> Between May 2025 and May 2026, employment in the sector dropped a staggering 21 percent, according to BLS data.
Yeah sure. I mean, same reason why HN readers hate AI, right? It replaces their jobs.
(Obviously the difference is that the poor old claims adjusters didn't spend the last two decades "disrupting" every other industry and telling everyone else to "learn to code". Ha! If you hear a faint high noise, that's the sound of the rest of the world playing a violin, made of highly disruptive nanomaterials.)
The difference being that the role of Engineer wasn't conceived as a layer of friction between consumers and their statutory rights to the point where a U.S. Senate subcommittee probe (Senate Homeland Security Subcommittee on Disaster Management) and state-level legal crackdowns were necessary to try and address what constituted systematic fraud by property/casualty insurance corporations.
Indeed, some of the core violations could be simply mandated as part of the inviolable system guardrails of an LLM - e.g. failed to begin investigating claims within 15 days, failed to accept or deny claims within 40 days, and failed to pay accepted claims or provide written notice of the need for additional time within 30 days, as required by law.
And at the end of the day, whatever weighting issues an LLM for Insurance Claim Adjustment has, it certainly won't steal the money and run off to a Casino with it
Anecdotally, many of them are aging out and the demands of adjusters are increasing while the pay hasn’t necessarily gone up. While technically you don’t have to know the ins and outs of construction, it helps a lot and there are just not a lot of people who have that knowledge. And if they do, they often go into construction themselves or sell roofs. Both of which can be far more lucrative.
On top of that, claims software has a lot of automation but very little real AI surface area. A lot of the things AI is good at (text generation) must have certain verbiage or use legally approved templates.
Granted, this may not be the case for all verticals, but this is just my observation from 20 years. (Mostly in smaller IA firms and state-based institutions).
Also, my wife has pointed out that there haven’t been any major cats in the last few years. Katrina kept people working for years. A lack of big storms has also contributed to this.
Ageing and out and neither being replaced directly or reduce numbers coming in at the bottom/mid as others move up, is still a drop in people. If part of the reason there is less need to bring people in lower down is that a few are being expected to do the work of a few more due to automation via AI, then that is AI replacing them, just not quite as directly as “we need less people as AI makes each more efficient so there are redundancies”.
But that's the thing—there isn't any real automation for this. An adjuster has to physically go out to someone's property. They have to take pictures. They have to inspect things. They have to coordinate with 3rd parties if necessary (like engineers).
There isn't a whole lot of room for automation in much of this.
Underwriting on the other hand, that is a different story.
There are probably two camps in IT (in terms of hating AI). One is afraid that AI will replace them, the other is about to rage quit because AI is damaging to their mental health, but being forced on them by management which is as clueless that those of the insurance claims adjusters.
So AI is going to take jobs not because AI is necessarily better or more appropriate, but because it accelerates bad decision making and makes those decisions exponentially worse.
See OpenAI putting the blame on a “rogue agent” for their own systems hacking other companies (which is a felony!!!!). When in reality they obviously control the while loop and tool call dispatching of the agents. But they decided to train attacker models, then run thousands of instances in parallel with the goal to solve hacking problems with close to no supervision and full execution privilege…
That company is highly amoral from top to bottom (yes even innocent Joe just cashing his million + bonuses while seeing all this crap and much more from inside and happily chugging along with 'just paying off that mortgage' tunnel vision).
Except shit, amoral behavior, backstabbing, lying at all times, just to get those sweet money and power.
Ultimately this isn't "AI's fault". As the article points out, clueless executives who don't understand the capabilities and limitations of specific LLMs push the technology on workers so they can say they are "using AI to improve efficiency".
Which clueless executives are we blaming? The ones who purchase products from vendors like OpenAI or AI-powered products that run API calls through OpenAI et al., or the vendors themselves who make bombastic claims about capabilities?
I don’t know if I fully blame my executives for buying Microsoft Teams when Microsoft Teams turns out to suck. Microsoft promised to my company’s executives that Microsoft Teams doesn’t suck just like Sam Altman promised that AI is so powerful and so capable of exceeding the capabilities of humans that it’s dangerous.
You should. It's their fault for picking a bad vendor. It's their fault for not finding someone with taste to solve the problem. Fundamentally its their business, pretending you can blame someone else for your ultimate accountability is stupid.
Nobody is forcing you to take poison, and saying "Well Microsoft promised me it isn't poison!!!" at this point, decades into it selling poison, doesn't make much sense.
They didn't pick the bad vendor, the herd did. They all go to the same conferences, attend the same vendor lunches and buy the same garbage. And today, most of the IT managers are not technical at all. They have art degrees and have never been technology practitioners.
Literally anyone off the street can be a "decision maker" in technology today. Just buy what everyone else is buying and collect a huge paycheck while working remote. People who understand tech and sort of know what they are doing, are not included.
No ... THEY very much did. In fact the whole idea of their job is that they are responsible for the outcomes. Seriously. Listen to their speeches. That gets repeated and repeated and repeated, again and again and again.
Of course, if insurance companies were rapidly held to account by courts, a core function of the courts if there ever was one, there would be no problem here.
Which is probably why most governments are defunding the courts.
Your executives are completely unable to evaluate the products they decide to buy?
If so, yes, they are to blame, either for not being able to evaluate the stuff they buy or for deciding on questions they are not qualified for. Either one is incompetence.
You can also blame them to continue renting the thing (because it's not brought) after it's shown to be defective. And if they decide to do irreversible transformation to your business before verifying that the thing even works, than yes, that's bare incapacity of running a company.
But isn’t this also just bad implementations of AI? “It got a stupid simple answer wrong”, seems like a gpt-4o on a buggy RAG implementation from 2 years ago problem.
Hard to fathom a modern model would get any of this basic stuff wrong. I know accountants using it for (a lot more complex but similar problem) tax law parsing and it going through flawlessly.
There seems to be some bidirectional media gaslighting happening here where the doomers and glazers are talking past each other a bit.
I don't know, it feels like "reading a claims summary and classifying the type of claim" should be the bread and butter LLM use case? Not that executives are blameless for pushing AI everywhere, but we should also be able to "blame" AI for doing poorly at a task it's supposed to be good at.
The interesting thing about AI v. other disruptive technologies (like the internet, steam engine, etc), is that AI has been personified both by the manufacturers of it (Anthropic being the most blatant by using a human name for its product) and users.
That makes it way more likely that people blame AI (doesn't make it right by any means, but does mean that the actual blame gets diffused even more).
Regarding "how is that a problem" it has nothing to do with the financial obligations (I agree with your take that the company is on the hook either way). It's about being able to learn and improve.
In order to learn and improve you have to know what went wrong, with AI being personified and pulled into the pool of entities that may be at fault, it makes it harder to figure out what actually went wrong and learn. Not impossible to figure out, just harder.
>You can't 'blame' the AI, as it can't be held accountable.
Seems like more of a semantic distinction IMO. Yes, I can't technically "blame" the AI because it's not accountable. But what word would you suggest for "I had [X technology] handle [Y task] and it failed to perform that task?" I can't "blame" my router if I lose internet and it prevents me from jumping on a Zoom call, but it's also true that the router failed to do the thing it was supposed to do.
Do you blame the hammer for bending the nail, or the person driving it? AI is nothing more than a tool being used by people.
When my internet goes down, I blame either my ISP for having an outage, or the manufacturer of my router (assuming it's a router issue? Haven't had that happen personally but I'm certain it exists) (Or i did something dumb with my ufw again but that's on me)
If you create an autonomous system and it fails, blame should be on you, imo.
The word is still 'blame', it just needs to be applied correctly.
Not that it is necessarily the case here, but when execs go "AI shopping" they have absolutely _zero_ idea that there are basically 3-4 SOTA models, thousands of smaller models, and then an uncountable number of wrappers on whatever underlying model. The AI landscape that is totally familiar to us is covered in shroud for them.
So they Google "Insurance claim AI tool", land on a vibecoded SaaS that is just a wrapper on a pocket Chinese model spun as "your next insurance pro", and then are getting the whole department on some lone 19 yr olds weekend project.
Part of the problem is the distribution of images (and text) you get from claims is not the same as what the model was trained on. A classic problem in ML.
Another part of the problem is that a model not specifically fine-tuned to make a total loss determination won't know the relevant factors, nor how an insurance company's concept of a total loss differs from the public's.
And still another part of the problem is that most total loss claims aren't what you, dear reader, are imagining: They are very rarely "the car is a thin pancake after being crushed by a meteor".
The much, much more common scenario is: "50% of the body panels sustained at least paint damage, both headlight modules need replacement, and the front wheels look funny. Given that the vehicle has an MSRP of $FOO, $BAR miles, no prior collision history on carfax, and is a popular color, is it cheaper to repair or total the vehicle?"
Of course, the model can turn over the hard cases to a human adjuster... but then what are we doing here? It only takes 10 seconds for the human adjuster to handle the "crushed by a meteor" case also.
Source: Listening to my SIL rant about being asked to stop training bespoke total loss models and just send it by 1-shotting a commercial LLM.
LLMs are really good when your primary goal is just to fob people off. So customer support when you don't care about your customers etc. I can imagine it's very appealing when you just want to come up with semi-plausable reasons to deny insurance claims. Who cares if it's wrong? They might give up anyway and you've saved paying out!
Not saying they're not good for other things, but the "waste people's time and make them go away" use is just so perfect for the capabilities of even cheap models.
Anybody that has worked on a phone exchange knows they already do this sort of thing. Some customers just never get through to a person. This is by design.
Can confirm. Until I worked on an honest phone system tuned to actually get people connected with call centre reps, I never quite had a feel for how malicious many contact funnels have become. A good one runs like a Swiss watch, and is trivially tunable to sub-5 to 10 minutes wait times. Anything longer is a conscious choice on the company's execs part. It doesn't "just happen", and to the degree it does, it shouldn't be happening on the regular. Not if you're watching your metrics and tuning appropriately.
Believe it or not, that's not even the topic of the article.
The article is entirely about the AI doing the first pass of the claim intake and causing a lot more work for everyone involved instead. Mis-routing, mis-categorization, hallucinating details, etc.
It seems like companies are getting a lot less trusting with their return policies.
It used to be you just email them a photo or video of the issue and they send you a replacement. Now companies won’t send one until they have received the defective one back.
When there is more efficiency its a win for AI. When there are errors its the problem of the humans that are supposed to be using AI and oversee it to "make them more efficient". This has been the main source of AI fatigue for me.
Two months ago I had a water pipe burst in my house.
Now I am in the claims process with the large insurance co., using Claude to basically run my side of the claim — reading the policy, organizing and filing the ALE receipt scans, reading and notifying me of messages from the agents, calling out when they are delaying too much or not fulfilling their promises, challenging their decisions on what to cover based on the policy, keeping a log of all of our correspondences, logging work estimates and invoices, I cant imagine doing all this tedious work myself—w/o Claude I’d probably just rollover fatigued.
Does my adjuster like this? On the one hand, I’m giving her incredibly tidy and documented receipts and logs, which I am sure is saving her time.
On the other hand, Claude is calling out her BS and delays, which have been atrocious—so much so that Claude is now adamant that she has gone too far and that I should be filing a complaint with the state insurance bureau.
> On the other hand, Claude is calling out her BS and delays, which have been atrocious—so much so that Claude is now adamant that she has gone too far and that I should be filing a complaint with the state insurance bureau.
My first guess: She is wildly overworked and that is an insurance company strategy.
This is an interesting customer strategy. Have you escalated your concerns to her management? Have you explained to her that you are considering filing a complaint with the state insurance bureau? It's the ol' stick vs carrot. I say: Start with the carrot. If that doesn't work, back to the stick!
My wife works in autism services. Insurance companies are the bane of her existence. Every six months (sometimes less), she has to write a huge report justifying services. These reports are frequently over 100 pages and she is only slotted so much time to do it, so she ends up doing a ton of unpaid work. The entire business model is to drown the practitioner in paperwork then use “peer reviewers” who are nurses that don’t know anything about the treatment to deny claims then waste the practitioner’s time on appeals in the hopes that people will give up. AI has obviously made this process easier and the insurance companies absolutely hate it.
People have no idea how inefficient the U.S.’s healthcare system is. And it isn’t just the private companies. A ton of states purposefully overburden and underfund their Medicaid systems for ideological reasons. Then the private insurance companies adopt the same practices later.
From time to time, I see similar claims like this on HN: "doing a ton of unpaid work". The full quote:
> These reports are frequently over 100 pages and she is only slotted so much time to do it, so she ends up doing a ton of unpaid work.
What if she refuses to do the work unpaid? This seems like an open-and-shut case with the US Dept of Labour. There is a whole page that explains how to make a claim here: https://www.dol.gov/agencies/whd/contact/complaints Also, if she is part of a labour union, she can raise concerns with them.
> A ton of states purposefully overburden and underfund their Medicaid systems for ideological reasons.
Can you provide some evidence for this claim? Also, does this affect the state(s) where your wife works? From what I found, 66% of Medicaid is paid for by the federal gov't, and the remaining share is funded by each state.
The most obvious example were the 10 States which refused to accept increased Federal funding for Medicaid that was made available with the passage of the ACA, which seems largely ideologically driven.
Otherwise the situation is more complex than the original comment suggests, and I can only speak to one state (Idaho), but I don't think the scenario is uncommon in other GOP controlled states and isn't limited to Medicaid.
Idaho has cut taxes in the state for five consecutive years, largely (IMO) on an ideological basis. This had the result, desired by many in a deeply conservative legislature, of creating budget deficits. Even the GOP is normally wary of espousing cuts directly to the state's contribution to Medicaid, but the deficit gives them cover to reduce funding and introduce barriers to service like caps on authorized services and new work requirements. Even when revenues were higher than expected for FY 2026, the governor's office had to act to actually retain those unexpected revenues as it was pretty clear that the Legislature was going to look to claw them back and continue drive down State spending. It's worth noting that health services, including Medicaid funding, represent about a third of the State's budget and their largest portion of the budget.
This whole process has been playing out in public education funding in the State for years as well. Coincidentally, charter school enrollment has increased by roughly 35% over the same 2021 - 2026 period.
Attacking a policy, program or institution financially and then pointing to the deficiencies of those same programs to further fuel funding and efficacy reductions is a pretty well established tactic in US politics as I'm sure it is elsewhere.
Depending on the competition for her job and the state laws, she would either be put onto a performance management program, or fired. I've been through this before. The HR approved response is that they expect those 100-page reports to be complete within normal working hours, and a failure to achieve that means you are unable to fulfill the requirements of the job.
Of course those in high demand who can easily move to better employers will often do so. However there is a lot of friction when moving jobs. It's very time consuming, mentally demanding, and risky. I've seen incredibly talented staff treated awfully in my years, and they refuse to leave for various reasons.
If enough people are fired for this reason and file complaints with DoL (US Dept of Labor), then surely the DoL will open a case against the company for unpaid wages. If I recall correctly, for a while, Amazon used to force staff to arrive early (before shifts) but did not pay them for it. DoL got involved and the rules changed. To be clear: It is difficult, but not impossible, to make labor practices change with the help of DoL.
EDIT
This part should have appeared first: I agree that your scenario is the most likely outcome, even if I think it is reprehensible!
In most states, the answer is fixed by law at either zero or one depending on whether you count insurance, because medical practices must be wholly owned by doctors.
Inefficiency is their business model. They just soak $$ into their system. More overall revenue even if most of it is some rube goldberg machine of apathy.
Hah! Insurance companies proudly announce to investors how much they undercut payments.
It was precisely because of AI that I had the time and language to fight a recent claims report for a totaled vehicle, and squeezed an additional 25% from them. And it was still not adequate payout.
Let claim adjusters and insurance get off their high horse until they start being the bane of existence and paying what they owe clients.
So I have three thoughts about this: The first thought is this is likely mostly survivorship bias. Yes, the claims that get to the humans are the ones that went wrong, and the mode of failure for LLMs is less that they get within 99% all of the time, it's more like 1% of the time they do something insanely dumb. At which point your customers are pissed off. That's kind of obvious, and it sucks for the humans who have to clear up the situation. But it's still a win for the vast majority of cases.
Secondly, does anyone actually know how much of your insurance premium is going on the call centre staff? most people don't claim, those that do mostly have simple claims. The actual cost for insurance companies is actually paying out claims, so even if you automated all of this it likely doesn't change your economics. Historically "New" Insurance companies only really succeed by mis-pricing risk and gaining market share that way - they often then fail when that risk materializes. Lemonade sounds a lot like that.
Finally, they haven't engaged with the tidal wave that's coming. Sure, AI agents handling claims is happening now. Just you wait. In a couple of years time it'll be AI agents making the claims for you and suddenly there'll be bots filing claims with infinite patience and a direct mandate to try and get as big a payout as possible. That is when it's going to get really hairy.
We are witnessing the greatest ripoff in world history. First they illegally scrape the entire history of human text, art, video, then they create products to replace humans, next the wealth of those fired humans is transferred to wealthy VCs and large businesses.
And all the while these crooks are claiming it's so humans can focus on more important things. Yeah right. If we're lucky, AI won't improve and there will be a huge backlash, like outsourcing in the early 2000s. If AI gets better, actually good enough to do most work currently done by humans, well then probably something really ugly happens.
I know some would label this view as "Luddite" with derision, but learning some of the background of the actual Luddites, the parallels are hard to ignore. If you're interested, 99pi did a solid episode recently [1].
Yes it's ALSO to a promote a book, but still... there's a lot more to it than just mindlessly raging against a new technology.
> Between May 2025 and May 2026, employment in the sector dropped a staggering 21 percent, according to BLS data. For early-career adjusters, the decline was even sharper: Entry-level postings have fallen 50 percent since 2025…
When your business model has gotten to the point where people cheer for a guy who murdered one of their CEOs, it’s not surprising that people would not be interested in joining and may see being murdered as an occupational risk beyond what their personal actuarial tables allow.
On the outside, I was able to use a consensus model to reach a successful settlement. I wouldn’t say I won, but was made whole after having to file in court.
If AI is making their lives miserable on the inside as well, I fully support it.
I think Insurance Claims Adjusters as a occupation was on decline for some time even before the latest boom in AI. Since 90s I believe the most of major Insurance companies shifted a strategy, claims are seen as a source of profit and adjuster are now seen as a nuisance that often increase the payout for claims, so their role were diminished to form-fillers in different software systems.
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[ 0.26 ms ] story [ 8.9 ms ] threadYeah sure. I mean, same reason why HN readers hate AI, right? It replaces their jobs.
(Obviously the difference is that the poor old claims adjusters didn't spend the last two decades "disrupting" every other industry and telling everyone else to "learn to code". Ha! If you hear a faint high noise, that's the sound of the rest of the world playing a violin, made of highly disruptive nanomaterials.)
https://www.hawley.senate.gov/hawley-chairs-hearing-that-exp...
The California Department of Insurance characterized State Farm's tactics as "burying survivors in red tape at the worst moments of their lives"
https://www.insurance.ca.gov/0400-news/0100-press-releases/2...
Indeed, some of the core violations could be simply mandated as part of the inviolable system guardrails of an LLM - e.g. failed to begin investigating claims within 15 days, failed to accept or deny claims within 40 days, and failed to pay accepted claims or provide written notice of the need for additional time within 30 days, as required by law.
And at the end of the day, whatever weighting issues an LLM for Insurance Claim Adjustment has, it certainly won't steal the money and run off to a Casino with it
https://www.nicb.org/news/regional-news/broward-insurance-ad...
Anecdotally, many of them are aging out and the demands of adjusters are increasing while the pay hasn’t necessarily gone up. While technically you don’t have to know the ins and outs of construction, it helps a lot and there are just not a lot of people who have that knowledge. And if they do, they often go into construction themselves or sell roofs. Both of which can be far more lucrative.
On top of that, claims software has a lot of automation but very little real AI surface area. A lot of the things AI is good at (text generation) must have certain verbiage or use legally approved templates.
Granted, this may not be the case for all verticals, but this is just my observation from 20 years. (Mostly in smaller IA firms and state-based institutions).
Also, my wife has pointed out that there haven’t been any major cats in the last few years. Katrina kept people working for years. A lack of big storms has also contributed to this.
> Anecdotally, many of them are aging out
Ageing and out and neither being replaced directly or reduce numbers coming in at the bottom/mid as others move up, is still a drop in people. If part of the reason there is less need to bring people in lower down is that a few are being expected to do the work of a few more due to automation via AI, then that is AI replacing them, just not quite as directly as “we need less people as AI makes each more efficient so there are redundancies”.
There isn't a whole lot of room for automation in much of this.
Underwriting on the other hand, that is a different story.
Except shit, amoral behavior, backstabbing, lying at all times, just to get those sweet money and power.
I don’t know if I fully blame my executives for buying Microsoft Teams when Microsoft Teams turns out to suck. Microsoft promised to my company’s executives that Microsoft Teams doesn’t suck just like Sam Altman promised that AI is so powerful and so capable of exceeding the capabilities of humans that it’s dangerous.
Nobody is forcing you to take poison, and saying "Well Microsoft promised me it isn't poison!!!" at this point, decades into it selling poison, doesn't make much sense.
Literally anyone off the street can be a "decision maker" in technology today. Just buy what everyone else is buying and collect a huge paycheck while working remote. People who understand tech and sort of know what they are doing, are not included.
That has been my experience.
When he asked me to email him scans of a bunch of personal documents, I asked him for his PGP key.
..."What's that?"
Of course, if insurance companies were rapidly held to account by courts, a core function of the courts if there ever was one, there would be no problem here.
Which is probably why most governments are defunding the courts.
Somehow the "accountability" shifted from meaning "being reaponsible for not defrauding, lying" into "it is fault of people who were lied to".
It's like a person voting for Trump the second time being confused at all his lies, at this point basic education would get you out of this.
Pretty much what this blog post says: https://hermit-tech.com/blog/ai-mania-is-eviscerating-global...
It seems pretty bad, no doubt about it
This is what they depend on actually. Scape goats for their failures. This quarter takes a hit then number go up.
If so, yes, they are to blame, either for not being able to evaluate the stuff they buy or for deciding on questions they are not qualified for. Either one is incompetence.
You can also blame them to continue renting the thing (because it's not brought) after it's shown to be defective. And if they decide to do irreversible transformation to your business before verifying that the thing even works, than yes, that's bare incapacity of running a company.
Half my colleagues are besotted with the technology and unaware that it is shaping their decision making, not the other way around.
Hard to fathom a modern model would get any of this basic stuff wrong. I know accountants using it for (a lot more complex but similar problem) tax law parsing and it going through flawlessly.
There seems to be some bidirectional media gaslighting happening here where the doomers and glazers are talking past each other a bit.
You can't 'blame' the AI, as it can't be held accountable.
That makes it way more likely that people blame AI (doesn't make it right by any means, but does mean that the actual blame gets diffused even more).
1) employee was willingly sabotaging the company: employee gets jail time plus fine, employer is on the hook financially
2) employee was involved either in accident or just made a stupid decision: employer is on the hook financially
So if that's the case, then employers are financially responsible for everything the AI they use says.
Of course, guaranteed that governments will change this the first time a court makes this obvious connection.
In order to learn and improve you have to know what went wrong, with AI being personified and pulled into the pool of entities that may be at fault, it makes it harder to figure out what actually went wrong and learn. Not impossible to figure out, just harder.
Seems like more of a semantic distinction IMO. Yes, I can't technically "blame" the AI because it's not accountable. But what word would you suggest for "I had [X technology] handle [Y task] and it failed to perform that task?" I can't "blame" my router if I lose internet and it prevents me from jumping on a Zoom call, but it's also true that the router failed to do the thing it was supposed to do.
When my internet goes down, I blame either my ISP for having an outage, or the manufacturer of my router (assuming it's a router issue? Haven't had that happen personally but I'm certain it exists) (Or i did something dumb with my ufw again but that's on me)
If you create an autonomous system and it fails, blame should be on you, imo.
The word is still 'blame', it just needs to be applied correctly.
LLMs aren’t there yet, but they might get there. My point is that your descriptions fail to capture when or why exactly the blame would shift.
So they Google "Insurance claim AI tool", land on a vibecoded SaaS that is just a wrapper on a pocket Chinese model spun as "your next insurance pro", and then are getting the whole department on some lone 19 yr olds weekend project.
Another part of the problem is that a model not specifically fine-tuned to make a total loss determination won't know the relevant factors, nor how an insurance company's concept of a total loss differs from the public's.
And still another part of the problem is that most total loss claims aren't what you, dear reader, are imagining: They are very rarely "the car is a thin pancake after being crushed by a meteor".
The much, much more common scenario is: "50% of the body panels sustained at least paint damage, both headlight modules need replacement, and the front wheels look funny. Given that the vehicle has an MSRP of $FOO, $BAR miles, no prior collision history on carfax, and is a popular color, is it cheaper to repair or total the vehicle?"
Of course, the model can turn over the hard cases to a human adjuster... but then what are we doing here? It only takes 10 seconds for the human adjuster to handle the "crushed by a meteor" case also.
Source: Listening to my SIL rant about being asked to stop training bespoke total loss models and just send it by 1-shotting a commercial LLM.
Not saying they're not good for other things, but the "waste people's time and make them go away" use is just so perfect for the capabilities of even cheap models.
The article is entirely about the AI doing the first pass of the claim intake and causing a lot more work for everyone involved instead. Mis-routing, mis-categorization, hallucinating details, etc.
They are using the cameras to catch fraud (where claimants try to lump previous damage with damage covered by the current claim.), etc.
They tried to lowball me on my payout (they totaled my truck).
I hired SnapClaim for $350 to mediate it.
They got $1,000 more against State Farm ($650 net to me)
Don't let State Farm or any other insurance co lowball you.
It used to be you just email them a photo or video of the issue and they send you a replacement. Now companies won’t send one until they have received the defective one back.
Now I am in the claims process with the large insurance co., using Claude to basically run my side of the claim — reading the policy, organizing and filing the ALE receipt scans, reading and notifying me of messages from the agents, calling out when they are delaying too much or not fulfilling their promises, challenging their decisions on what to cover based on the policy, keeping a log of all of our correspondences, logging work estimates and invoices, I cant imagine doing all this tedious work myself—w/o Claude I’d probably just rollover fatigued.
Does my adjuster like this? On the one hand, I’m giving her incredibly tidy and documented receipts and logs, which I am sure is saving her time.
On the other hand, Claude is calling out her BS and delays, which have been atrocious—so much so that Claude is now adamant that she has gone too far and that I should be filing a complaint with the state insurance bureau.
This is an interesting customer strategy. Have you escalated your concerns to her management? Have you explained to her that you are considering filing a complaint with the state insurance bureau? It's the ol' stick vs carrot. I say: Start with the carrot. If that doesn't work, back to the stick!
People have no idea how inefficient the U.S.’s healthcare system is. And it isn’t just the private companies. A ton of states purposefully overburden and underfund their Medicaid systems for ideological reasons. Then the private insurance companies adopt the same practices later.
Then her client doesn’t get the help they need? That should be obvious.
> This seems like an open-and-shut case with the US Dept of Labour.
Even if it wasn’t for the “u” in labor I could tell you don’t live in the US.
Otherwise the situation is more complex than the original comment suggests, and I can only speak to one state (Idaho), but I don't think the scenario is uncommon in other GOP controlled states and isn't limited to Medicaid.
Idaho has cut taxes in the state for five consecutive years, largely (IMO) on an ideological basis. This had the result, desired by many in a deeply conservative legislature, of creating budget deficits. Even the GOP is normally wary of espousing cuts directly to the state's contribution to Medicaid, but the deficit gives them cover to reduce funding and introduce barriers to service like caps on authorized services and new work requirements. Even when revenues were higher than expected for FY 2026, the governor's office had to act to actually retain those unexpected revenues as it was pretty clear that the Legislature was going to look to claw them back and continue drive down State spending. It's worth noting that health services, including Medicaid funding, represent about a third of the State's budget and their largest portion of the budget.
This whole process has been playing out in public education funding in the State for years as well. Coincidentally, charter school enrollment has increased by roughly 35% over the same 2021 - 2026 period.
Attacking a policy, program or institution financially and then pointing to the deficiencies of those same programs to further fuel funding and efficacy reductions is a pretty well established tactic in US politics as I'm sure it is elsewhere.
Depending on the competition for her job and the state laws, she would either be put onto a performance management program, or fired. I've been through this before. The HR approved response is that they expect those 100-page reports to be complete within normal working hours, and a failure to achieve that means you are unable to fulfill the requirements of the job.
Of course those in high demand who can easily move to better employers will often do so. However there is a lot of friction when moving jobs. It's very time consuming, mentally demanding, and risky. I've seen incredibly talented staff treated awfully in my years, and they refuse to leave for various reasons.
EDIT
This part should have appeared first: I agree that your scenario is the most likely outcome, even if I think it is reprehensible!
It was precisely because of AI that I had the time and language to fight a recent claims report for a totaled vehicle, and squeezed an additional 25% from them. And it was still not adequate payout.
Let claim adjusters and insurance get off their high horse until they start being the bane of existence and paying what they owe clients.
Secondly, does anyone actually know how much of your insurance premium is going on the call centre staff? most people don't claim, those that do mostly have simple claims. The actual cost for insurance companies is actually paying out claims, so even if you automated all of this it likely doesn't change your economics. Historically "New" Insurance companies only really succeed by mis-pricing risk and gaining market share that way - they often then fail when that risk materializes. Lemonade sounds a lot like that.
Finally, they haven't engaged with the tidal wave that's coming. Sure, AI agents handling claims is happening now. Just you wait. In a couple of years time it'll be AI agents making the claims for you and suddenly there'll be bots filing claims with infinite patience and a direct mandate to try and get as big a payout as possible. That is when it's going to get really hairy.
Yup - by checking your Claude usage meter.
And all the while these crooks are claiming it's so humans can focus on more important things. Yeah right. If we're lucky, AI won't improve and there will be a huge backlash, like outsourcing in the early 2000s. If AI gets better, actually good enough to do most work currently done by humans, well then probably something really ugly happens.
Yes it's ALSO to a promote a book, but still... there's a lot more to it than just mindlessly raging against a new technology.
[1] https://99percentinvisible.org/episode/552-blood-in-the-mach...
When your business model has gotten to the point where people cheer for a guy who murdered one of their CEOs, it’s not surprising that people would not be interested in joining and may see being murdered as an occupational risk beyond what their personal actuarial tables allow.
On the outside, I was able to use a consensus model to reach a successful settlement. I wouldn’t say I won, but was made whole after having to file in court.
If AI is making their lives miserable on the inside as well, I fully support it.
The flood of nonsensical AI slop applications that HR is facing has forced this.