Anyone firing employees because they thought that AI would do their jobs in 2025 should be fired. It really doesn’t take much research to see AI isn’t at the place where it’s replacing people – yet. And business managers – particularly in small and mid-sized companies – who think it is better think again.
At best, generative AI platforms are providing a more enhanced version of search, so that instead of sifting through dozens of websites, lists and articles to figure out how to choose a great hotel in Costa Rica, fix a broken microwave oven or translate a phrase from Mandarin to English, we simply ask our chatbot a question and it provides the best answer it finds. These platforms are getting better and more accurate and are indeed useful tools for many of us.
But these chatbots are nowhere near replacing our employees.
It’s somewhat akin to claiming that now that we have hammers, carpenters aren’t needed.
I don’t think LLMs will ever replace a single worker.
Companies that care about quality cannot replace workers with LLM.
Problem is some “executives” think they can save cost by “AI”, and they are trying.
They’re going/are replacing workers - the problem is they’re going to make someone else do more work and check/fix the output.
In the end, there won’t be any cost savings (or frankly, even any “productivity”) - just another tool companies pay for because every other company uses it.
That’s the problem. I am already seeing AI slop in my area of work. And they usually need heavy clean up. In the end, its not saving any time.
It almost certainly already has replaced several.
Also, AI is not synonymous with LLM.
AI can replace management, they are about the most least useful in a company.
Has it actually replaced them?
Sure maybe some people have lost their jobs, but I don’t think they’ve really been replaced.
It’s closer to laying someone off without replacement … because evening I’ve seen has suggested AI not only can’t do the work but it also doesn’t improve the productivity of workers using it in any meaningful way.
I’d argue that’s all AI means anymore if it has any meaning left at all.
The term artificial intelligence is broader than many people realize. It doesn’t refer to a single technology or a specific capability, but rather to a category of systems designed to perform tasks that would normally require human intelligence. That includes everything from pattern recognition, language understanding, and problem-solving to more specific applications like recommendation engines or image generation.
When people say something “isn’t real AI,” they’re often working from a very narrow or futuristic definition - usually something like human-level general intelligence or conscious reasoning. But that’s not how the term has been used in computer science or industry. A chess-playing algorithm, a spam filter, and a large language model can all fall under the AI umbrella. The boundaries of AI shift over time: what once seemed like cutting-edge intelligence often becomes mundane as we get used to it.
So rather than being a misleading or purely marketing term, AI is just a broad label we’ve used for decades to describe machines that do things we associate with intelligent behavior. The key is to be specific about which kind of AI we’re talking about - like “machine learning,” “neural networks,” or “generative models” - rather than assuming there’s one single thing that AI is or isn’t.
A lot of people have been working tedious and repetitive “filler” jobs.
spammerssalespeople, basic customer support, HR personnel, etc.In the near future, AI-controlled robots are going to start replacing low skilled labor, then intermediate skilled ones.
“AI” has the meaning of machines replacing what used to require humans to perform. It’s a moving goalpost: once one is achieved, we call it an “algorithm” and move to the next one, and again, and again.
Right now, LLMs are at the core of most AI, but AI has already moved past that, to “AI Agents”, which is a fancy way of saying “a loop of an LLM and some other tools”. There are already talks of moving past that too, the next goalpost.
Meanwhile companies keep pushing “AI” (as in, LLMs integrated with image/video generation, STT and TTS, networking, file generation and reading, etc.), as traditional, useful ML, built for one purpose and fulfilling that purpose at least well, sinks into irrelevancy.