[Yaina]

I think what we're seeing, and what the article describes, are company leaders across industries reacting to the AI hype by saying "we need AI too!" not because they've identified a specific problem it can solve, but because they want to appear innovative or cut labor costs.

Right now, the market values saying you're doing AI more than actually delivering meaningful results.

Most leaders don't seem to view AI as a practical tool to improve a process, but as a marketing asset. And let’s be honest: we're not talking about the broad field of machine learning here, but mostly about integrating LLMs in some form.

So coming back to the revenue claims: Greenhouse (the job application platform) for example now has a button to improve your interview summary. Is it useful? Maybe. Will it drastically increase revenue? Probably not. Does it raise costs? Yes; because behind the scenes they’re likely paying OpenAI processing fees for each request.

This is emblematic of most AI integrations I've seen: minor customer benefits paired with higher operational costs.

[bongodongobob]

That's exactly it. We are using AI to reformat all of our documentation... And they we've been told to review the output. No one asked for this, there are no benefits, and it's adding completely unneeded extra work.

[fragmede]

Would you feel the same way if they'd hired a human technical writer to generate documentation and you had to review the output?

[bongodongobob]

Yes, because our documentation is fine. No one thinks any changes need to be made. Leadership is realizing all their AI hype has no benefit to anything we do so they're scrambling to find projects to use it for.

[bdbdkdksk]

The Greenhouse example is so crazy - with no additional context about the interview, what possible value could an AI add to a summary of a real event that happened?

[Yaina]

It's just an additional button in their WYSIWYG editor. I'm sure its not much more than a simple prompt telling ChatGPT or whatever to clean up the text for clarity.