The comment was definitely not LLM generated. However, I certainly did use search for help in sourcing information for it. Some of those searches offered AI generated results, which I cross-referenced, before using to write the comment myself. That in no way is the same as “an LLM-generated comment”.

For the benefit of external observers, you can stick the comment into either https://gptzero.me/ or https://copyleaks.com/ai-content-detector - neither are perfectly reliable, but the comment stuck out to me as obviously LLM-generated (I see a lot of LLM-generated content in my day job), and false positives from these services are actually kinda rare (false negatives much more common).

But if you want to get a sense of how I noticed (before I confirmed my suspicion with machine assistance), here are some tells: "Large firms are cautious in regulatory filings because they must disclose risks, not hype." - "[x], not [y]"

"The suggestion that companies only adopt AI out of fear of missing out ignores the concrete examples already in place." - "concrete examples" as a phrase is (unfortunately) heavily over-represented in LLM-generated content.

"Stock prices reflect broader market conditions, not just adoption of a single technology." - "[x], not [y]" - again!

"Failures of workplace pilots usually result from integration challenges, not because the technology lacks value." - a third time.

"The fact that 374 S&P 500 companies are openly discussing it shows the opposite of “no clear upside” — it shows wide strategic interest." - not just the infamous emdash, but the phrasing is extremely typical of LLMs.

It's popular now to level these accusations at text that contains emdashes.

The use of “ instead of ", two different types of hyphens/dash, specific wording and sentence construction are clear signs that the whole comment was produced by chatGPT. How much of it was actually yours (people sometimes just want LLM to rewrite their thoughts), we will never know but it's an output of an LLM.