← Using AI at Work: AI in the Workplace & Generative AI for Business Leaders
Using AI at Work: AI in the Workplace & Generative AI for Business Leaders
97: Using AI for Customer Support: Voice AI vs Humans in Customer Service Strategy with Nathan Strum
00:38:22
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- [00:00]
A
I would definitely would not go with an AI if there's no way to escalate that call to a human, why
- [00:06]
B
the human is a better option instead of a voice agent or something along those lines.
- [00:10]
A
So what we found is the voice agents are very good at sticking to scripts, very good at certain workflows, very good when something doesn't fall outside of the norm workflow that it expects. And so what we know from customer service is you can never get rid of edge cases, and edge cases are unpredictable and unpredictability is best handled by human.
- [00:34]
B
What are the risks? For a listener that says, hey, let's rent a list of names and blast them with the voice AI agent, It's
- [00:40]
A
already a very risky job to be doing an outbound call to somebody that's not expecting your call.
- [00:45]
B
Even if it's the human, huh?
- [00:47]
A
Even if it's the human, Right. So you throw the AI on top of that and you're just lighting the the fuel on fire.
- [00:52]
B
So for those listeners that have standard business needs, where would be some low hanging fruit that you would say, hey, you're okay, you're safe using AI here?
- [01:01]
A
Somebody's got to answer that phone within one ring. It's got to be a receptionist you've hired. And if it's not a receptionist you've hired because that's too expensive for your budget, then it has to be another solution. And that's where AI voice agents do really shine.
- [01:15]
B
Nathan Strom is the CEO and co founder of Abby Connect, where he spent two decades helping small businesses deliver better customer experiences and is now leading the shift toward a smarter future with AI powered reception that keeps the human touch. And welcome to Using AI at Work. I'm your host, Chris Daigle. Each week we'll be learning how today's business owners, entrepreneurs and ambitious professionals are getting more done with smart use of tomorrow's tech. Let's get started. Right now, every business leader is asking the same question. What are we going to do about AI? If this is you, chiefaiofficer.com has the answer. We give you a simple path forward where we provide executive and team training so your people know exactly how to safely use generative AI in their day to day. We also manage the deployment and implementation to make sure tools actually get adopted and deliver results. And we'll also guide company wide transformation so AI becomes part of your operating system, not just another shiny object. The companies that act now will increase productivity, cut costs and grow faster than their competitors. Those that wait will get left behind. So if you want to make AI work in your business, visit chiefaiofficer.com and see how we're helping companies of all sizes finally get results from AI. Hi, everybody, and welcome to another episode episode of Using AI At Work. My name is Chris Daigle, and I'm the host of the show. And today our guest is Nathan strum, who's representing Abbyy.com they're headquartered in Las Vegas with about 20,000 square feet of office space that's housing humans. And it seems to me that many people could look at that arrangement in today's scenario and say that's kind of risky, especially considering Abby's push into the AI space. So they're primarily focused on have been voice support, phone support for companies for the bulk of their career. But we're going to talk about what it's like to still maintain the human side while also introducing AI really best practices across the entire organization. So, Nathan, before we get started, why don't we tell the audience what they should expect to learn from today's episode?
- [03:18]
A
Well, as you rightfully said, we've been in this business for 20 years with humans answering calls and have gained a lot of experience in those 20 years. I know I look. Look young, but it's been a fun ride. And we're taking that experience and applying it to today's AI world and AI customer service. And through everything that we've learned, we believe that humans are going to be more important than ever.
- [03:48]
B
Well, I like hearing that because, you know, just on paper, it seems many companies are thinking, wow, we can flatten our headcount or reduce our headcount significantly. And especially in the voice AI, the phone support environment, and here you are talking about doubling down on the human side of that interaction. So tell me, what's the thesis internally about why the human is a better option instead of a voice agent or something along those lines?
- [04:22]
A
Sure, yeah. So what we found is the voice agents are very good at sticking to scripts, very good at certain workflows, very good when something doesn't fall outside of the norm workflow that it expects. And so what we know from customer service is you can never get rid of edge cases, and edge cases are unpredictable, and unpredictability is best handled by human people. And so that's where the human receptionist really shines over the AI.
- [04:56]
B
So, you know, as a consumer of products, my personal preference would be that if I want to solve an issue that requires me picking up the phone, my preference is to get it solved quickly. If AI can do it, that's great if it does it faster, but if all things being equal, if it would be the same effort to work with an AI or work with a person, my preference would be to work with the person. I don't know if that's. Are you seeing any trends or any surveys or research indicating that that's the norm, or would people rather just deal with an agent because it's kind of anonymous and low engagement?
- [05:31]
A
Well, I'll remind you the dawn of the Internet when we all used to talk to each other and we all used to ask each other questions and ask what's the weather in San Francisco? Or what time is the game start for the Cardinals in Arizona? And then after the Internet, we started Googling everything. And so our communication preferences do. Do change with the times, and our communication preferences do adapt to technology. And I believe that we do see that in AI as well.
- [06:05]
B
Can you think of any examples or use cases that you've experienced there at Abbyy where the human was the obvious better solution and somewhere maybe the AI agent was the obvious better solution? And what I'm looking for is as our listeners are kind of like digging in on this conversation with us, they all have some form of their. Some process in their business that requires a human to connect with a customer, a prospect, whatever. In this show, we're looking for ways to introduce the technology safely, you know, and not just because it's the tech, but because it's the right choice for the business. So what I'm looking here, looking for here with this question actually is just, are there some examples where one of the listeners should go like, that's always a human versus, hey, an agent's okay over here for this phone interaction?
- [06:53]
A
Yeah. Okay. So on the AI side, we have a lot of clients that use AI for scheduling. And so you call into your dental office and you want to schedule an appointment and get on the calendar with a human. The friction point there with a human receptionist is there's a lot of tedious work that comes into looking up the client, finding the right time. So it could take a little bit of time for that call to progress versus an AI instantly knows what times are available and who's calling and doesn't have to really spend time searching through a database or a ui. So that's on the AI side.
- [07:36]
B
Okay, makes sense.
- [07:39]
A
Absolutely. On the human side, we all, most businesses care about new clients and revenue. And we all know that a client that calls us or speaks to us in person, a prospect, we have a lot better chance of Converting and so same thing here. We'd rather our prospects talk to a human.
- [08:03]
B
That makes a lot of sense. I've been waiting for that moment where voice AI got so good that we could actually just unleash it as an outbound sales rep. But it's not there yet for us or I would imagine for many people. So there's some interesting, I don't know, experiences that you guys have had. How many employees, ballpark would you say were have been impacted by the decision for Abby to kind of take a more active and aggressive deployment of AI?
- [08:31]
A
Well, we're, we're growing as far as our headcount goes after the introduction of AI because.
- [08:38]
B
Interesting.
- [08:39]
A
Yeah. And one thing that is interesting, we're actually growing our human receptionist side faster because we have people that are interested in the AI because it's the big buzz right now, they call us and then they end up buying the human service. So it's a pretty neat thing to see. A small percentage of our business is AI right now. It's growing, it's growing faster than the human side, but it is still small percentage.
- [09:09]
B
Yeah. So my experience has been that when you're talking to any business right now, if you're doing B2B, that if you have something to do with AI, the other part, the other side is extremely interested. So I find that pretty telling that after they have somebody who gives them a perspective from both sides, despite the cost savings, despite the scalability of it, they still choose the human. So that's encouraging for a lot. Because I know one of the examples that had to do with customer service that I'm most familiar with was an early example where OpenAI was working with Klarna, the payments. And Klarna was really bullish on Gen AI right from the get go. They embedded, they had OpenAI people embedded in their organization and stuff. And I remember hearing an example from the customer service side that in the first month of using, it was bots. It wasn't voice, but using bots that those customer service bots had handled, I don't know, like 2 million minutes worth of communication, which was the equivalent of like their entire human staff of 700 plus people that were on the phone. And you know, this was early on and I thought, oh my gosh, like this, this doesn't bode well for, you know, humans because if they can come in there in 2023 and do this now fast forward to 2026, they've kind of pulled back a lot on that and they've ended up bringing on a lot of humans that they let go to come back in and support that. Even though the. When surveyed, the client experience was the same. They didn't know if they were working with an agent or like a human or an AI agent, but the scores were the same. So on paper it looked like, oh, those folks are, you know, the, the phone representatives are on trouble. But in practice, it didn't quite work out like that. Have you seen some of those examples in your industry as well?
- [11:05]
A
We have. We've had. We've seen some interesting things. So we've had clients on the human receptionist side, been with us for years, Love the service that said, hey, listen, Abby, we've got to cut our costs, but we need somebody to answer our phones. Let's try this AI. And they came over, they traded the AI, loved it, but said, hey, listen, our callers, you know, 50% of them just, just aren't jiving with the AI. Yeah, you just can't. We can't do it. They went back to the human side. So we have seen that transition the same way that Klarna had it.
- [11:38]
B
Yeah. Were you familiar with that, that, that case? Yeah. Okay. Because I know Klarna has done a few things that have been like, the initial results have been like, oh, my gosh. And then like, they quietly roll it back a little bit later because it's not as all. Is not as it seems. I guess it's not all about the numbers when it comes to the. Particularly the human interaction, particularly when it comes to a financial transaction like what Klarna deals with. Are you involved in the selection of the different tools that you guys use to support the AI stuff?
- [12:10]
A
Yeah, so we select some of the foundational models and then we also build a lot ourselves.
- [12:15]
B
Interesting. Okay, when did you guys start, I guess, your initial tests or working with the voice AI?
- [12:23]
A
So we started building almost immediately. When 3.5 came out in 2022, I went to the engineers, I said, look, if you can build something that does exactly what our human receptionist does, we'll take it to beta. If not, that's okay, but we're not doing anything with this. We're going to scrap it. I was pleasantly surprised when we went into beta and had some great customer feedback. And so we went into beta where people are using it in 2024 and then officially launched in 2025.
- [13:00]
B
So, like, with anything with AI, right? If you talk to somebody and you say, oh, you should try this tool, and they say, oh, no, I tried it. Well, well, when did you try It. Oh, it was last year. Like. No, I'm sorry. Completely different tool at this point, my friend. How have you seen the progression of the capability of voice AI since, I mean, early on when you guys were. Is it getting much better?
- [13:21]
A
It is, it is. There's been improvements. I think the biggest improvements are the speech to text side. So for, for all of you that don't know how it works, you've got three major components. You've got the speech to text, that's one model and that sends the data to the LLM, like OpenAI, anthropic Gemini, and then that sends it to a text to speech model. So 11 Labs is the big name in this industry and that's how you get the call end to end. And so we've seen some major improvements in all three categories. But some of the really defining changes that aren't big names that people hear about are in the text to speech and really. Excuse me, Speech to text and capturing the right words that people are saying with all different accents.
- [14:22]
B
Yeah, we just were looking at a note taker that apparently can discern from 60 something different accents. So that's. And I've never seen those tools mention that as a bonus or a benefit before. So. So one of the things that, like when I'm encountering opportunities to use this a. I don't know, I guess I would start with something kind of off the shelf like a, an 11 labs agent. I know they have those figure out the N8N or the automation that that triggered that sort of thing. But we don't schedule a lot of appointments and you know, we're not doing a lot of outbound cold calling or anything like that. So for those listeners that have, you know, I guess standard business needs, where would be some low hanging fruit that you would say, hey, you're okay, you're safe using AI here, the tech is there, it's easy to install or use. Customer feedback has been that in this application it's acceptable, that sort of thing.
- [15:24]
A
Sure, yeah, Good question. First of all, please don't do outbound calls with AI.
- [15:29]
B
Let's talk about that before we jump in there because there's got to be legalities and all kinds of stuff. What are the risks for a listener that says, hey, let's rent a list of names and blast them with the voice AI agent.
- [15:44]
A
It's already a very risky job to be doing an outbound call to somebody that's not expecting your call.
- [15:50]
B
Even if it's the human. Huh?
- [15:51]
A
Even if it's the human.
- [15:52]
B
Right.
- [15:53]
A
So you throw the AI on top of that. You're just lighting the, the, the fuel on fire.
- [15:59]
B
So bad news, don't do it.
- [16:00]
A
Bad news, don't do it. Okay, so for inbound, let's talk about the good site. For inbound, I would say that the real time where you really need to think about this is who's answering your phones now? Because somebody's got to answer that phone within one ring. And if it's not you, the business owner, which I never recommend because you've got other things to do, then it's got to be a receptionist you've hired. And if it's not a receptionist you've hired because that's too expensive for your budget, then it has to be another solution. And that's where AI voice agents do really shine, is that within one ring, calls are answered. People feel like they're heard. They get somebody on the phone, and whether they take the call to the completion is one case or they transfer it to a human is another case.
- [16:55]
B
So in this case, something is better than nothing when it comes to somebody picks up the phone, they want to talk to somebody at your office, it's better that they get an AI agent than ring, ring, ring. Please leave a message.
- [17:06]
A
Absolutely, absolutely.
- [17:08]
B
For the people who are, they're calling the company, they're thinking they're going to order the widget or ask questions about the order or whatever, and they engage with AI. What do you guys recommend that we say, you know, how you've reached, you know, Acme Corp, and this is the virtual AI assistant or blah, blah. Do you, like, announce that up front that they're dealing with AI or how do you recommend we reveal it?
- [17:32]
A
Okay, so from an ethical standpoint, it's always been my position that yes, you should in every scenario, text, voice, articles, everything you should know, you should know. And so you should. As a business, you're responsible for telling people that. However, we did give our clients the choice in the beginning. It's their business. There is no legal authority right now telling us that it has to be done. So we gave them that choice. What we found was, is the results were just incredibly better when you announce it that it's AI because there are little nuances, and if somebody thinks they're talking to a human, they get a little frustrated.
- [18:17]
B
Yeah, yeah, yeah. You mean if they think they're talking to a human and those, those AI nuances float in, they think the humans, like, bad at their job or whatever.
- [18:26]
A
Exactly, exactly. But they'll give a little bit of freedom to the AI.
- [18:30]
B
Interesting, right? Okay. Huh. You know, I. I saw a. That's a perfect example. I saw a story the other day. Somebody was saying that they were calling to flight, got delayed situation. I think it might have been United, actually. And they got on the phone and this is an AI professional that was, you know, trying to rebook their. Their flight and that sort of thing. And he's. The guy said, about halfway through the call, I asked it. I said, are you a. Is this AI? And he said the response was like, no, I get that all the time. And then he said the next question was, can, you know, like, how many prime numbers? Blah, blah, blah. Like, he did something that only a computer would know. Right? And that same voice was like, oh, that's 18.3.
- [19:13]
A
Oh, my gosh.
- [19:14]
B
So even in that situation, when they were queried, I guess the rules were for that company, don't announce that you're AI. And so, folks, if you didn't follow what I just said, if you want to test it, you can ask it. Like, you know, our chief AI officer always asks those voices, do you have a good chocolate chip cookie recipe? And if the person's like, I guess so. You know, you're like, okay, that's probably a human. But if it goes, sure, take, you know, two cups sugar, immediately you're going to know that that's an AI because maybe the rules that they have set up for the AI on how it should respond haven't necessarily covered all the angles. So there's ways for you to coax it out of the voice, even if they're. They've been trained to tell you no. So that's not something. An experience I would want my clients to have where they've. They even ask, is this an AI? And my AI is trained to be dishonest. That's good on you. United, I think.
- [20:12]
A
Imagine the trust. I mean, imagine the trust out the window, Especially a company. You put your hands in there, you put your lives in their hands.
- [20:21]
B
Yeah. And, you know, but if you think about it, right, this was an AI professional. And whatever model they were using was good enough for him to be like, is this an AI? He wasn't. He even. He wasn't certain. So I would imagine that the average person, because, like Nathan, you, I. The listeners, we're kind of in a bubble. The fact that we're just even talking about this stuff at the level that we're talking about the majority of the, you know, even the developed countries, the Western world, they wouldn't even be able to follow this conversation. So for them to encounter, you know, an AI voice that was really good. So good that they had to ask, wait a minute, is this an AI? I would imagine that the risk reward for a larger company, maybe they said, you know, we won't have that many people that notice it, so let's just go for it.
- [21:08]
A
Okay. And until the information gets to the podcaster that starts talking about it and
- [21:13]
B
everybody finds out, I would imagine there's probably. Because I know that I used to have a sales floor in the Salt Lake City area. A lot of humans on phones out there.
- [21:25]
A
Yeah.
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B
And there were, there were like legal frameworks that had to be followed, like the TCPA and things like that. Is there legislation at a federal level currently that, that anybody who wants to use AI, even if they're going to announce that it's AI, but anybody wants to use AI, should know about to make sure that they're staying compliant, or at least in the good graces of whatever parties are monitoring this stuff.
- [21:48]
A
There's nothing that's been passed, but there are things that are being debated right now. There's a, there's that ties a lot of different call center rules and regulations, not just for AI, but also for humans. Yeah. So for example, that if you call and you're speaking to somebody offshore, they have to tell you. And so they're trying to bring jobs back to the U.S. right. And so that is one part of this legislation that I'm thinking of. I can't remember the name of it,
- [22:22]
B
but nothing as far as like the AI side of things? Well, that's a good question. I would, I guess all things being equal, a caller would rather deal with a human. Or would you say that that's probably how your data is, is trending, that they'd rather deal with a human than AI?
- [22:39]
A
Not necessarily. Not in every occasion. Not in every occasion.
- [22:43]
B
Okay. For the occasions where they would rather have the human. But for a business, the economics don't work out. To have a US based person, would you recommend that they opt for the human but offshore or nearshore, or opt for the AI with the, you know, no accent and sounds like somebody from the Midwest or whatever. Best practices for, you know, voice selection.
- [23:06]
A
Oh, well, you're. Yeah. I mean, first of all, I would definitely would not go with an AI if there's no way to escalate that call to a human.
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B
Okay.
- [23:15]
A
You're gonna break the trust of your business in half within seconds. It just can't be done. But on the flip Side, you know, the offshores, they're getting better, but they're still a little frustrating sometimes. We all know that.
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B
So that's, I mean, a huge economic engine in, you know, I know in the Philippines and India and all those sorts of places. Right. Are they adopting the technology and using that?
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A
The big technology that they've rolled out over the past few years is where it changes their accent.
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B
Interesting.
- [23:58]
A
Yeah. As they're talking, it takes their voice and changes the accent and that's all AI driven.
- [24:07]
B
I don't know that I've even seen that. Is it pretty common?
- [24:11]
A
I don't know if it's common yet. It's growing.
- [24:15]
B
Yeah.
- [24:15]
A
Selling. They're buying it.
- [24:18]
B
Okay. Because I'm trying to like think a few steps ahead here about what does this mean for jobs and you know, like which, which economic models are going to get disrupted and things like that. And it seems like anything that's very human intensive right now, but doesn't require like advanced skill sets or, you know, precision knowledge is something like, you know, Dario Amade, the CEO of Anthropic, said that he expects 50% of entry level white collar jobs to be gone in the next few years. And so I think about, because I've had not just sales floors, but I've had, you know, customer service call centers, great people, a lot of fun. But computer might be smarter than a few of them and, and less temperamental. Right. So if I was going to do it again, my preference would be small element of human. But the business primarily being AI supported, I can scale it 24, 7, all those sorts of things. So I'm evaluating like what does this mean for those offshore models where we've just been able to get the human at a cheaper price but at the expense of English as a primary first language or whatever. So, huh. Are you guys modeling out like how you stay ahead of this over the next few years?
- [25:39]
A
Well, you know, as far as that prediction by Anthropic, we predict that 75% of businesses are going to be clients of Abby. So you could predict whatever you want. I mean he's obviously predicting what's going to help him. Yeah. You know, I don't know if I believe that. You know, what, what evidence does he have why, you know what, why does he know the future? Nobody else knows the future, you know.
- [26:10]
B
Yeah.
- [26:10]
A
So I don't know. I don't put too much stock in that. But how we're going to stay relevant is there are my core belief, take this to my grave because I'm Still, I'm pretty old, so it's going to be soon is that there just are fundamentally conversations that just need to be between one human and another human. And if we can focus on those conversations, we can actually improve customer service because we can spend more time and more energy on those calls and less energy on these routine calls.
- [26:49]
B
Yeah, I think I would probably have to agree with you on that. Provided that the economics made sense that I could still remain competitive. The preference would be the humans. Now, in our pre call, before we did the podcast today, there was a couple things that stood out about kind of how Abby looks at this with the concept of AI being about the people and the systems, not necessarily about the tech. Give me a little more, I don't know, mass or substance on how you guys are thinking about this. Obviously, you want to take care of your employees and that sort of thing, but across the business, operationally, how does this translate of AI being about people, not tech?
- [27:30]
A
Okay, yeah, great question. So, first of all, we don't look at AI as a cost cutter. We look at it as rebalancing expenses. And we're increasing expenses in some areas, we're decreasing in others. But what I get really excited about right now because I'm passionate about systems and making things easier for employees so that they can be happier and provide better customer service, is we're looking at every human interaction, every system in the company that has friction, and we're rethinking it. How can AI reduce this friction or eliminate the friction? I'll give you an example. In product development, it's the product manager's responsibility to get customer feedback and translate that into priorities for the engineering team. And that product manager gets feedback from multiple sources. Surveys, they interview customers themselves, they look at replays of customers using your platform. But they also get a really good amount of information from account managers and salespeople that are on the front lines talking to your customers. The problem is, is that they're relying on the customer service managers and the salespeople to remember to give that feedback to them. And those salespeople and account managers, they've got their own priorities, right? They want to help the product managers, but they just don't have the time. And that's the gold information right there. So we have AI listening to those calls and distilling out the information that the product manager needs. Everybody's happier. No human has been fired. Our customer is getting more of what they want, and our product managers are much happier.
- [29:17]
B
In employee, one of the other talking points that was brought up in our original conversation was this change management of hey guys, great news, we're bringing in AI and then the staff level looks around and goes, is that great news? And I would imagine especially in a call center environment, if I'm a phone agent, maybe I don't even know that AI is a threat, but I would be certainly concerned. How did it go when you guys started this? Was it kind of a, you know, skunk works in the back closet or was it full transparency for the team even if they weren't involved in it?
- [29:56]
A
Well, we knew that we were going to be like the most obvious test case for freaking your employees out.
- [30:04]
B
Yes.
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A
Because we're going and saying, hey, we're developing a receptionist to our majority of our company, which are receptionists. So we knew we had to think about this and, and we knew that we weren't going to be replacing them. So we were coming from it from a good point of view. So our first process was to introduce AI in a way that's non threatening. And the way that we did that was we really talked about it on a personal level, how we're using AI personally and we talked about fun use cases and we talked about, you know, different things in our life we were doing. And that got people a little bit interested in talking about it. And then the next part was we said, hey listen, you guys are hearing about how AI is going to revolutionize this, this, this whole world. We're going to introduce learning management software modules for you to learn AI so that you can develop the skills that necessary to get the new jobs in this new society. And whether they're from with Abby or not, you know, at least you're prepared for the next job that you have. But that goes along with our culture. Yep, we're very into growth, we're very into, listen, if you outgrow us and go to a career at a law firm as a paralegal, we're so happy. We couldn't be happier. So that was kind of the way that we took the direction. And then once we started talking about the product, we already have the trust of our employees. So that kind of helped. And so that when we say this product doesn't replace you, they trust us.
- [31:50]
B
Nice. You know, I think that this is one of those areas that, you know, some companies may say, well, we're not really, we don't do any engineering so AI, the data science side is not going to help us there. You know, we don't have a lot of contracts so AI's not gonna be able to help us with like, high volume, high velocity legal review communication, particularly on the phone is one of those areas that I think has got to be pretty much a universal activity for at least most of the listeners here. I'm sure we can find some edge cases where that's not the case. So this is something that, like, if a company wanted to, you know, engage with. Abby, what does. What are you looking for in a client who is gonna. They're hearing this and they appreciate, hey, I like the fact that they're not trying to just eliminate all humans and plug in technology and just wing it until the tech is good enough. But they also appreciate the fact that you're applying AI where you feel it has the best application and highest value for both the caller and the client. What are you looking for in a client?
- [32:57]
A
Well, so when clients call us, we don't have a preconceived notion of what they should use in their business. We like to really understand what their goals are. And our objective is to sell outcomes and not products. And so what outcome are you looking for with your phones? And let us help you with our experience, provide some, some feedback and guidance on how we might help you, but also with your input. And so we look at it as a relationship.
- [33:27]
B
Nice. Any particular industry?
- [33:30]
A
Same industries that we've been in for 20 years. Law attorneys, you know, law firms, financial advisors. Home services is a huge one. You know, you got your plumbers, electricians are out doing their work, they can't answer the phone. Dental offices and medical. But just the whole gamut of small business. You need your phones answered, you're doing your work well.
- [33:54]
B
I would feel comfortable. The main thing about working with external vendors in general for us is that we know AI. And I don't want to necessarily work with vendors who the extent of their AI use in their business is using ChatGPT to write emails. I want to know that companies that I'm working with are leveraging the technology as best as they can, but they're like, in pursuit of efficiency and optimization without the sacrifice of authenticity of the customer experience or whatever, but that they're not trying to do things the old way. Why? Because that, like, I benefit as a client if my vendors are optimized.
- [34:37]
A
Yeah.
- [34:38]
B
So I think for anybody that was. That is. Is looking to. Because I agree with you 100%, something is better than nothing, even if it's the AI voice that's on the, on the other end of the phone. But like, I don't leave messages if a Business isn't answering the phone. I'm like, oh, let me go down the list. I'll call the next business.
- [34:55]
A
Right, right, right.
- [34:56]
B
So I think for anybody that's listening, that they don't have that, that, that feedback loop, that communication line dialed in. I would be looking for a vendor like Abby because they are intelligently using AI, not just in the delivery of their product, but in their operations. That they've got people like Nathan who are thinking about this, that. Because here's what, what can happen for sure. You, you find the vendor and they're all enthusiastic and we have a Klarna situation. Chris, don't worry, we fired everybody. Our prices are low. And then 30 days later I'm like, hey, guys, like, your technology broke and there's no, there's nobody answering the phone. So I would certainly encourage any listener to explore that kind of hybrid situation like we've got here. Not exclusively boutique or we don't touch AI and not exclusively like, oh, humans are inefficient. We'll just run everything through the algo. I kind of like where you guys are coming from on this.
- [35:53]
A
Nathan, there's one other gotcha. There's one other gotcha. You got to really be careful with the new companies that are really technology based and trying to do things that are more service based like answering phones, because they're really coming from this, from a technology only standpoint. They don't really understand the human element of customer service.
- [36:15]
B
Yeah. Yeah, Awesome. I can certainly see that being an issue if they're simply looking at it as a function of the spreadsheet and the compute and not necessarily the authenticity of the interaction.
- [36:27]
A
Right.
- [36:29]
B
At least in theory. On paper it looks good, but until it starts, until grandma calls up, it's not quite, not quite the experience you would want them to have. Well, that's fantastic. Well, Nathan, thank you so much. How can people find out more about what you guys are doing at Abby and are you putting out like, I don't know, updates from the field about some of the things you guys are discovering or is any of that available to us?
- [36:49]
A
Yeah, definitely. Well, please come to our website, abby.com a b b y.com but also on social, we're active on LinkedIn. Our handle is Abby Connect. I think you call it a handle, but that's, that's how you find us. And we'll provide updates and love chat with you there.
- [37:07]
B
Awesome. Well, thank you so much for taking some time today, Nathan. And for those of you listening, the best way that you can help make sure that we continue this show is to let other people know about it. And how can you do that? Pass a link to a friend if an episode landed really well with you, let them know about some of the things that you're learning from some of the guests on the show. And of course, if you could take a moment to just leave us a review. It definitely matters and helps us make sure that we're getting our message in front of more AI encouraged executives and thought leaders out there and knowledge workers out there in the in the world. So thanks everybody for listening in and my advice, as always, go use AI. Thanks for tuning in to Using AI at Work. Don't forget to subscribe for more conversations about how to use AI at work and a special thank you to our sponsor, Chief AI Officer for empowering businesses with AI education and training. Visit their website for a free AI Readiness Assessment and AI Strategy Guide to help you get started using AI at Work. That's www.chiefai officer.com. follow us on Twitter at the handle Using AI at Work and visit www.using aiatwork.com for free resources to help you harness AI in your role.