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95% of Companies See 'Zero Return' on $30B Generative AI Spend

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Re: 95% of Companies See 'Zero Return' on $30B Generative AI Spend

#201
post #86
post #56

Full disclosure: I'm currently in a leadership role on an AI engineering team, so it's in my best interest for AI to be perceived as driving value. Here's a relatively straightforward application of AI that is set to save my company millions of dollars annually. We operate large call centers, and agents were previously spending 3-5 minutes after each call writing manual summaries of the calls. We recently switched to…

Pro-tip: don't write the summary at all until you need it for evidence. Store the call audio at 24Kb/s Opus - that's 180KB per minute. After a year or whatever, delete the oldest audio. There, I've saved you more millions.

Imagine a follow-up call of a customer. They are referring to earlier calls and the call center agents needs to check what it was about. So they can skim/read the transcripts while talking to the customer. I guess it's really hard to listen to transcripts while you're on the phone.

Re: 95% of Companies See 'Zero Return' on $30B Generative AI Spend

#202

What are the actual use cases that can generate revenue or at least save costs today? I can think of: 1. Generate content to create online influence. This is at this point probably way oversaturated and I think more sophisticated models will not make it better. 2. Replace junior developers with Claude Code or similar. Only sort of works. After all, you can only babysit one of these at a time no matter how senior you…

I am working on a project that uses LLM to pull certain pieces of information from semi-structured documents and then categorize/file them under the correct account. it's about 95% accurate and we haven't even begun to fine tune it. i expect it will require human in the loop checks for the foreseeable future, but even with a human approval of each item, its going to save the clerical staff hundreds of hours per year.…

All of the AI projects promise that they just need some fine tuning to go from poc to actual workable product. Nobody was able to fine tune them.

Sorry this is some bull. Either it works or it doesn’t.

Re: 95% of Companies See 'Zero Return' on $30B Generative AI Spend

#203

Earlier quoted context omitted.

Because it's going to destroy knowledge work and the entire middle class.

I thought we hated doing the menial office jobs though.

Maybe spoiled brats did. I like "menial" office jobs a lot more than starving or doing humiliating acts on OnlyFans to pay my bills, which is the future we're barreling toward.

What menial about knowledge work, anyway?

Re: 95% of Companies See 'Zero Return' on $30B Generative AI Spend

#204

Earlier quoted context omitted.

Given that people skimp on work that is viewed as trash anyway, how were you getting value out of the summaries in the first place?

they weren't its likely a checkbox for compliance or some policy a middle manager put in place that is now tied to a kpi

Could be CRM, leaving summaries for the next person. I suppose it would sound like I'm implying a prior.

Re: 95% of Companies See 'Zero Return' on $30B Generative AI Spend

#205
post #86
post #56

Full disclosure: I'm currently in a leadership role on an AI engineering team, so it's in my best interest for AI to be perceived as driving value. Here's a relatively straightforward application of AI that is set to save my company millions of dollars annually. We operate large call centers, and agents were previously spending 3-5 minutes after each call writing manual summaries of the calls. We recently switched to…

Pro-tip: don't write the summary at all until you need it for evidence. Store the call audio at 24Kb/s Opus - that's 180KB per minute. After a year or whatever, delete the oldest audio. There, I've saved you more millions.

Sentiment analysis, nuanced categorization by issue, detecting new issues, tracking trends, etc, are the bread and butter of any data team at a f500 call center.

I'm not going to say every project born out of that data makes good business sense (big enough companies have fluff everywhere), but ime anyway, projects grounded to that kind of data are typically some of the most straight-forward to concretely tie to a dollar value outcome.

Re: 95% of Companies See 'Zero Return' on $30B Generative AI Spend

#206

One thing I ponder after remembering previous tech booms, is that they often left behind something extremely valuable (fiber). With all the GPU datacenters rolling out, what next bubble can take advantage of this boon, if it is one?

It will probably all be used to mine bitcoin.

Re: 95% of Companies See 'Zero Return' on $30B Generative AI Spend

#207
post #56

Full disclosure: I'm currently in a leadership role on an AI engineering team, so it's in my best interest for AI to be perceived as driving value. Here's a relatively straightforward application of AI that is set to save my company millions of dollars annually. We operate large call centers, and agents were previously spending 3-5 minutes after each call writing manual summaries of the calls. We recently switched to…

I wouldn't allow myself to be held accountable for anything in a summary I didn't write.

Re: 95% of Companies See 'Zero Return' on $30B Generative AI Spend

#208
My guess is that this title could also be written as, “The value of AI projects are being captured by just 5% of companies.”

It’s pretty clear to anyone who’s using this technology that it’s significant. Theres still tons to work out and the exact impact is still unknown. But this cat isn’t going back in the bag.

Re: 95% of Companies See 'Zero Return' on $30B Generative AI Spend

#209

Earlier quoted context omitted.

you want to be able to search over summaries so you need to generate them right away

Pro-tip: You won't ever do that.

I would imagine OP is probably mining service call summaries to find common service issues, or at least that's what I would do.

Re: 95% of Companies See 'Zero Return' on $30B Generative AI Spend

#210

What are the actual use cases that can generate revenue or at least save costs today? I can think of: 1. Generate content to create online influence. This is at this point probably way oversaturated and I think more sophisticated models will not make it better. 2. Replace junior developers with Claude Code or similar. Only sort of works. After all, you can only babysit one of these at a time no matter how senior you…

One use case I'd love to see an easy plug-and-play solution for is a RAG build around companies vast internal documentation/wikis/codebase to help developers onboard and find information faster. I would love to see less of people trying to replace humans with language models and more of people trying to use language models to make humans jobs less frustrating.

In all the companies I have worked at and have looked at such docs, unfortunately this doesn't really work because those internal documentation sites are statistically never up to date or even close. They are hilariously unclearly written or out of date.

As for relying on the code base, that is good for code, although not for onboarding/deployment/operations/monitoring/troubleshooting that have manual steps.

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