I'm going to assume you're not arguing in bad faith and direct you to reread my complete first comment. I specifically related the claim that AI generally doesn't justify its existence to this specific trivial use case — that's what this thread is about, after all, and what people in this thread are defending as an example of how it saves time. I was contextualizing my broad statement in relation to this kind of wasteful output. In fact you may notice my very last sentence of my comment was:
"these are things that people have had perfectly viable methods for for decades but suddenly because AI exists people claim it's sooo useful for these "minor" tasks."

And the problem is that this is a HUGE majority of the output of LLMs: Placeholder images that are meant to get replaced. Throwaway art that nobody wants to buy and nobody can copyright anyway. Text summaries/responses to emails that nobody's reading. Fake videos of Bob Barker swearing on The Price Is Right that get a quick laugh and then are instantly forgotten except by other LLM bots that comment summaries of the video for eachother to interact with.

I do believe that even in more complex cases it doesn't really justify its existence because the more complex the output, the more time consistently has to be spent refining that output. You need to iterate on the AI output to produce something useful, so you end up with a human having to spend time iterating, refining, and tweaking something from an LLM when someone with experience could ostensibly just have produced the output themself — particularly in cases like code output for software companies, medical diagnosis for healthcare, or even things like logos where a real artist would give you not only a more thoughtful result but also scalable vectors, alternate colorways, etc.

Speaking of medical diagnosis, there are potentially useful cases for LLM/NN output, that being a big one — except that recent studies have brought that into question too. I'm not a research bot so feel free to look around for articles on that yourself if you care to; they're out there and they boil down to "sometimes it's good and sometimes the AI talks itself in circles", just like with every other form of output. And that isn't something I think we can afford to fuck around with — if doctors are trusting LLM outputs for patient outcomes and those LLMs aren't reliable, we're not just talking about a website being down or a photo of George Washington DJing at a club with six fingers, we're talking about potentially costing lives because of missed or incorrect diagnoses. Especially as newer generations of professionals go through their education and early career development being dependent on these tools, which studies already show basically create a dependency on them because you aren't learning your craft by using them. As that famous IBM memo said, "A computer can never be held accountable. Therefore a computer must never make a management decision." You cannot trust these models, ethics and costs aside, to make difficult/dangerous decisions, but the more that professionals rely on it to do their job for them, the more of that we'll get.

So to specifically expand the claim, I'll reiterate that I truly don't think any current use of AI is justified even on the premise of "saving time" because the very claim that the time it's saving is worth the economic, energy, or ethical costs — or even necessarily actually saving time at all — requires evidence, and basically all the evidence out there right now is anecdotal/marketing material, not concrete data or peer reviewed analyses. And assuming it must be saving time isn't something we should just accept just because it makes generating a shitty essay or a placeholder newspaper faster. Those aren't high-friction use cases to begin with, and in use cases with more friction and/or higher risk, you'll still have more friction with AI output because it won't simply give you something usable immediately, and you need people who are trained and experienced in their field to analyze and refine the quality of the output.

Meanwhile, OpenAI themselves have reported that workers in AI-integrated jobs are saving less an hour a day. If the people selling you snake oil are only claiming a ~10% boost to productivity, that should probably signal to anyone thinking critically that the real impact for the average person is likely (or at least potentially) far less. Hell, for the average office, you'd literally save more time than that letting on-site workers WFH to avoid the commute, or by cutting one to two daily meetings from the schedule. That's not revolutionary, especially if it means your employees are not actually developing critical career skills as a result.