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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 re

• ddddang 1y ago
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• zeromyte 1y ago
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• vasco 1y ago
  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.
  • deleted 1y ago
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  • dymk 1y ago
    Have you tried having it summarize the meetings you have?
  • mbStavola 1y ago
    Part of me also wonders if people may agree that its better simply because they don't actually have to do the summarization anymore. Even if it is worse by some %, that is an annoying task you are no longer responsible for; if anything goes wrong down the line, "ah the AI must've screwed up" is your way out.
    • roflc0ptic 1y ago
      I’m inclined to believe that call center employees don’t have a lot of incentive to do a good job/care, so a lossy AI could quite plausibly be higher quality than a human
      • freehorse 1y ago
        Also it should be easy to correct some obvious mistakes in less convoluted discussions. Also, prob a support call is less complex than eg a group meeting by many aspects, and with a prob larger margin of acceptable errors.
      • latexr 1y ago
        For many years now, every time I have to talk with someone on a call centre there has been a survey at the end with at least two questions: 1. Would you recommend us? 2. Was the agent helpful? I have a friend who used to work at a call centre and would routinely get the lowest marks on the first item and the highest on the second. I do that when the company has been shitty but I understand the person on the line really made an effort to help. Obviously, those ratings go back to the supervisor and matter for your performance reviews, which can make all the difference between getting a raise or being fired. If anything, call centre employees have a lot of incentive to do a good job if they have any intention of keeping it, because everything they do with a customer is recorded and scrutinised.
        • roflc0ptic 1y ago
          Fair point, though I think “did I accurately summarize a conversation” is much harder to check/get away with vs “did I piss off the person on the other end”
    • evereverever 1y ago
      That re-synthesis of information is incredibly valuable to storing it in your own memory. Of course, we can just rely on knowing nothing just to look things up, but I want more for thinking peoples.
  • jcims 1y ago
    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)
    • mjcohen 1y ago
      Make sure that is legal where you are and, if needed, you have their permission.
  • kenjackson 1y ago
    AI definitely summarizes meetings better than me and _almost_ anyone else I've seen do it (there is one exception -- one guy was a meeting note taker god. He was so good that he set up a mailing list because so many people wanted to read his meeting notes.) I could probably do better than AI if I really tried, but I've only ever done that a few times.
• doubled112 1y ago
  At work we've tried AI summaries for meetings, but we spent so much time fixing those summaries that we started writing our own again. Is there some training you applied or something specific to your use case that makes it work for you?
  • nsxwolf 1y ago
    We stopped after it kept transcribing a particular phrase of domain jargon as “child p*rn”, again and again.
  • cube00 1y ago
    Unless a case goes down the legal road, nobody is ever bothering to read old call summaries in a giant call center. When was the last time you called a large company and the person answering was already across all the past history without you giving them a case number first?
    • doubled112 1y ago
      Does an AI summary hold up in court? Or would you still need to review a transcript or recording anyway?
      • cube00 1y ago
        You can store low quality audio cheaply on cold storage so I suspect that's the real legal record if it got that far.
  • shawabawa3 1y ago
    My guess is that the summaries are never actually read, so accuracy doesn't actually matter and the AI could equally be replaced with /dev/null
  • mrweasel 1y ago
    We tried Otter.ai, someone complained and asked: "Could you f-ing not? I don't trust them" and now Otter is accused of training their models on recorded meetings without permission. Yeah, I don't even care if it works, I don't trust any of these companies.
• butlike 1y ago
  How can you double-check the work? Also, what happens when the AI transcription is wrong in a way that would have terminated the employee. You can't fire a model. Finally, who cares about millions saved (while considering the above introduced risk), when trillions are on the line?
  • throitallaway 1y ago
    I presume they're not using these notes for anything mission or life critical, so anything less than 100% accuracy is OK.
    • butlike 1y ago
      I disagree with the concept of affluvic notes. All notes are intrinsically actionable; it's why they're a note in the first place. Any note has unbounded consequence depending on the action taken from it.
      • wredcoll 1y ago
        You're being downvoted, I suspect for being a tad hyperbolic, but I think you are raising a really important point, which is just the ever more gradual of removing a human's ability to disobey the computer system running everything. And the lack of responsibility for following computer instructions. It's a tad far-fetched in this specific scenario, but an AI summary that says something like "cancel the subscription for user xyz" and then someone else takes action on that, and XYZ is the wrong ID, what happens?
  • PaulRobinson 1y ago
    Having a human read a summary is way faster than getting them to write it. If they want to edit it, they can. AI today is terrible at replacing humans, but OK at enhancing them. Everyone who gets that is going to find gains - real gains, and fast - and everyone who doesn't, is going to end up spending a lot of money getting into an almost irreversible mistake.
    • 1y ago
• pluc 1y ago
  You could do that offline 20 years ago with Dragon Naturally Speaking and a one-time licence.
  • dymk 1y ago
    You could get a transcript, not a summary
  • loloquwowndueo 1y ago
    Only if your audio was crystal clear, you spoke like a robot very slowly, and each customer has to do a 30-minute “please read this text slowly to train the speech recognition software” preamble before talking to the actual human.
• glimshe 1y ago
  This makes sense. AI is obviously useful for many things. But people wouldn't invest tens of billions to summarize data center calls and similar tasks. Replacing data center workers isnt where the money is - it's replacing 100K-200K/year workers.
• generic92034 1y ago
  > It's not going to replace anyone's job. Is it not, in the scenario you are describing? You are saying the agents are free now to do higher-value work. Why were there not enough agents before, especially if higher-value work was not done?
  • hobs 1y ago
    Because call centers are cost centers - nobody pays a dime more than they have to in these situations and its all commodity work.
    • generic92034 1y ago
      But that means the so-called "higher-value" work does not need to be done, so agents can be fired.
  • cube00 1y ago
    It's such a useless platitude. The "higher value work" is answer more calls so we can have less staff on queue.
    • c0nducktr 1y ago
      Exactly. The only thing this does is allows the company to have fewer staff while making the jobs of the few who remain worse. Great product, can't imagine why the general public aren't thrilled about 'AI'.
• positron26 1y ago
  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?
  • thrown-0825 1y ago
    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
    • positron26 1y ago
      Could be CRM, leaving summaries for the next person. I suppose it would sound like I'm implying a prior.
• Terr_ 1y ago
  I think the biggest issue is accurately estimating the LLM failure risk, and what impacts the company is willing to tolerate in the long term. (As distinct from what the company is liable to permit through haste and ignorance.) With LLMs the risk is particularly hard to characterize, especially when it comes to adversarial inputs.
• hobs 1y ago
  That is a good thing, but that's also just a training gap - I worked with tech support agents for years in gigantic settings and taking notes while you take an action is difficult to train but yields tangible results, clarity from the agent on what they are doing step by step, and builds a shared method of documenting things that importantly focuses on the important details and doesn't miss a piece which may be considered trivial by an outsider but (for instance) defines SOP for call escalation and the like.
• dsr_ 1y ago
  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.
  • lotsofpulp 1y ago
    The summaries can help automate performance evaluation. If the employee disputes it, I imagine they pull up the audio to confirm.
    • Imustaskforhelp 1y ago
      the amount of false positives coming from wrongful AI summaries plus having to pull up the audio to confirm is so much more hassle than not using AI and evaluating on some different metric at the first place. Seriously not kidding but the more I read these comments, the more I become horrified realizing wtf,The only reason I can think of integrating AI is because you wish to integrate AI. Nothing wrong with that, But unless proven otherwise through some benchmarks there is no way to justify AI. So its like an experiment, they use AI and if it works/ saves time, great If not, then time to roll it. But we do need to think about experiments logically and the way I am approaching it, its maybe good considering what customer service is now but man that's such a low standard that as customers we shouldn't really stand it. Call centres need to improve period. AI can't fix it. Its like man, we can do anything to save some $ for the shareholders. Only to then "invest" it proudly into AI so that they can say they have integrated AI and so they can have their valuations increased since VC's / stock market reacts differently to the sticker known as AI man.. so saying that you use AI, should be a negative indicator instead of a positive one in the market and the whole bubble is gonna come crashing down when people realize it. It physically hurts me now thinking about it once again. This loop of making humans bad for money, using that money for inferior product, using that inferior product only because you want AI sticker, because shareholders want valuation increase and the company is willing to do this all because they feel/ are rewarded for this by people who will buy anything AI related thinking its gold or maybe that more people will buy it from them at an even higher evaluation because AI sticker and so on.. Almost sounds like a pyramid.
• tux3 1y ago
  > it's a huge, measurable efficiency gain. > It's not going to replace anyone's job Mechanically, more efficiency means less people required for the same output. I understand there is no evidence that any other sentence can be written about jobs. Still, you should put more text in between those two sentences. Reading them so close together creates audible dissonance.
  • flkiwi 1y ago
    You're not accounting for teams already being understaffed and overtasked in many situations, with some AI tools allowing people to get back to doing their jobs. We aren't expecting significant headcount changes, but we are expecting significant performance and quality improvements for the resources we have.
    • tux3 1y ago
      The reason that caused the team to be understaffed and overtasked has not gone away because of AI. I am expecting the team to stay understaffed and overtasked, for the same reason it was before: it's less expensive. With or without an LLM summarizing phone calls.
  • missedthecue 1y ago
    "Mechanically, more efficiency means less people required for the same output." Why can't it mean more output with the same number of people? If I pay 100 people for 8 hours of labor a day, and after making some changes to our processes, the volume of work completed is up 10% per day, what is that if not an efficiency gain? What would you call it? It really depends on the amount of work. If the demand for your labor is infinite, or at least always more than you can do in a days work, efficiency gains won't result in layoffs, just more work completed per shift. If the demand for the work is limited, efficiency gains will likely result in layoffs because there's no point in paying someone who was freed up by your new processes to sit around twirling a pen all day.
    • tux3 1y ago
      All else equal, the demand for support calls doesn't go up as your support becomes more efficient. I get that we're trying to look for positive happy scenarios, but only considering the best possible world instead of the most likely world is bias. It's Optimistic in the sense of Voltaire.
• belter 1y ago
  Are the summaries reviewed by the agents? And if not how do you handle hallucinations, or transcribe of wrong insurance policy id for example? Like, customer wants to cancel insurance policy AB-2345D and transcribe says wants to cancel insurance policy AD-2345B
• pedrocr 1y ago
  > agents were previously spending 3-5 minutes after each call writing manual summaries of the calls Why were they doing this at all? It may not be what is happening in this specific case but a lot of the AI business cases I've seen are good automations of useless things. Which makes sense because if you're automating a report that no one reads the quality of the output is not a problem and it doesn't matter if the AI gets things wrong. In operations optimization there's a saying to not go about automating waste, cut it out instead. A lot of AI I suspect is being used to paper over wasteful organization of labor. Which is fine if it turns out we just aren't able to do those optimizations anyway.
  • nulbyte 1y ago
    As a customer of many companies who has also worked in call centers, I can't tell you how frustrating it is when I, as a customer, have to call back and the person I speak with has no record or an insufficient record of my last call. This has required me to repeat myself, resend emails, and wait all over again. It was equally frustrating when I, as a call center worker, had to ask the custmer to tell me what should already have been noted. This has required me to apologize and to do someone else's work in addition to my own. Summarizing calls is not a waste, it's just good business.
• Shank 1y ago
  Who reads the summaries? Are they even useful to begin with? Or did this just save everyone 3-5 minutes of meaningless work?
  • vosper 1y ago
    AI reads them and identifies trends and patterns, or answers questions from PMs or others?
    • cube00 1y ago
      AI writes inaccurate summaries and then consumes its own slop so it can hallucinate the answer to the PM's questions after misreading said slop. Much like dubbing a video tape multiple times, it's going to get worse as you add more layers text predictors.
  • doorhammer 1y ago
    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.
• recallingmemory 1y ago
  So long as precision isn't important, I suppose. Hallucination within summaries is the issue I keep running into which prevents me from incorporating it into any of our systems.
  • thrown-0825 1y ago
    I have seen ai summaries of calls get people into trouble because the ai hallucinated prices and features that didn't exist
• trevor-e 1y ago
  This is a great use-case of AI. However I strongly doubt your point about "It's not going to replace anyone's job" and that "they also free up the human agents to do higher-value work". The reality in most places is that fewer agents are now needed to do the same work as before, so some downsizing will likely occur. Even if they are able to switch to higher-value work, some amount of work is being displaced somewhere in the chain. And to be clear I'm not saying this is bad at all, I'm just surprised to see so many deluded by the "it won't replace jobs" take.
• varispeed 1y ago
  What’s the actual business value of a “summary” though? A transcript is the record. A tag or structured note (“warranty claim,” “billing dispute,” “out of scope”) is actionable. But a free-form blob of prose? That’s just narrative garnish - which, if wrong or biased, is worse than useless. Imagine a human agent or AI summarises: “Customer accepted proposed solution.” Did they? Or did they say “I’ll think about it”? Those aren’t the same thing, but in the dashboard they look identical. Summaries can erase nuance, hedge words, emotional tone, or the fact the customer hung up furious. If you’re running a call centre, the question is: are you using this text to drive decisions, or is it just paperwork to make management feel like something is documented? Because “we saved millions on producing inaccurate metadata nobody really needs” isn’t quite the slam dunk it sounds like.
• amluto 1y ago
  I’d like to see a competent AI replace the time that doctors and nurses spend tediously transcribing notes into a medical record system. More time spent doing the actual job is good for pretty much everyone.
  • simmerup 1y ago
    Until it hallucinates and the AI has written something wrong about you in your official medical record
  • nottorp 1y ago
    Competent, yes. But the current ones are likely to transcribe "recommend amputating the left foot" as "recommend amputating the right foot". Still want it?
  • beart 1y ago
    But... that is the actual job. A clear medical history is very important, and I'm not ready yet to cut out my doctor from that process. This reminds me of the way juniors tend to think about things. That is, writing code is "the actual job" and commit messages, documentation, project tracking, code review, etc. are tedious chores that get in the way. Of course, there is no end to the complaints of legacy code bases not having any of those things and being difficult to work with.
    • wl 1y ago
      Charting is for billing. If the point were to have accurate medical records useful for facilitating diagnosis and treatment, we'd structure medical records way differently. Fishing clinically-useful bits of information out of encounter and progress notes is tedious and only done as a last resort.
      • hinkley 1y ago
        I presume for malpractice suits as well.
    • hinkley 1y ago
• jordanb 1y ago
  We use Google meet and it has Gemini transcriptions of our meetings. They are hilariously inaccurate. They confuse who said what. They often invert the meaning "Joe said we should go with approach x" where Joe actually said we should not do X. It also lacks context causing it to "mishear" all of our internal jargon to "shit my iPhone said" levels.
  • ricardonunez 1y ago
    I don’t know how it can confuse because input on mic is relatively straight forward to get. I use fathom and others and they are accurate, better than manual taken. Interesting take, that I don’t memorize 100% on the calls anymore since I rely on note takers, I only remember the major points but when I read the notes, everything comes clear.
  • rowanseymour 1y ago
    Same here. It's frustrating that it doesn't seem to have contextual awareness of who we are and the things we work on so things like names of our products, names of big clients, that we use repeatedly in meetings, are often butchered.
  • orphea 1y ago
    Oh, that's what happening. I thought my English is just terrible :(
  • thisisit 1y ago
    I found that if you have people with accents and they emphasize certain words then it becomes very difficult to read. One example, I find is "th" is often D because how people pronounce it. Apart from that it is a hit or miss.
  • sigmoid10 1y ago
    That's the difference between having real AI guys and your average linkedIn "AI guys." The other post is a perfect example for a case where you could take a large but still manageable, cutting-edge transcription model like Whisper and fine-tune it using existing hand made transcriptions as ground truth. A match made in heaven for AI engineers. Of course this is going to work way, way better for specific corporate settings than slapping a random closed source general purpose model like Gemini on your task and hoping for the best, just because it achieves X% on random benchmark Y.
• actsasbuffoon 1y ago
  That’s the thing. There’s value in AI, it’s just not worth half a trillion dollars to train a new model that’s 0.4% better on benchmarks. Meta is never going to get a worthwhile return on spending $100M on individual engineers. But that doesn’t mean AI is without its uses. We’re just in that painful phase where the hype needs to die down and we treat LLMs as what they really are; an interesting new tool in the toolkit that provides some new ways to solve problems. It’s almost certainly not going to turn into AGI any time soon. It’s not worth trillions. It’s certainly worth something, though. I think the financials on developing new frontier models are terrible. But I’ve already built multiple AI projects for my company that are making money and we’ve got extremely happy customers. Investors thought one company was going to win the AI Wars and make a quadrillion dollars. Instead it’s probably going to be 10,000 startups that will build interesting products based on AI, and training new models won’t actually be a good financial move.
  • Imanari 1y ago
    Could you broadly describe the AI projects you have built?
    • trueismywork 1y ago
      Pinn for simulations
    • actsasbuffoon 1y ago
      I literally just had a conversation with my CEO this morning where he told me not to disclose the projects I’ve been working on, so I can only speak about it obliquely. We identified some problems our customers have, and I’ve come up with interesting ways to use LLMs as part of an automated system to solve some of those problems. It’s not the kind of thing where we just dump some data into the ChatGPT API and get an answer. We’re doing fairly deep integrations that do some interesting/powerful things. It’s been a big deal for our prospective clients and investors.
• nuker 1y ago
  > recently switched to using AI to transcribe and write these summaries Did users knew that conversation was recorded?
  • prophesi 1y ago
    You would be hard-pressed to find a call center that _doesn't_ start every phone call with a warning that the conversation may be recorded.
  • creaturemachine 1y ago
    Yeah the standard "this call may be recorded for quality or training purposes" preamble shouldn't cover for slurping your voiceprint to further the butchering of client service that this call centre is here for.
  • watwut 1y ago
    Typical call center call is recorded and you are told so by the start of the conversation. I had quite a few of those.
• Capricorn2481 1y ago
  > Not only are the summaries better than those produced by our human agents We have someone using Firefly for note taking, and it's pretty bad. Frequently gets details wrong or extrapolates way too much from a one-off sentence someone said. How do you verify these are actually better?
• ghalvatzakis 1y ago
  I lead an AI engineering team that automated key parts of an interviewing process, saving thousands of hours each month by handling thousands of interviews. This reduced repetitive, time-consuming tasks and freed human resources to focus on higher-value work
  • the_snooze 1y ago
    I'm under the impression that one of the most critical responsibilities a lead has is to establish and maintain a good working culture. Properly vetting new additions feeds directly into that. Why offload it to AI?
    • ghalvatzakis 1y ago
      Just to clarify, these aren’t interviews for job positions
      • Jolter 1y ago
        What kind of interviews do HR do, apart from job interviews?
        • ghalvatzakis 1y ago
          Not HR either. I work for an experts network firm
          • Jolter 1y ago
            Aha, see, your choice of words there was ”freed human resources” which threw me off. I see now.
      • hinkley 1y ago
        Clear as mud.
• pjmorris 1y ago
  I wonder how this change affects what the agents remember about the calls, and how that affects their performance on future calls. And I wonder whether agent performance, as measured by customer satisfaction, will decline over time, and whether that will affect the bottom line.
• stronglikedan 1y ago
  I wouldn't allow myself to be held accountable for anything in a summary I didn't write.
• MangoToupe 1y ago
  > We operate large call centers, and agents were previously spending 3-5 minutes after each call writing manual summaries of the calls. This is a tiny fraction of all work done. This is work people were claiming to have solved 15 years ago. Who cares?
• didibus 1y ago
  Where is the money being saved? Are you reducing the number of agents? Otherwise, it should actually cost more, before you simply had customers wait longer to speak to the next agent no? Or do you sell "support calls" so you're able to sell more of them given the same number of agents?
• ozgune 1y ago
  Previously discussed here: https://news.ycombinator.com/item?id=44941118 https://news.ycombinator.com/item?id=44941118 It's also disappointing that MIT requires you to fill out a form (and wait for) access to the report. I read four separate stories based on the report, and they all provide a different perspective. Here's the original pdf before MIT started gating it: https://web.archive.org/web/20250818145714/https://nanda.media.mit.edu/ai_report_2025.pdf https://web.archive.org/web/20250818145714/https://nanda.med...
• doorhammer 1y ago
  I'm curious, have you noticed an impact on agent morale with this? Specifically: Do they spend more time actually taking calls now? I guess as long as you're not at the burnout point with utilization it's probably fine, but when I was still supporting call centers I can't count the number of projects I saw trying to push utilization up not realizing how real burnout is at call centers. I assume that's not news to you, of course. At a certain utilization threshold we'd always start to see AHTs creep up as agents got burned out and consciously or not started trying to stay on good calls. Guess it also partly depends on if you're in more of a cust serv call center or sales. I hated working as an actual agent on the phones, but call center ops and strategy at scale has always been fascinating.
  • lljk_kennedy 1y ago
    Thank you, I came to say this too. You're mushing your humans harder, and they'll break. Those 5 mins of downtime post-call aren't 100% note taking - it's catching their breath, trying to re-compose after dealing with a nasty customer, trying to re-energise after a deep technical session etc. I think AI in general is just being misused to optimise local minima in detriment to the overall system.
    • ponector 1y ago
      Imagine how AI changed the call center's work: 1. Some agents have been laid off. 2. Survivors got stripped off 5-minutes summarizing breaks between calls and assigned new higher targets of how many calls should they take per hour/day. And it wasn't a good job before AI...
      • doorhammer 1y ago
        So, I fully agree that we should be aware how AI use is impacting front-line agents--honestly, I'd bet AI is overall a bad thing in most cases--but that's just a gut feeling. That said, it's possible the agents weren't given extra time to make notes about calls and write summaries; often they're not. You usually have different states you can be in as a call center agent. Something like: "On a call", "Available to take a new call", "Unavailable to take a new call" Being on a call is also being unavailable to take a call, but you'd obviously track that separately. "Unavailable" time is usually further broken down into paid time (breaks), unpaid time (lunch) etc And _sometimes_ the agent will have a state called something like "After Call Work" which is an "Unavailable" state that you use to finish up tasks related to the call you were just on. So, full disclosure: I did work for a huge e-com supporting huge call centers, but I only worked for one company supporting call centers. What I'm talking about is my experience there and what I heard from people who also worked there who had experience with other call centers. A lot of call centers don't give agents any "After Call Work" time and if they do, it's heavily discouraged and negatively impacts your metrics. They're expected to finish everything related to the call _during_ the call. If you're thinking "that's not great" then, yeah, I agree, but it was above my paygrade. It's entirely possible that offloading that task to an LLM gives agents _more_ breathing room. But also totally possible that you're right. I don't know the GPs exact situation, but I feel pretty confident that other call centers are doing similar things with AI tagging and summaries and that you see both situations (AI giving more breathing room some places and taking it away others).
• ethagknight 1y ago
  This highlights the potentially unrealistic spend on AI, where the proposal is to spend 10s of millions to save... marginal millions... that could have also been saved by a change in process with limited additional spend. I also would assume that there are far more significant behavioral or human factors that consume the time writing those minutes, i.e. an easy spot to kill 5-10 min before opening the line for the next inbound call, but the 5-10 minute break will persist anyway. I fully believe AI will create a lot of value and is revolutionary, especially for industries where value is hidden within data. Its the pace of value creation that stands out to me (how long til its actually useful and better and creates more value than it costs??) but the bubble factor is not ignorable on the near term.
• computerthings 1y ago
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• apwell23 1y ago
  i was pretty sure you were going to say "meeting summaries" ( which apparently is poster child of LLM application) . my guess was wrong but not really.
• chasd00 1y ago
  so you're saving 3-5 minutes per agent per call. I'm guessing calls come into a queue and then the next available agent starts to handle it. If an average call takes about 20min until the agent hangs up and is free for another then after about 5 calls they've saved enough time to take an extra call they wouldn't have before. 5 calls is 1.4 hrs on the phone, i'm guessing with breaks and call center reps not being 100% on the ball all the time then your agents probably will take maybe 3-4 more calls per day with the AI than without (assuming call volume is such that there are always more calls than agents can handle) Is that really millions of savings annually? Maybe it is but I always hesitate when a process change that saves one person a few minutes is extrapolated all the way out to dollars/year. What you'll probably see is the agents using those 3-5 minutes to check their phone.
• croes 1y ago
  But I doubt it justifies the billions of dollars getting burned for training language models and building power plants. And are full transcriptions not the better option?
• tempodox 1y ago
  That’s an important point. Real-life use cases are not sexy. And they don’t lend themselves to overblown hype generation and “creative marketing”.
• ponector 1y ago
  Your company saved millions means they fired many agents and hiked amount of cases per agent?
• dvfjsdhgfv 1y ago
  What I found is that although some tools are good for transcription and the final result is quite accurate, this is not necessarily true for summaries. Yes, I routinely read meeting summaries spit out by the so-called SOTA tools and they almost always contain major errors. So if you actually need them for anything serious, it would be wise to keep the audio.