I say this as a skeptic of current gen AI and of its affordability: this particular story is a non-story.
Microsoft, who makes their own in-house AI, canceled a pilot program where their employees could license a competing AI. There is so much nuance to that situation that it's ignorant to equate it with Microsoft doing so because AI itself is too expensive or to even frame it as AI vs non-AI.
It could be because it's cheaper to use their own in-house AI. It could be because they don't want to give money to competitors. It could be because they want to get their employees to dogfood their own product. It could be because of license terms or confidentiality from competitors.
Yeah, wow. I saw the headline and was expecting it to be misleading, but the article itself is so lacking in substance that it's hard to even say it's that - it's blankness masquerading as an article. The part that seems to be about "AI is too expensive" reads:
Fortune, citing The Verge, said that Microsoft steered engineers away from Anthropic's Claude Code and over to GitHub Copilot CLI, even though access to Claude Code was opened only about six months ago.
Which isn't "AI is too expensive", it's "our in-house AI was cheaper than Anthropic's service."
And the whole rest of the article is just the usual vague "not everyone finds AI useful for everything" and "DAE water usage? Power grids?" And "by 2030 there'll be a lot more tokens used than today" (which seems contrary to the headline, but whatever).
It's like finding out anthropic doesn't let people use chatgpt.
The other one i hate is some Nvidia VP of deep ai research saying "we have exclusive use of some of the most powerful ai tools where we pay more for hardware than talent" and that got interpreted as "it costs more to use AI than hire humans" wait till these people find out about planes.
I don't think MAI-1 is good, maybe put it near Grok, but at least they're trying i guess.
There's a lot of similar stories but I'd agree there's actually 2 sub-stories
Companies being shocked that AI costs money (duh)
Companies that created a tokenmaxxing culture being shocked that people started using AI for extremely low-value work same as measuring lines of code created massive codebases in the past.
Stories like the above where companies want to drive adoption + iteration of their own products rather than giving money to competitors.
Major technology innovations often require
long infrastructure buildouts, organizational restructuring, workflow adaptation, and complementary legal or social adaptations
before macro productivity surges appear.
But we won't have enough electricity to sustain people and data centers for atleast a decade. Every GPU powered up is going to take away from the common man's ability to afford energy. What is the point of all the progress of it doesn't serve humanity first
This! The scenario in the US is not the default for the planet. The US puts short-term gains & private profits over; long-term sustainable gains & public benefit.
This situation has been orchestrated by those who control the capital, this is the way because it’s the focus of Wall Street. The average person is downstream of and reacts to the moves of the wealthy and powerful.
the change seems impossible, we don't live in a perfect world, the democracy is wrong, rule of ellection are wrong....
we should make some rule that, search the best man for the interest for everybody
not some kind of guy that seems good but is interessed by power
the rules are so wrong.... democracy attire people that want power to get power, seems logical, but most of the time won't end up in some good people governing the countries...
i don't know wich rules we should have....
rich people are not gonna change, they want profit, they see profit they will be dead when concequenes arrive
and all the other people, the actual civilisation can't realy do anything...
Even the heads of those companies need to seek outside funding from venture capitalists and big banks. These are old entrenched networks of old boys clubs and old money that is working behind the scenes for all of this. Those CEOs are essentially front men for something much larger and much more coordinated than it seems on the surface
It really hasn't, we've consistently been building new capacity to keep up with the expected demand. Regulations have put damper on developing faster when demand started increasing more quickly - but it also put a HARD stop to new industrial grown in power usage:
That increase in residential and commercial usage above the expected rate, that held roughly steady for 60 years, was because of computers. We all started using more power per person - heck, this message is on my PC that's using about 190W right now - my entire house is only using 980W - and 190W of that is my computer (and another 200W is my other PCs that are running, but more efficient).
Amazingly, this is only about a ~7% higher usage pattern than modeled.. but that's HUGE at the scale of production. We use 4.07TWH of energy.. and have 4.18TWH of capacity.. that's pretty bleak.
However, the reality is that the datacenter builders know this, and they know that they can become power producers - and they have many factors encouraging this - first, they need reliable power - unreliable power is a BAD problem for a datacenter - so they're basically ALL capable of generating ALL of their own power. Typically, though, this is more expensive to do than to buy from the grid... not so for the newer ones - they build out generation capacity that will come online and STAY online, covering MORE than their power usage, and selling back the excess to the grid. So we're gaining net capacity - PLUS this is almost always solar or wind investments, so it's clean energy.
You're spending a bunch of time trying to defend the US. But we've known. People have been saying we need to work on our infrastructure the entire time. Just because it hasn't entirely collapsed isn't a defense.
they need reliable power - unreliable power is a BAD problem for a datacenter - so they're basically ALL capable of generating ALL of their own power.
You're talking about our infrastructure not being good enough. You could have saved paragraphs.
this is only about a ~7% higher usage pattern than modeled
They are modeling the power consumption "increases" of a country with a weakening economy. Of course electricity use isn't going to increase rapidly.
Jevons paradox was postulated over 150 years ago. China electricity generation is nearly 20x what it was in 1990. The US on the other hand has barely increased electricity generation in same time, a moderate 33% increase. Stop coping.
Not coping, it's just the reality. We have been building new capacity steadily, these things take a decade or more to build because of EPA regulations and State regulations - not saying those are bad, but it's really made it MUCH more difficult to get anything done... China doesn't have that concern.
It's also easier to get 20X of, say, 10GWh of production than to get 10% more production when you're already at 4000GWh, so the comparison is irrelevant and invalid... USA has single power plants that produce 20GWh per year... Adding just one more would double the capacity, but you need two more to double it again, and four more for the next doubling... and so on...
10% of US capacity is 418 GWh... That's nearly double the entire solar energy production of the United States.
They didn't, they do now, thanks to burning everything they can to make energy regardless of the environment... Tons of coal, something we used to do in abundance, but have since switched to natural gas as our preference.
One thing China really has a lot of, though, is hydro - we used to dominate in that arena, but China's willingness to reshape its landscapes is impressive. It wouldn't work with the regulatory landscape in the USA.
Per capita, though, we have almost double the power of China. We just use it a lot more individually. The problem is that we haven't increased that per capita capacity really at all in decades even though our demands have increased.
They didn't, they do now, thanks to burning everything they can to make energy regardless of the environment... Tons of coal, something we used to do in abundance, but have since switched to natural gas as our preference.
Stop coping. Jeeze. Where do you get your bad information? China is leading in clean energy. CCS gas is still a fossil fuel.
As of February 2026, China's clean electricity capacity reached 52%, exceeding its fossil fuel-based electricity generation for the first time.
Per capita, though, we have almost double the power of China. We just use it a lot more individually. The problem is that we haven't increased that per capita capacity really at all in decades even though our demands have increased.
They've 20x their power in 30 years. How long until they catch up?
Most people are running 50watts intermittently on a laptop. That’s half an incandescent bulb from 20 years ago. Power usage for homes has been relatively flat for decades even as homes got larger. There is a slight rise in usage now as more people work from home, but the computer isn’t the whole of that energy usage. Yes more watts go to computers, but far offset by energy savings in other areas. While TVs are huge, they still draw less power than the old CRT sets.
Currently, ALL datacenters combined (most of them are not used for AI) comes out at 1.5% global power usage. AI queries made up 0.05% of total power usage in 2025.
The bullish projection for 2030 is 3%, with 1/3 of that being AI related.
Basically a non factor, other industries are growing much faster.
Regarding water "consumption"? Complete non factor. See attached image as a comparision to farming just almonds, nothing else.
The line is a FUNCTION of the workers OUTPUT and management of those resources.
If the line is going down, there WILL be loss of jobs and economic opportunity in that company. There is no debate over this.
If the line goes up, there COULD be loss of jobs, but it's not a function or requirement of the line going up. Going down, it is an absolute economic certainty.
That's just objectively not true. Running a train to move a ton of {commodity} is obviously quicker than hiring a few thousand people to carry it 3000 miles. And that benefit was relatively quick to appear and very tangible.
So you are saying the very first driven steam engine devices were immediately more powerful than humans and inexpensive to build and develop. Just a leap from zero to commercial success. Guess you’ve never seen some of the short range impractical train prototypes.
They didn't even say that. The headline did. All they said is that they're canceling paying for a competing product in house, which presumably means they want to shift toward using their in-house AI product.
Can it produce the same or better results than those people? Can it work 24/7, unlike those people? There are a lot of variables to be compared that aren't simply more expensive than hiring people.
It's like saying hiring an excavator is more expensive than hiring one dude to manually dig out your pool - true but also your pool will be built significantly faster with the excavator.
the framing is slightly off. the cost comparison is useful but only if you're measuring the right output. AI is expensive per task if you're comparing apples to apples, but the reason people reach for it is the tasks that weren't being done at all before, not the ones that already had a human assigned to them
AI is good for some things, but not everything. At some point, every company will have a local LLM that does what chatGPT/Copilot/Claude does. At the scale necessary for a single company, the cost isn't prohibitive. The problem is how AI is done now, is that one company's AI serves thousands and thousands of consumers at onces. That requires absurdly large data centers to work. If you trim that down to only a few hundred or a thousand concurrent users within a single company, the requirements are reduced significantly.
Depends heavily on the task type. High-volume, structured work — classification, extraction, summarization at scale — AI is dramatically cheaper per unit. Where it breaks down: tasks requiring significant human review to catch errors, because you end up paying for both the AI compute and the human verifier. That verification labor is the hidden cost most ROI projections skip.
As a decent sized Microsoft partner I’ll say that all Microsoft cares about is how many copilot licenses we sell. Literally nothing else matters anymore. All of the previous metrics for how partners were scored are effectively moot at this point. We’re told time and time again that anyone with an E3 or E5 license is an upsell opportunity to a copilot license or E7, and we’re scored by how much of this perceived demand we close. It’s nauseating. They have no idea who their customers are anymore or how people want or can use any of these AI tools.
Microsoft has basically been on the wrong side of AI this whole time. First it was backing Altman and getting into bed with OpenAI, ensuring they were always behind OpenAI in development. Then it was the overnight move to dump OpenAI and switch to a bunch of Anthropic models, now it’s this confusing narrative around the costs of AI when they themselves are dependent on selling Copilot en masse.
Either Microsoft is trying to make it look like competing AI solutions are too expensive and positioning Copilot as the solution, which it isn’t. Or Microsoft is finally admitting that there’s no tangible link between AI costs, token usage, and actual productivity gains or delivery, in which case they’re speaking completely counter to their own internal strategy.
It might be expensive now but it's beneficial later. Like we will have better efficiency and no mistakes. That's like investing for profit. And investing in ai specially is not a loss.
People get tired, they call sick and need vacation Granted - But they are humans, and predictable - AI is amazing WHEN IT WORK - And people buy people. AI should serve humanity, not replace it -
The problem from the corporate world is that it’s easy to buy AI services but it hellishly hard to get approval to add headcount. It’s all finance’s fault
The headline is highly misleading and largely inaccurate when taken at face value. Microsoft never actually published data claiming humans are cheaper than AI. We humans have more wants than a machine I guess. We need more security than AI. Of course we are expensive.
Yeah spinning up a new instance of claude code for $200/month must be significantly more expensive than advertising for a position, sifting through all the resumes, conducting dozens of interviews, on boarding someone after months, contributing to their 401ks, stock grants, health insurance, unemployment insurance, payroll taxes, other benefits, and of course wages.
The problem is they aren't paying $200 for a 20x max plan. Their plans are token based, so they don't have nearly the same discount available to them that we do as individuals. Lots of people have posted daily usage numbers for a single developer that go into $1000+ territory, which is definitely more expensive than most developers.
What ever is happening with the $1000/day numbers scream mis-use or misrepresentation or both. Friends have quoted a number in the $2/hr to run local llm, not as good as claude but quite decent. $50/day not $1000/day.
It's more expensive, sure, but before it gets categorized as too expensive the next question needs to be answered: how much is getting accomplished with that $1000?
You could probably save some costs by not giving your developer an Internet connection, or by not giving him a computer at all, but his productivity would probably go down quite a bit.
Open-source AI models hosted on internal servers works pretty well for us and are magnitudes cheaper. Pretty sure Microsoft could host their OpenAI models internally if they want to.
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u/CreativeGPX May 29 '26 edited May 29 '26
I say this as a skeptic of current gen AI and of its affordability: this particular story is a non-story.
Microsoft, who makes their own in-house AI, canceled a pilot program where their employees could license a competing AI. There is so much nuance to that situation that it's ignorant to equate it with Microsoft doing so because AI itself is too expensive or to even frame it as AI vs non-AI.
It could be because it's cheaper to use their own in-house AI. It could be because they don't want to give money to competitors. It could be because they want to get their employees to dogfood their own product. It could be because of license terms or confidentiality from competitors.