten­ing his­tory af­fected?

No. Your ac­count, scrob­bles, and lis­ten­ing his­tory re­main un­changed.

Yes. Your data and pri­vacy set­tings re­main un­changed. There is no change to how your data is

stored or pro­tected as a re­sult of this own­er­ship change.

No. There is no change to our ap­proach to data han­dling or pri­vacy as part of this tran­si­tion.

No. If you’re a Pro mem­ber, your sub­scrip­tion, billing, and ben­e­fits re­main the same.

There are no changes to pric­ing at this time.

I build tools us­ing the Last.fm API — should I be con­cerned?

No. API func­tion­al­ity con­tin­ues as nor­mal. We value the de­vel­oper com­mu­nity and will con­tinue

sup­port­ing the ecosys­tem around Last.fm.

If you’re a Pro mem­ber, thank you — your sub­scrip­tion di­rectly sup­ports the work we do. If

you’re not, you can learn more about Pro here: https://​www.last.fm/​pro

I never thought I’d see this hap­pen. So ex­cit­ing!

Congratulations to the team! Very ex­cit­ing

I wish the team all the best in go­ing for­ward on their own.

Congratulations and best of luck!

Wow, this is ex­cit­ing news! I can’t wait to see what’s ahead.

Congrats to the whole team! Can’t wait to see where the plat­form will go!

Are we get­ting the band back to­gether?

wow! that is bril­liant news! con­grats and look­ing for­ward to what’s com­ing!

Super happy to see this ex­cel­lent news! Can’t wait to see what hap­pens next!

Love to see it, con­grat­u­la­tions!

Now let’s undo the re­gion lock for Russian users.

yes!! bring back ra­dio that would be awe­some

And groups!! It would be so nice

27th May 2026

Anthropic are strongly ru­mored to be about to have their first prof­itable quar­ter. Stories are cir­cu­lat­ing of com­pa­nies sur­prised at how ex­pen­sive their LLM bills are be­com­ing from us­age by their staff. I think this is be­cause OpenAI and Anthropic have both found prod­uct-mar­ket fit.

Enterprise cus­tomers are now pay­ing API prices

I think they’ve found prod­uct-mar­ket fit

And they’re ramp­ing up

The AI-failure sto­ries around this are pretty thin

We also know the labs are spend­ing a lot

API rev­enue is be­com­ing less im­por­tant

April is a new in­flec­tion point

Enterprise cus­tomers are now pay­ing API prices

I cur­rently sub­scribe to the $100/month Max plan from Anthropic and the $100/month Pro plan from OpenAI. If you are a heavy user of cod­ing agents these plans are a fan­tas­tic deal. I just ran the ccusage tool on my lap­top to get an es­ti­mate of how much I would have spent if I were to pay for API to­kens in the past 30 days and got:

$1,199.79 for Anthropic Claude Code

$980.37 for OpenAI Codex

That’s $2,180.16 worth of to­kens for $200—not bad at all! I’m a mod­er­ately heavy user of these tools, but I’m cer­tainly not run­ning agents every hour of the day and night.

I had as­sumed that com­pa­nies mak­ing ex­ten­sive use of agents were get­ting sim­i­lar dis­counts. It turns out I could not have been more wrong about that.

I haven’t been able to track down the ex­act date, but at some point in the last six months Anthropic switched their Enterprise plan (originally “Claude seats in­clude enough us­age for a typ­i­cal work­day” back in August 2025) to $20/seat/month plus API pric­ing for us­age. This story about the change from The Information is dated Apr 14, 2026, but cites an Anthropic spokesper­son claim­ing that the pric­ing change oc­curred in November 2025. Existing cus­tomers are find­ing out about the change as they re­new their con­tracts.

OpenAI made a sim­i­lar pric­ing change in April. The Codex rate card (Internet Archive copy) cur­rently says:

Note: On April 2, 2026, we up­dated Codex pric­ing to align with API to­ken us­age, in­stead of per-mes­sage pric­ing. This change was ap­plic­a­ble to new and ex­ist­ing Plus, Pro, ChatGPT Business and new ChatGPT Enterprise plans. On April 23, 2026, we made this up­date for all ex­ist­ing ChatGPT Enterprise plans as well, in­clu­sive of Edu, Health, Gov, and ChatGPT for Teachers.

Note: On April 2, 2026, we up­dated Codex pric­ing to align with API to­ken us­age, in­stead of per-mes­sage pric­ing. This change was ap­plic­a­ble to new and ex­ist­ing Plus, Pro, ChatGPT Business and new ChatGPT Enterprise plans.

On April 23, 2026, we made this up­date for all ex­ist­ing ChatGPT Enterprise plans as well, in­clu­sive of Edu, Health, Gov, and ChatGPT for Teachers.

It’s a lit­tle harder to de­code as they quote prices in “credits”, but as far as I can tell those credit costs are an ex­act match for the API to­ken costs listed for those mod­els.

All of which is to say that as of April 2026 the “Enterprise” cost for both OpenAI Codex and Anthropic Claude Code/Cowork is the same as the listed API price.

GPT-5.5 (released April 23rd) is 2x the API price of GPT-5.4. Opus 4.7 (April 16th) is around 1.4x the price of Opus 4.6 when you take their new to­k­enizer into ac­count.

So April saw both lead­ing model com­pa­nies re­lease new fron­tier mod­els with a higher API price, and both com­pa­nies now have mea­sures to lock their en­ter­prise cus­tomers (who tend to sign year-long deals) at those API prices, not the pre­vi­ous ex­treme dis­counts.

I think they’ve found prod­uct-mar­ket fit

Why these sud­den ag­gres­sive moves on pric­ing? Both Anthropic and OpenAI are plan­ning to IPO, but I sus­pect there’s a more im­por­tant fac­tor here: I think they’ve fi­nally found prod­uct-mar­ket fit, with the cod­ing/​gen­eral-pur­pose agent prod­ucts em­bod­ied by Claude Code/Cowork and Codex.

Tools like ChatGPT are wildly pop­u­lar, but that wild pop­u­lar­ity has been dif­fi­cult to turn into rev­enue. In February OpenAI boasted more than 900 mil­lion weekly ac­tive users for ChatGPT, but only 50 mil­lion—5.6% of that—were pay­ing con­sumer sub­scribers.

Charging $10-$20/month per user is an OK busi­ness, but you’d need 1 – 2 bil­lion sub­scribers stick­ing around for four years to cover $1 tril­lion in in­fra­struc­ture.

Companies spend­ing $200+/month/user will get you there a whole lot faster—and as noted above, as a power-user I’m at ~$1,000/month in API costs per ven­dor al­ready.

Coding agents re­ally did change every­thing. These are tools which burn vastly more to­kens, but are also quickly be­com­ing daily dri­vers for the work car­ried out by ex­tremely well-com­pen­sated pro­fes­sion­als. Right now that’s still mostly soft­ware en­gi­neers, but a cod­ing agent is a tool that can au­to­mate any­thing you can do by typ­ing com­mands into a com­puter… so they are clearly ap­plic­a­ble to a much wider set of skilled knowl­edge work­ers.

As I’ve dis­cussed on this site at length, the mod­els re­leased in November 2025 el­e­vated agents to be­ing gen­uinely use­ful. We’ve had six months to get used to that idea now—it’s no won­der com­pa­nies are be­gin­ning to spend real money on this tech­nol­ogy.

You could ar­gue that ChatGPT achieved prod­uct-mar­ket fit when it be­came the fastest-grow­ing con­sumer app in his­tory back in February 2023… but it cer­tainly was­n’t mak­ing any ac­tual money back then. Coding agents plus en­ter­prise pric­ing marks the point when these com­pa­nies start mak­ing very real rev­enue. Maybe even enough to start cov­er­ing their costs!

And they’re ramp­ing up

As fur­ther ev­i­dence that en­ter­prise agents rep­re­sent prod­uct-mar­ket fit for these com­pa­nies, con­sider their open job list­ings.

OpenAI have 703 open jobs right now, of which I’d cat­e­go­rize 229 (32.6%) as re­lat­ing to en­ter­prise sales and sup­port—ac­count ex­ec­u­tives, “Go To Market”, “Forward Deployed Engineers” and the like.

Anthropic have 390 open jobs, 105 (26.9%) of which look en­ter­prisey to me.

It’s pleas­ingly ironic that these AI labs have picked a busi­ness model with such a heavy de­mand on hu­man la­bor—en­ter­prise sales con­tracts don’t close them­selves with­out a whole lot of hu­mans in the mix!

(I ran this analy­sis by scrap­ing their job sites with Claude Code, then hav­ing it use Datasette’s JSON API to pipe that data into Datasette Cloud where I used Datasette Agent for the analy­sis, ex­ported here. Dogfood!)

The AI-failure sto­ries around this are pretty thin

I started dig­ging into this in re­sponse to a grow­ing vol­ume of sto­ries claim­ing that large com­pa­nies were sound­ing the alarm be­cause their AI us­age costs had grown so large.

The most widely cited of these sto­ries ap­pear quite overblown to me.

The most dis­cussed has been Uber, based on this re­port where CTO Praveen Neppalli Naga in­di­cated that Uber had “maxed out its full year AI bud­get just a few months into 2026”, mostly thanks to Claude Code.

Given that Claude Code only got re­ally good in November it’s en­tirely un­sur­pris­ing to me that a bud­get set in 2025 may have failed to pre­dict de­mand for that tool in 2026!

That Uber story was fur­ther fu­eled by com­ments made by Uber’s COO, Andrew Macdonald, on the Rapid Response pod­cast. I tracked down the seg­ment and there re­ally is­n’t much there. Here’s what Andrew said:

But then you some­times go and talk to your se­nior en­gi­neer­ing lead­ers and you’re say­ing, OK, how many pro­jects that were on the cut­ting room floor got moved above the line be­cause of the pro­duc­tiv­ity gains be­cause 25% of our code com­mits were via Claude Code last quar­ter? That link is not there yet, right? I think maybe im­plic­itly there’s more that is get­ting shipped. But it’s very hard to draw a line be­tween one of those stats and, OK, now we’re ac­tu­ally pro­duc­ing like 25% more use­ful con­sumer fea­tures, right? And that line is hard to draw.

But then you some­times go and talk to your se­nior en­gi­neer­ing lead­ers and you’re say­ing, OK, how many pro­jects that were on the cut­ting room floor got moved above the line be­cause of the pro­duc­tiv­ity gains be­cause 25% of our code com­mits were via Claude Code last quar­ter?

That link is not there yet, right? I think maybe im­plic­itly there’s more that is get­ting shipped. But it’s very hard to draw a line be­tween one of those stats and, OK, now we’re ac­tu­ally pro­duc­ing like 25% more use­ful con­sumer fea­tures, right? And that line is hard to draw.

Somehow this frag­ment turned into head­lines like Uber’s COO says it’s get­ting harder to jus­tify the money spent on AI to­ken­maxxing, be­cause the mar­ket for sto­ries about AI fail­ures re­mains enor­mous.

The other pop­u­lar story around this is Microsoft starts can­cel­ing Claude Code li­censes, os­ten­si­bly to en­cour­age their en­gi­neers to dog­food their own Copilot CLI agent in­stead—but The Verge re­porter Tom Warren says “sources tell me the de­ci­sion is also a fi­nan­cial one”, trig­gered by the June 30th end of Microsoft’s fi­nan­cial year.

I think both of these sto­ries sup­port my “product-market fit” hy­poth­e­sis. The best ad­vice I ever heard on pric­ing a prod­uct was that your cus­tomer should suck air through their teeth and then say yes. Uber’s bud­get over­run and Microsoft’s seat can­cel­la­tions look like that ef­fect play­ing out in prac­tice.

We also know the labs are spend­ing a lot

The big AI labs spend bil­lions of dol­lars on both train­ing and in­fer­ence. Credible fig­ures are hard to come by, but we did get one huge hint as to the fig­ures in­volved from, oddly enough, the re­cent SpaceX S-1:

[…] in May 2026, we en­tered into Cloud Services Agreements with Anthropic PBC (“Anthropic”), an AI re­search and de­vel­op­ment pub­lic ben­e­fit cor­po­ra­tion, with re­spect to ac­cess to com­pute ca­pac­ity across COLOSSUS and COLOSSUS II. Pursuant to these agree­ments, the cus­tomer has agreed to pay us $1.25 bil­lion per month through May 2029 […]

[…] in May 2026, we en­tered into Cloud Services Agreements with Anthropic PBC (“Anthropic”), an AI re­search and de­vel­op­ment pub­lic ben­e­fit cor­po­ra­tion, with re­spect to ac­cess to com­pute ca­pac­ity across COLOSSUS and COLOSSUS II. Pursuant to these agree­ments, the cus­tomer has agreed to pay us $1.25 bil­lion per month through May 2029 […]

The Anthropic an­nounce­ment said that this deal meant they could “increase our us­age lim­its for Claude Code and the Claude API”, heav­ily im­ply­ing that Colossus is be­ing used for in­fer­ence, not model train­ing.

Anthropic al­ready have vast amounts of com­pute from other providers. The fact that they’re will­ing to spend $1.25 bil­lion per month for ex­tra ca­pac­ity from just one of their ven­dors hints at how big these in­fer­ence bud­gets have be­come.

API rev­enue is be­com­ing less im­por­tant

Over the past two years my im­pres­sion has been that OpenAI made more of their in­come from sub­scrip­tion rev­enue while Anthropic made more from their API.

Anthropic’s API rev­enue was his­tor­i­cally quite de­pen­dent on a small num­ber of large API cus­tomers—this VentureBeat story from August 2025 quotes “sources fa­mil­iar with the mat­ter” sug­gest­ing that just Cursor and GitHub Copilot were re­spon­si­ble for $1.2 bil­lion of the com­pa­ny’s then-$4 bil­lion rev­enue.

Today Anthropic are ru­mored to hit $10.9 bil­lion in the sec­ond quar­ter, po­ten­tially even op­er­at­ing at a profit for the first time.

This pivot-to-En­ter­prise sug­gests that the labs have re­al­ized that the real money lies in cut­ting out the mid­dle­men. Anthropic’s Claude Code di­rectly com­petes with Cursor and Copilot. No won­der Cursor are in­vest­ing in their own mod­els!

April is a new in­flec­tion point

I’ve called November 2025 the November in­flec­tion point be­cause that was when GPT-5.1 and Opus 4.5, com­bined with their re­spec­tive cod­ing agent har­nesses, got good—good enough that we’ve spent the last six months adapt­ing to agent sys­tems that can re­li­ably get use­ful work done.

I think April 2026 is a new in­flec­tion point where the rev­enue im­pli­ca­tions of this have started to land, to the ben­e­fit of the fron­tier AI labs and with ma­te­r­ial im­pacts on the bud­gets of large com­pa­nies.

We’ll know for sure how real this mo­ment is when the S-1 doc­u­ments for the up­com­ing Anthropic and OpenAI IPOs give us some real, au­dited num­bers to get our teeth into.

There is a cer­tain wild­ness in the tech in­dus­try these days that both mim­ics pre­vi­ous eras of large changes, like cloud com­put­ing (runaway costs in the early days), and is like noth­ing we’ve ever seen be­fore (record rev­enues ac­com­pa­nied by mass lay­offs).

One pos­si­ble ex­pla­na­tion: Tech ex­ec­u­tives, es­pe­cially CEOs, are col­lec­tively suf­fer­ing from delu­sions of AI grandeur. And at least one tech CEO has said as much out loud: Box founder Aaron Levie.

“CEOs are uniquely prone to AI psy­chosis be­cause they’re suf­fi­ciently dis­tant from the last mile of work that still has to hap­pen to gen­er­ate most value with AI,” Levie wrote on X.

CEOs “play with AI,” de­velop a pro­to­type, or gen­er­ate a con­tract, to use Levie’s ex­am­ples, and then make the leap to be­liev­ing agents can do the work.

But these top-level ex­ec­u­tives aren’t the peo­ple who have to re­view code, dis­cover bugs, and iden­tify calls to hal­lu­ci­nated li­braries be­fore soft­ware is de­ployed. They aren’t re­spon­si­ble for train­ing AI mod­els on a com­pa­ny’s idio­syn­cratic con­tract terms, nor do they have to spend days comb­ing through con­tracts to find sneaky terms, as Levie in­di­cates.

In other words, Levie’s the­ory posits, CEOs don’t re­ally un­der­stand processes well enough to know what re­ally can and can’t be au­to­mated. But that lack of knowl­edge does­n’t stop them from act­ing on their be­liefs.

It’s im­por­tant to note that Levie is not an AI hater. Quite the op­po­site. He mostly posts AI pos­i­tiv­ity on X to his 2.7 mil­lion fol­low­ers, writ­ing blogs ti­tled “Headless soft­ware is the fu­ture” on how soft­ware built for AI agents is the way for­ward. He also puts his money where his mouth is, back­ing AI star­tups as an ac­tive an­gel in­vestor.

So what are CEOs to do in­stead? Levie ad­vises CEOs to use AI “a ton” to re­ally see what it can and can’t do, “and come out the other side with an ap­pre­ci­a­tion for both the up­side and the real work.”

CEOs are uniquely prone to AI psy­chosis be­cause they’re suf­fi­ciently dis­tant from the last mile of work that still has to hap­pen to gen­er­ate most value with AI.So when they play with AI, they see the happy path re­sults, of­ten not con­sid­er­ing the next 10 or 20 things that have… https://​t.co/​ne5mvJ4Rgx— Aaron Levie (@levie) May 24, 2026

CEOs are uniquely prone to AI psy­chosis be­cause they’re suf­fi­ciently dis­tant from the last mile of work that still has to hap­pen to gen­er­ate most value with AI.

So when they play with AI, they see the happy path re­sults, of­ten not con­sid­er­ing the next 10 or 20 things that have… https://​t.co/​ne5mvJ4Rgx

I have enough faith in hu­man­ity to be­lieve that there are CEOs out there at­tempt­ing to do just that, but right now, they seem to be in the mi­nor­ity.

In just the first five months of 2026, the tech in­dus­try has had nearly as many lay­offs as in all of 2025: 115,430 peo­ple have been fired from 152 tech com­pa­nies so far in 2026, com­pared to 124,636 peo­ple let go by 275 com­pa­nies in 2025, ac­cord­ing to in­dus­try lay­off tracker Layoffs.fyi.

And the bulk of com­pa­nies have pointed to AI as a rea­son for cut­ting these jobs. Many ar­gue that the biggest tech com­pa­nies are AI wash­ing, or cred­it­ing AI pro­duc­tiv­ity gains in the past or fu­ture, when other busi­ness de­ci­sions and met­rics are re­ally dri­ving the cuts.

Still, some of these sto­ries are sur­pris­ing. Zeb Evans, the CEO of pro­ject man­age­ment and pro­duc­tiv­ity soft­ware startup ClickUp, proudly de­clared on X that he had laid off al­most a quar­ter of his em­ploy­ees — 22% — af­ter rolling out about 3,000 AI agents to do in­ter­nal work.

Evans swore this was­n’t done to re­duce costs. Instead, he wants a work­force com­posed of peo­ple who run AI agents and spend their days quickly re­view­ing the agents’ work. He be­lieves this will cre­ate a “100x org,” as he calls it.

While AI can be a very use­ful tool, the data on AI and pro­duc­tiv­ity does­n’t sup­port such as­sump­tions. By miles.

A meta-analy­sis of other re­search pub­lished in October in UC Berkeley’s California Management Review found “no ro­bust re­la­tion­ship be­tween AI adop­tion and ag­gre­gate pro­duc­tiv­ity gain.”

Research pub­lished in March by the National Bureau of Economic Research did con­clude that AI adop­tion im­proved pro­duc­tiv­ity but noted “a pro­duc­tiv­ity para­dox, in which per­ceived pro­duc­tiv­ity gains are larger than mea­sured pro­duc­tiv­ity gains.”

After cre­at­ing thou­sands of agents to work on tasks, re­searchers at MIT con­cluded that agents just aren’t do­ing hu­man-qual­ity work yet in many cases. They pre­dict at the cur­rent rate of LLM im­prove­ment, mod­els will “be able to com­plete most text-re­lated tasks with suc­cess rates of, on av­er­age, 80%–95% by 2029 at a min­i­mally suf­fi­cient qual­ity level.”

In other words, AI is on track to per­form at base com­pe­tence on most tasks in about three years. These re­searchers be­lieve agents will need an­other few years to out­per­form hu­mans.

Meanwhile, re­search pub­lished in the Harvard Business Review showed that when every­one is us­ing AI to pro­duce more stuff, the bot­tle­neck sim­ply shifts to ex­ec­u­tives. Their work awaits the peo­ple who must au­tho­rize all the stuff every­one is pro­duc­ing. If every­one is em­pow­ered to act, then from what OpenAI ex­pe­ri­enced last year, we can tell that things may get out of con­trol.

Are CEOs ready for that? If not, the most cer­tain out­come of the on­go­ing CEO AI psy­chosis will sim­ply be or­ga­ni­za­tional chaos.

When you pur­chase through links in our ar­ti­cles, we may earn a small com­mis­sion. This does­n’t af­fect our ed­i­to­r­ial in­de­pen­dence.

Is that YouTube video clip you’re watch­ing real or was it made with AI?

YouTube wants to make it eas­ier for view­ers to know when con­tent on its plat­form is AI-generated. In 2024, it started la­bel­ing con­tent when cre­ators dis­closed they have used AI tools. Now YouTube is mak­ing AI-generated con­tent la­bels more promi­nent for view­ers — and it’s go­ing to start au­to­mat­i­cally ap­ply­ing the la­bels if it de­tects that a video in­cludes “significant pho­to­re­al­is­tic AI use.”

“We’ve heard con­sis­tently from our com­mu­nity that they value trans­parency when it comes to gen­er­a­tive AI con­tent,” YouTube said in a blog post Wednesday an­nounc­ing the up­dates. “These changes are de­signed to bal­ance trans­parency with cre­ator con­trol.”

Under YouTube’s guide­lines, cre­ators will still be re­quired to man­u­ally dis­close when they use re­al­is­tic AI. But start­ing this week, it also will roll out a new in­ter­nal sys­tem to help iden­tify AI-generated con­tent. “If a cre­ator does­n’t spec­ify whether or not they used AI, but our sys­tems de­tect sig­nif­i­cant pho­to­re­al­is­tic AI use, we will now au­to­mat­i­cally ap­ply a la­bel,” YouTube said.

YouTube cre­ators who be­lieve their con­tent was in­cor­rectly flagged as AI-generated can mod­ify the dis­clo­sure sta­tus us­ing the YouTube Studio tool. However, ac­cord­ing to YouTube, the AI la­bels will “remain per­ma­nent” in some cases, in­clud­ing for con­tent cre­ated us­ing YouTube’s own AI tools (such as Veo or Dream Screen) and for con­tent that con­tains C2PA meta­data (based on stan­dards from the Coalition for Content Provenance and Authenticity) that in­di­cates it was fully AI-generated.

In ad­di­tion, YouTube is mov­ing the dis­clo­sure la­bel for pho­to­re­al­is­tic and mean­ing­fully AI-altered or AI-generated con­tent to a more promi­nent po­si­tion. Until now, YouTube la­beled AI con­tent in a video’s ex­panded de­scrip­tion. Going for­ward, for long-form videos, the AI la­bel will now ap­pear di­rectly be­low the video player and above the de­scrip­tion. For YouTube Shorts, the la­bel will ap­pear as an over­lay on the video it­self.

YouTube re­leased im­ages show­ing where the new la­bels will ap­pear:

“The goal here is con­text at a glance. If it looks real but was made with AI, view­ers will know im­me­di­ately,” Rene Ritchie, YouTube head of ed­i­to­r­ial and cre­ator li­ai­son, says in a video about the changes. He added that the AI la­bels alone “do not af­fect how our videos are rec­om­mended or whether they can earn money. This is purely about giv­ing view­ers the right in­for­ma­tion at the right time.”

Meanwhile, for con­tent that YouTube de­ter­mines is “unrealistic, an­i­mated or slightly al­tered” (but not fully AI-generated), dis­clo­sures will con­tinue to ap­pear in the ex­panded de­scrip­tion sec­tion.

The up­dates come af­ter YouTube ear­lier this month ex­panded its like­ness-de­tec­tion pro­gram to all cre­ators (18 and older). That’s de­signed to help users “detect and man­age how AI is used to de­pict you on YouTube.” For cre­ators who en­roll in the pro­gram, YouTube’s sys­tems will iden­tify videos that may be al­tered or syn­thetic uses of their fa­cial like­ness; they can then re­quest re­moval of “unauthorized con­tent that uses your like­ness di­rectly in YouTube Studio.”

May 27, 2026

[[read-time]] minute read

We’ve heard con­sis­tently from our com­mu­nity that they value trans­parency when it comes to gen­er­a­tive AI con­tent. That’s why since 2024, we’ve been la­bel­ing con­tent when cre­ators dis­close they’ve used AI tools.

We’ve learned in that time about what peo­ple find use­ful when it comes to AI dis­clo­sures, and to­day we’re mak­ing two up­dates that we think will make this process much sim­pler and more in­tu­itive for cre­ators and view­ers on YouTube.

More vis­i­ble, sim­pli­fied la­bels

We’re mov­ing the dis­clo­sure la­bel for pho­to­re­al­is­tic and mean­ing­fully AI al­tered or gen­er­ated con­tent to a more promi­nent po­si­tion.

For Long-form Videos: The la­bel will now ap­pear di­rectly be­low the video player, above the de­scrip­tion.

For Shorts: The la­bel will ap­pear as an over­lay on the video it­self.

By mov­ing these la­bels on to the main stage, view­ers get the con­text they need at a glance. This is now the sin­gle la­bel for­mat for all pho­to­re­al­is­tic and mean­ing­fully AI al­tered or gen­er­ated con­tent on YouTube.

For con­tent that is un­re­al­is­tic, an­i­mated, or slightly al­tered, view­ers can find this dis­clo­sure in the ex­panded de­scrip­tion.

AI us­age dis­clo­sure at video up­load time.

Introducing au­to­matic AI de­tec­tion

While we still re­quire cre­ators to man­u­ally dis­close when they use re­al­is­tic AI, we want to make the process more seam­less and re­li­able. Starting in May 2026, we’re rolling out new in­ter­nal sig­nals to help iden­tify AI-generated con­tent.

If a cre­ator does­n’t spec­ify whether or not they used AI, but our sys­tems de­tect sig­nif­i­cant pho­to­re­al­is­tic AI use, we will now au­to­mat­i­cally ap­ply a la­bel.

As this tech­nol­ogy con­tin­ues to im­prove, cre­ators re­main in con­trol. If a cre­ator thinks their con­tent was in­cor­rectly iden­ti­fied as AI-generated, they can up­date the dis­clo­sure sta­tus in YouTube Studio. However, dis­clo­sures will re­main per­ma­nent in a hand­ful of cases, in­clud­ing:

Content cre­ated us­ing YouTube’s own AI tools, like Veo or Dream Screen.

Content con­tain­ing C2PA meta­data in­di­cat­ing they were fully gen­er­a­tive AI.

Our com­mit­ment to re­spon­si­bil­ity

These changes are de­signed to bal­ance trans­parency with cre­ator con­trol. It’s im­por­tant to note that a dis­clo­sure la­bel alone does not change how a video is rec­om­mended or whether it’s el­i­gi­ble to earn money. In a world where AI is chang­ing what’s pos­si­ble, our goal is sim­ple: make it as easy as pos­si­ble for cre­ators and view­ers to have the right in­for­ma­tion.

When a fire truck fails to de­ploy in a burn­ing build­ing and four peo­ple die, the cause is­n’t just me­chan­i­cal fail­ure. It’s a busi­ness model.

On the night of June 26, 2025, fire­fight­ers on Tower Ladder 14 raced to a Chicago apart­ment build­ing where an ar­son­ist had poured gaso­line on both stair­wells. When they ar­rived, the aer­ial lad­der would not go up. The crew had to shut the rig off en­tirely and restart it. The de­lay lasted ap­prox­i­mately one minute. Four peo­ple died that night — in­clud­ing a preg­nant woman, her five-year-old son, and her sis­ter, who threw her own child from a third-floor win­dow be­fore per­ish­ing her­self.

Nobody told the sur­viv­ing fam­ily about the lad­der mal­func­tion. They found out from jour­nal­ists.

That mal­func­tion­ing truck is a thread. Pull it, and what un­rav­els is one of the clear­est il­lus­tra­tions of how pri­vate eq­uity — the $9.4 tril­lion in­dus­try that qui­etly con­trols roughly 11,500 American com­pa­nies and 11 mil­lion jobs — turns es­sen­tial pub­lic in­fra­struc­ture into profit ex­trac­tion ma­chines, of­ten at lethal cost.

The Business Model: Brilliant for Investors, Brutal for Everyone Else

Private eq­uity is not a mys­tery. The me­chan­ics are straight­for­ward, the in­cen­tives are trans­par­ent, and the out­comes are pre­dictable once you un­der­stand how the ma­chine works.

A pri­vate eq­uity firm raises a fund — typ­i­cally from pen­sion funds, sov­er­eign wealth funds, en­dow­ments, and wealthy in­di­vid­u­als. It then ac­quires com­pa­nies, usu­ally through a lever­aged buy­out (LBO): a struc­ture where 50 to 90 per­cent of the pur­chase price is fi­nanced by debt, and that debt is loaded onto the bal­ance sheet of the ac­quired com­pany, not the firm mak­ing the ac­qui­si­tion. The firm then charges the fund a man­age­ment fee — his­tor­i­cally 2 per­cent of as­sets an­nu­ally — plus car­ried in­ter­est: a 20 per­cent cut of any prof­its, taxed at the long-term cap­i­tal gains rate of 20 per­cent rather than the or­di­nary in­come rate of 37 per­cent. Critics have long called this a tax loop­hole. Congress has de­bated clos­ing it for two decades and has not.

US pri­vate eq­uity AUM reached $3.128 tril­lion in 2024 alone, ac­cord­ing to S&P Global. Total pri­vate mar­kets AUM glob­ally sits at ap­prox­i­mately $15 tril­lion.

The model works when ap­plied to un­der­per­form­ing busi­nesses that gen­uinely need re­struc­tur­ing. PE firms can bring op­er­a­tional dis­ci­pline, growth cap­i­tal, and strate­gic fo­cus. That is the af­fir­ma­tive case, and it is real.

The prob­lem emerges when the model is ap­plied to es­sen­tial ser­vices with in­elas­tic de­mand — in­dus­tries where the cus­tomer has no choice but to pay, where qual­ity degra­da­tion is hard to mea­sure un­til cat­a­stro­phe strikes, and where the typ­i­cal PE time­line of 3-to-7 years be­fore exit cre­ates in­cen­tives to strip value rather than build it.

The Senate Joint Economic Committee’s July 2024 re­port de­scribed this as a “buy, strip and flip” busi­ness model: PE firms load ac­quired com­pa­nies with debt, cut costs ag­gres­sively, then re­sell at a profit — of­ten at the di­rect ex­pense of work­ers, com­mu­ni­ties, and the ser­vices those com­pa­nies pro­vide. Public com­pa­nies ac­quired by PE are ap­prox­i­mately ten times more likely to go bank­rupt than a com­pa­ra­ble con­trol group sub­ject to the same mar­ket forces, the re­port found.

The Fire Truck Racket: A Case Study in Manufactured Scarcity

The fire truck in­dus­try is the sharpest and most doc­u­mented ex­am­ple of what PE con­sol­i­da­tion does to es­sen­tial ser­vices.

Two decades ago, more than two dozen in­de­pen­dent man­u­fac­tur­ers com­peted to build America’s fire ap­pa­ra­tus. Today, three com­pa­nies con­trol ap­prox­i­mately 80 per­cent of the mar­ket: REV Group, Pierce Manufacturing (owned by Oshkosh Corporation), and Rosenbauer. This con­cen­tra­tion was not an ac­ci­dent of mar­ket forces. It was en­gi­neered.

REV Group is the cen­tre­piece of the story. The com­pany — owned by pri­vate eq­uity firm American Industrial Partners — sys­tem­at­i­cally ac­quired for­merly in­de­pen­dent man­u­fac­tur­ers in­clud­ing E-One, Ferrara, KME, Ladder Tower, and Spartan. The old name­plates still ex­ist as brand names. But be­hind them sits a sin­gle PE-backed con­glom­er­ate con­trol­ling a mas­sive share of the sup­ply chain for emer­gency ve­hi­cles that every American city de­pends on.

The re­sult is a back­log that reads like a fi­nan­cial op­por­tu­nity in earn­ings calls and a cri­sis in every fire sta­tion in the coun­try. As of 2025, REV Group’s back­log stands at $4.5 bil­lion. Wait times for a cus­tom fire truck run to four years. Prices have dou­bled in a decade: a pumper truck now costs around $1 mil­lion; a lad­der truck runs over $2 mil­lion. Profit mar­gins in the in­dus­try have tripled — from the his­toric 4-to-5 per­cent range to over 13 per­cent.

“Our $4.5 bil­lion back­log is at­trac­tive among in­dus­trial man­u­fac­tur­ers, is largely backed by mu­nic­i­pal tax re­ceipts, and of­fers sig­nif­i­cant value ac­cre­tion op­por­tu­nity, pro­vid­ing a path­way for growth and mar­gin ex­pan­sion over the next sev­eral years.”

— Mark Skonieczny, CEO, REV Group, 2025 in­vestor earn­ings call

Note what Skonieczny is telling in­vestors: the back­log is not a prob­lem to be solved. It is an as­set. The cus­tomers — fire de­part­ments serv­ing American cities — are locked in be­cause they have no al­ter­na­tive. Their or­ders, backed by tax re­ceipts, are guar­an­teed rev­enue. The com­pa­ny’s in­cen­tive is to main­tain the back­log, not elim­i­nate it.

The Senate heard this clearly. At a September 10, 2025 hear­ing, Senator Josh Hawley (R-MO) put it bluntly to the man­u­fac­tur­ers:

“This did­n’t just hap­pen to you ac­ci­den­tally. This is a busi­ness de­ci­sion, is­n’t it? You keep these back­logs like this. […] Another word for this would be a heist. This sounds to me like pri­vate eq­uity came in; bought up all of these small com­pa­nies; com­bined them; shut down their pro­duc­tion; rolled up a huge back­log; mas­sive prof­its; stiffed these guys; and now you’re mak­ing out like ban­dits.”

— Sen. Josh Hawley, US Senate Subcommittee on Disaster Management, September 10, 2025

The pro­duc­tion data sup­ports Hawley’s char­ac­ter­i­sa­tion. REV Group closed mul­ti­ple pro­duc­tion fa­cil­i­ties in Pennsylvania and Virginia even as its back­log grew. The com­pany si­mul­ta­ne­ously spent $530 mil­lion on stock buy­backs and div­i­dend pay­ments, in­clud­ing a $180 mil­lion spe­cial div­i­dend paid di­rectly to pri­vate eq­uity own­ers just be­fore the com­pany went pub­lic. The CEO earns $6 mil­lion an­nu­ally.

The com­pet­i­tive mar­ket is gone. The Fire Apparatus Manufacturers Association — the in­dus­try trade group — holds an­nual meet­ings where mem­bers share “economic data, fire mar­ket trends, and ap­pa­ra­tus sales and or­der sta­tis­tics.” Antitrust at­tor­ney Basel Musharbash tes­ti­fied to Congress that the con­glom­er­ates “appear to have trans­formed a once vi­brant in­dus­try into a racket.” Four cities — Los Angeles County, Green Bay, Allentown, and oth­ers — have filed fed­eral an­titrust law­suits. The Texas Attorney General opened a price-fix­ing in­ves­ti­ga­tion. The de­fen­dants deny all wrong­do­ing.

Meanwhile, Ed Kelly, pres­i­dent of the International Association of Fire Fighters, told the Senate: “Sometimes we have fire­fight­ers re­spond­ing in pickup trucks, like a paint­ing crew with ground lad­ders on it.”

This Is a Pattern, Not an Anomaly

The fire truck in­dus­try is the most pub­licly doc­u­mented case, but the un­der­ly­ing play­book — ac­quire, con­sol­i­date, re­duce sup­ply, ex­tract mar­gin — ap­pears across es­sen­tial sec­tors with alarm­ing con­sis­tency.

Ambulances

Private eq­ui­ty’s grip on emer­gency med­ical ser­vices fol­lows the same arc. KKR con­trols sig­nif­i­cant am­bu­lance mar­ket share through Envision Healthcare and Global Medical Response (parent of Rural/Metro). As PE’s mar­ket share in air am­bu­lance grew, the me­dian charge for a trans­port in­creased over 60 per­cent be­tween 2012 and 2017, ac­cord­ing to re­search cited in Senate tes­ti­mony. The pre­dictable end­point: Envision Healthcare filed for Chapter 11 bank­ruptcy in 2023 un­der the weight of debt it was sad­dled with af­ter its PE ac­qui­si­tion — leav­ing con­tracts can­celled, re­sponse times de­graded, and in at least one doc­u­mented case, a de­layed am­bu­lance ar­rival that may have con­tributed to a death.

Nursing Homes

PE in­vest­ment in nurs­ing homes grew from $5 bil­lion in 2000 to $104 bil­lion in 2024. More than 1,500 fa­cil­i­ties now op­er­ate un­der PE con­trol. The doc­u­mented out­comes are not am­bigu­ous: PE-owned nurs­ing homes show more care de­fi­cien­cies, sig­nif­i­cantly re­duced staffing hours, higher hos­pi­tal­i­sa­tion rates, and in­creased mor­tal­ity. People un­der­go­ing surgery at PE-acquired hos­pi­tals faced a 17 per­cent higher prob­a­bil­ity of dy­ing within 90 days than pa­tients at non-ac­quired cen­tres, ac­cord­ing to peer-re­viewed re­search. At least two PE-owned nurs­ing home chains filed for bank­ruptcy in 2024 alone — LaVie Care Centers (backed by Formation Capital) and Goldner Capital Management — leav­ing res­i­dents dis­placed and staff un­paid.

Housing

Institutional in­vestors — many PE-backed — own more than 500,000 sin­gle-fam­ily rental homes and are pro­jected to con­trol 40 per­cent of the US sin­gle-fam­ily rental mar­ket by 2030. The DOJ opened a crim­i­nal in­ves­ti­ga­tion in 2024 into RealPage, a prop­erty-man­age­ment soft­ware firm used by ma­jor land­lords, over al­le­ga­tions that its al­go­rith­mic pric­ing sys­tem en­abled co­or­di­nated rent in­creases across com­pet­ing land­lords — ef­fec­tively au­tomat­ing what an­titrust law would oth­er­wise pro­hibit. The Senate passed a bi­par­ti­san hous­ing bill in March 2026 tar­get­ing large in­vestors, though its scope re­mains lim­ited.

Local Newspapers

Alden Global Capital — a hedge fund with tac­tics in­dis­tin­guish­able from PE — sys­tem­at­i­cally ac­quired lo­cal news­pa­pers and gut­ted them, cut­ting news­rooms faster than any other owner in the coun­try. The 2019 Gannett-GateHouse merger, backed by New Media Investment Group (a hedge fund), put one in five US daily news­pa­pers un­der fi­nan­cial-en­gi­neer con­trol. Academic re­search found that when a PE firm ac­quires a news­pa­per, the news­room shrinks by an av­er­age of nine re­porters and ed­i­tors — around 14 per­cent of staff — not be­cause the pa­pers aren’t prof­itable, but be­cause the model de­mands mar­gin ex­trac­tion. The ef­fect is the de­struc­tion of lo­cal de­mo­c­ra­tic ac­count­abil­ity in­fra­struc­ture.

The Structural Problem Nobody Is Naming

The main­stream cov­er­age of PE tends to fo­cus on in­di­vid­ual cases: a hos­pi­tal that went bank­rupt, a nurs­ing home with code vi­o­la­tions, a city that can’t get a fire truck for four years. The sto­ries are com­pelling. What they of­ten miss is the sys­temic ar­chi­tec­ture that makes these out­comes not bugs but fea­tures.

PE’s struc­tural in­cen­tive is to max­imise re­turns over a 3-to-7 year in­vest­ment hori­zon. When ap­plied to gen­uinely com­pet­i­tive in­dus­tries with mul­ti­ple play­ers, this can drive ef­fi­ciency. When ap­plied to es­sen­tial ser­vices — par­tic­u­larly af­ter roll-up ac­qui­si­tions that elim­i­nate com­pe­ti­tion — it cre­ates some­thing more trou­bling: a model that prof­its from degra­da­tion of the very ser­vices the pub­lic can­not opt out of.

The debt load­ing mech­a­nism is key and un­der­re­ported. When a PE firm ac­quires a nurs­ing home chain or an am­bu­lance com­pany via LBO, the debt does­n’t sit on the PE fir­m’s bal­ance sheet. It sits on the ac­quired com­pa­ny’s bal­ance sheet. The firm has al­ready ex­tracted its man­age­ment fees. If the com­pany even­tu­ally files for bank­ruptcy, the PE firm has typ­i­cally al­ready re­ceived div­i­dends and fees that ex­ceed its eq­uity con­tri­bu­tion. The losses fall on cred­i­tors, work­ers, pen­sion funds, and — in the case of es­sen­tial ser­vices — the com­mu­ni­ties that de­pended on those ser­vices.

REV Group’s $180 mil­lion spe­cial div­i­dend to PE own­ers be­fore IPO is a text­book ex­am­ple. The money was ex­tracted be­fore the mar­ket ever had a chance to price in the risk. The fire de­part­ments who need the trucks have no equiv­a­lent exit op­tion.

What Comes Next

Four cities have now sued the ma­jor fire truck man­u­fac­tur­ers. The IAFF has for­mally asked the FTC to in­ves­ti­gate an­titrust vi­o­la­tions. The Senate held a bi­par­ti­san hear­ing — no­table for its rar­ity — in which sen­a­tors from both par­ties used words like “heist” and “racket” with­out the man­u­fac­tur­ers of­fer­ing a cred­i­ble re­but­tal.

The broader PE re­form de­bate has gained ground. The Stop Wall Street Looting Act, in­tro­duced in Congress, would make PE firms li­able for the debts of their port­fo­lio com­pa­nies, close the car­ried in­ter­est tax loop­hole, re­strict div­i­dend re­cap­i­tal­i­sa­tion (the prac­tice of load­ing debt to pay PE own­ers be­fore exit), and give work­ers a pri­or­ity claim in bank­ruptcy. It has not passed.

The harder ques­tion — one that the an­titrust suits and Senate hear­ings won’t fully re­solve — is whether es­sen­tial in­fra­struc­ture should be sub­ject to the same fi­nan­cial-en­gi­neer­ing logic as any other in­vestable as­set class. The mar­ket an­swer is: what­ever gen­er­ates re­turn is fair game. The pub­lic ser­vice an­swer is: some in­dus­tries ex­ist to serve com­mu­ni­ties, and the cost of mak­ing them pure profit ve­hi­cles is paid in de­layed am­bu­lances, un­main­tained fire trucks, and bod­ies in burned apart­ments.

The fire in Chicago is not a metaphor. It is a con­se­quence. And it will keep hap­pen­ing un­til the struc­tural in­cen­tives that pro­duced it are ad­dressed — not case by case, but at the level of the model it­self.

Canada has an­nounced plans to buy a fleet of early warn­ing planes from Sweden’s Saab rather than a com­pet­ing op­tion from Boeing, as the coun­try seeks to re­duce re­liance on US de­fense firms.

Mark Carney, the prime min­is­ter, said on Wednesday that Canada would opt for Saab’s GlobalEye, which is based on Bombardier’s Global 6500 jet. Boeing’s E-7 Wedgetail plane — which has suf­fered from de­lays and cost over­runs — had also been in con­tention.

“With a suite of ad­vanced sen­sors and mis­sion sys­tems, Saab’s GlobalEye will be a key re­source for the Canadian armed forces to de­tect and de­ter threats across the Arctic,” Carney told a de­fense con­fer­ence in Ottawa.

The prime min­is­ter pledged in March that Canada would take full re­spon­si­bil­ity for pro­tect­ing its vast Arctic ter­ri­tory, af­ter re­ly­ing on decades on a part­ner­ship with the US to mon­i­tor its more than 4.4m sq km (1.7m sq miles) of land and sea, a ter­ri­tory larger than India.

In a state­ment, Saab said it planned to in­vest in re­search and de­vel­op­ment work in Canada as part of any deal.

Although Carney did not give de­tails of the fleet size or the cost of a po­ten­tial con­tract, mil­i­tary of­fi­cials had ear­lier said they were look­ing to buy six early warn­ing air­craft.

Philippe Lagasse, as­so­ci­ate di­rec­tor of in­ter­na­tional af­fairs at Ottawa’s Carleton University, said Canada’s de­ci­sion to buy the GlobalEye planes was “an im­por­tant test case for the Carney gov­ern­men­t’s pol­icy of piv­ot­ing away from American mil­i­tary ca­pa­bil­ity”.

He said in a state­ment that the de­ci­sion con­firmed Canada’s re­la­tion­ship with Sweden, a new Nato ally that had also been keen to strengthen its ties to the Canadian mil­i­tary.

Canada has pre­vi­ously said it is keen to work more closely with the Nordic coun­tries in the Arctic on de­fense and other is­sues, in a global en­vi­ron­ment where the US has be­come a less re­li­able part­ner.

“GlobalEye is al­ready cre­at­ing jobs in Canada, and work­ing with the Canadian sup­ply chain. This de­ci­sion ties our two na­tions even closer to­gether,” the Swedish prime min­is­ter, Ulf Kristersson, said in a so­cial me­dia post.

Saab is also in the run­ning to sell Canada some of its Gripen fight­ers. Canada has a deal to buy 88 F-35 jets from Lockheed-Martin, but last year, af­ter the US slapped tar­iffs on key Canadian im­ports, Carney asked the mil­i­tary to in­ves­ti­gate whether it could cut back the or­der and buy some planes from an­other man­u­fac­turer.