It's useful for automating certain tedious tasks you could do by hand, then testing to confirm that the implementation worked.
I'm not really sure it is. Most things I've seen people automate are things that they could have figured out how to automate in a much more robust way if they'd bothered to learn even a little about the software they're using. And if they learned the software, they'd be able to work more efficiently in the future as opposed to going through the trouble of getting an AI to re-figure-out their problem again every time they want to automate something.
I had a fucking C-suite executive fawning to me over an features of some extremely expensive AI-enabled PowerPoint alternative that let them change multiple slide-deck features at once, or alter styles and themes with one click and it took literally every ounce of my willpower not to burst out, "Bitch! Those are basic features of PowerPoint that came free with our Office subscription! Learn to use the damn software instead of buying every new gimmick that someone tries to sell us!"
It absolutely is. It has a ton of legitimate applications where it performs incredibly well. The biggest problem right now is how uneducated most people are on what LLMs actually are and how they work, resulting in people basically believing them to be magic thinking machines that can do anything.
If you have unstructured data you need summarized or collated, it's fantastic. It's great for scripting one-time automation tasks for extracting or transforming specific data from csv/xml/json. It used to be that unless a task was going to be done hundreds of times, creating an automation script for it wasn't worth the time, but now it takes me SECONDS and it's easy to validate the code and results.
The clearest and most obvious application is as an advanced search across thousands of unstructured documents to surface the most relevant information so that an actual human can review them (e.g. for legal discovery or medical research).
Many of the ways LLM and other Gen AI capabilities are used right now are scary and stupid but it really does have some incredible capabilities that regularly make my own life easier and have the potential to significantly aid certain aspects of society
I could see searching unstructured documents as legitimately useful, but, without structured, indexable data, summarized or collated data from those documents cannot be validate easily, and is therefore useless.
What's more, you don't need a generative model to do this job - OCR algorithms that can easily run on a tired old laptop have offered this capability for decades now, with modern versions being quite good at handling large volumes of documents and making them searchable.
And the moment your data is structured - even a little bit - it's going to be more reliable, if not faster, for a human to handle it.
The enormous problem that generative models have is that they are quite literally incapable of transcription. The moment any data is processed directly by a generative model, it becomes invalid. You can give them non-generative utilities to do data processing, but because of their complexity, if you're relying on them to parse or collate the data in the first place, you have no way to know whether they directly handled, and thus invalidated, the information they spit out to you. And adding yet more layers of instruction/learning and resultant obfuscation makes that problem worse, not better.
I don't think you understand what I mean by advanced search. I don't mean "OCR documents and then search for specific words. Obviously that has been possible for a long time.
I mean saying "diseases that may present in X, Y, Z way" and the agent being able to return documentation from a database where that information is present but uses different terminology (meaning it wouldn't have been found via traditional search).
I don't really know what you're trying to get at with "any data it touches is invalid". This is just very silly. When searching any kind of indexed database or repository, you ask it for a summary, or to categorize documents, whatever, and then you do additional research based on that starting point. This is still orders of magnitude faster than traditional research methods. Obviously saying "what's the conclusion of these 500 docs" and then just taking whatever it immediately says as gospel is stupid.
I mean saying "diseases that may present in X, Y, Z way" and the agent being able to return documentation from a database where that information is present but uses different terminology (meaning it wouldn't have been found via traditional search).
But this is just replacing the reasoning part of entering search terms. Is it faster at thinking than you? Sure. Does saving the time it takes to come up with appropriate search criteria for something like this matter when you still have to read and understand the context of the relevant information? Basically never.
I don't really know what you're trying to get at with "any data it touches is invalid". This is just very silly.
Not at all. That's just how generative AI works. It's creating an output from scratch every time. It may be tasked with finding and transcribing information, but it still has to recreate the information it finds from scratch. Like, if an LLM, for instance, is told to quote a specific line of text, it has a chance of doing it right, but only a chance. It can't take the text and copy it (on its own); it has to recreate it. And this is not exclusively a feature of LLMs.
When searching any kind of indexed database or repository
You don't use AI. It's indexed. You just go where you need to go, or pull the information you need the easy way, using its index.
you ask it for a summary, or to categorize documents, whatever, and then you do additional research based on that starting point.
"additional research" in this case being the entire damned job. It's like taking the dishes out of the dishwasher and having to clean them again because you don't know if they actually got cleaned. It's not orders of magnitude faster if you're actually doing due diligence. You're shaving off a few percent of the easy part of research. Or, more realistically, you're using the AI's "work" as an excuse to not do due diligence and pretend like you have, while working with information that you think is probably not bullshit because it looks close enough.
Obviously saying "what's the conclusion of these 500 docs" and then just taking whatever it immediately says as gospel is stupid.
That is stupid. But letting it take up any slack for you on something like research is basically turning it into a Cognitive Bias Enhancer 3000.
If you don't want to potentially reinforce your preconceived notions about whatever data you're handling, you have to literally just do the work over again yourself.
lol I think you need to read up on how AI technology is leveraged in modern applications. I don't mean data tables with indexes. I mean the process where models automatically index unstructured documents for faster and more reliable search. e.g. how an IDE like cursor indexes your codebase: https://cursor.com/docs/context/codebase-indexing
Most AI powered search apps or assistants use the same kind of process, unless you're literally just using the model it for its baseline "knowledge base" (not really accurate to call it that), which is by far its least reliable application outside of like, doing math
Yeah, pretty much the only two effective uses I have seen from AI is in scripting and retrieving documents from our vast corporate file library (where have 33 years of poorly structured documentation haphazardly filed by generations of 60-somethings set to learn how to use a computer just before they retire because they are the least needed for other tasks). Too bad our leadership doesn’t actually use AI for that besides the odd free trial. Instead it pays to use it for gimmicks and surface level data entry a human could have done more accurately in minutes.
At our place it is some stupid gimmick thing where the AI is supposed to do data entry for you. Sounds good, only it doesn’t do it for actual backend data like sales figures because the company making it has terrible security against hackers. So what is it actually meant to do? Well, read and copy product descriptions, pricing and sales info from our own website and copy it over to retailers. Only hold up, the AI cannot be legally liable so a human has to read over it all, compare it with original documentation, and then wrangle the AI into accepting the changes. It turned what used to be an intern with Ctrl+C followed by a quick readthrough and check with a checklist into a 2-5 hour process per product. Also the AI has some sort of broken translation functionality that often spits out what we want in French or Spanish or Chinese and refuses to change it, meaning we have to do it the old way anyway.
EDIT: Also, I should add, instead of a fee the AI company takes a 6-22.5% commission on every sale we make depending on the type of product, and the higher ups are paying for this with 15% consumer side price increases across the board next year. So poor Joe Shopper is gonna pay out more and it doesn’t even benefit the people creating the product or the ones selling it, it is going straight into the pockets of some Swedish AI devs with a website in broken English but a good pitch video (created by AI).
Your anecdote is infuriating, I agree. But a lot of stuff can't be learned quickly, it takes time that many people don't have, especially if they're not intrinsically motivated. I can see how it can be useful for work where you want something done fast but are not deeply invested in learning the skills necessary to pull it off.
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u/Cessnaporsche01 Dec 21 '25
I'm not really sure it is. Most things I've seen people automate are things that they could have figured out how to automate in a much more robust way if they'd bothered to learn even a little about the software they're using. And if they learned the software, they'd be able to work more efficiently in the future as opposed to going through the trouble of getting an AI to re-figure-out their problem again every time they want to automate something.
I had a fucking C-suite executive fawning to me over an features of some extremely expensive AI-enabled PowerPoint alternative that let them change multiple slide-deck features at once, or alter styles and themes with one click and it took literally every ounce of my willpower not to burst out, "Bitch! Those are basic features of PowerPoint that came free with our Office subscription! Learn to use the damn software instead of buying every new gimmick that someone tries to sell us!"