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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

#161

Post by biophysboy »

jampa wrote: post #42

The biggest mistake people are making is treating AI as a product instead of a feature. While people are doing their work, they don't think, "Oh man, I am really excited to talk with AI today, and I can't wait to talk with a chatbot." People want to do their jobs without being too bored and overwhelmed, and that's where AI comes in. But of course, we cannot hype features; we sell products after all, so that's the sta…

1000% agree, so many AI "applications" right now are solutions looking for a problem.

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

#162

Post by smohare »

dsr_ wrote: post #86
jawns wrote: 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.

[dead]

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

#163

Post by seatac76 »

JCM9 wrote: post #16

We are entering the “Trough of disillusionment.” These hype cycles are very predictable. GPT-5 being panned as a disappointment after endless hype may go down as GenAI’s “jump the shark” moment. It’s all fun and games until the bean counters start asking for evidence of return on investment. GenAI folks better buckle up. Bumps ahead. The smart folks are already quietly preparing for a shift to ride the next hype wave…

Good point. I wonder if the Windsurf folks saw the writing on the wall and cashed out when they could.

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

#164

Post by systemerror »

spogbiper wrote: post #76
IgorPartola wrote: post #34

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.…

The big issue with LLMs is that they’re usually right — like 90% of the time — but that last 10% is tough to fix. A 10% failure rate might sound small, but at scale, it's significant — especially when it includes false positives. You end up either having to live with some bad results, build something to automatically catch mistakes, or have a person double-check everything if you want to bring that error rate down.

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

#165

Post by lubesGordi »

lenerdenator wrote: post #55
highwaylights wrote: post #28

Earlier quoted context omitted.

I wouldn’t be surprised if 95% of companies knew this was a money pit but felt obligated to burn a pile of money on it so as not to hurt the stock price.

I also wouldn't be surprised if bean counters were expecting a return in an unreasonable amount of time. "Hey, guys, listen, I know that this just completely torched decades of best practices in your field, but if you can't show me progress in a fiscal year, I have to turn it down." - some MBA somewhere, probably, trying and failing yet again to rub his two brain cells together for the first time since high school. J…

Agreed agentic coding is a huge change. Smart startups will be flying but aren't representative. Big companies won't change because the staff will just spend more time shopping online instead of doing more than what is asked of them. Maybe increased retail spend is a better measure of AI efficacy.

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

#166

Post by deepdarkforest »

quotemstr wrote: post #124
frozenport wrote: post #38

Earlier quoted context omitted.

Yo what’s the next hype cycle that smart folks like us should be working on?

Defense will increasingly become a national priority over the next few decades. Pax Americana is teetering.

That and consumer robotics. The latter will explode if (big if) RL and llm reasoning get combined into something solid. Lots and lots of smart people are working on it already of course, we are seeing great improvements but nothing really usable. i think we will finally get to a real hype stage in maybe 3-4 years

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

#168

Post by krainboltgreene »

alooPotato wrote: post #152
dsr_ wrote: post #86

Earlier quoted context omitted.

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.

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.

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

#169

Post by jcims »

vasco wrote: post #70
jawns wrote: 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 wonder if the human agents agree the AI summaries are better than their summaries. I was nodding as I read and then told myself "yeah but it wouldn't be able to summarize the meetings I have", so I wonder if this only works in 3rd person.

I built a little solution to record and transcribe all of my own meetings. I have many meetings (30hr week+) and I can't keep pace with adequate note-taking while participating in them all.

I'm finding that the summarization of individual meetings very useful, I'm also finding that the ability to send in transcripts across meetings, departments, initiatives whatever to be very effective at surfacing subtexts and common pain points much more effectively than I can.

I'm also using it to look at my own participation in meetings to help me see how I interact with others a (little) bit more objectively and it has helped me find ways to improve. (I don't take its advice directly lol, just think about observations and determine myself if it's something that's important and worth thinking about)

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

#170

Post by doorhammer »

Shank wrote: post #99
jawns wrote: 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…

Who reads the summaries? Are they even useful to begin with? Or did this just save everyone 3-5 minutes of meaningless work?

Not the op, but I did work supporting three massive call centers for an f500 ecom.

It's 100% plausible it's busy work but it could also be for: - Categorizing calls into broad buckets to see which issues are trending - Sentiment analysis - Identifying surges of some novel/unique issue - Categorizing calls across vendors and doing sentiment analysis that way (looking for upticks in problem calls related to specific TSPs or whatever) - etc

False positives and negatives aren't really a problem once you hit a certain scale because you're just looking for trends. If you find one, you go spot-check it and do a deeper dive to get better accuracy.

Which is also how you end up with some schlepp like me listening to a few hundreds calls in a day at 8x speed (back when I was a QA data analyst) to verify the bucketing. And when I was doing it everything was based on phonetic indexing, which I can't imagine touching llms in terms of accuracy, and it still provided a ton of business value at scale.

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