Will AI Change Customer Service Forever in 2025? | CXOTalk #879

AI is reshaping customer communications with terms like virtual workforce and AI receptionist. I'm Michael Krigsman, and I spoke with Damon Covey from Go to to explore how small companies can use AI agents to improve both efficiency and customer service. One of the main customer services challenges is being able to communicate effectively with your customer over the channel and the way they want to talk to you.

If a customer wants to text you, if they want to do reach out to you via Instagram or Facebook, things of that nature, being able to communicate with them that way. And traditionally what that looked like for customers is they got to go use all those different platforms to communicate with those customers and they didn't have a way to do that. Now there are solutions that bring all of those things together.

So it makes both the employee experience or the business experience and then also the end user experience as seamless as

possible. So as customers needs to evolve, we've added more and more channels and opportunities to communicate over the years to to that cloud communication solution or in the business of providing the opportunity to talk to customers, to communicate with customers, schedule appointments, things of that nature in the way that customers want to talk with the company directly and that's it. That's a challenge traditionally, especially for smaller customers. Can you give us a few examples?

If you have a dentist practice and someone wants to communicate with you and set an appointment, they're very often just going to be doing whatever they do during the day and and a text is much faster to set that appointment. So that's one example. Another example I can give you from my personal experience is I had a pipe that burst in my basement. I was trying to reach out and find a plumber.

I didn't know a plumber. So I started calling down the list of plumbers and the first one to text me back got my business right. And so being able to communicate again with the customers in the way they want to, the way they're communicating in flow is a really critical part of especially a small business practice. So making it easier for customers to interact with the

business. Making it easier and then also having it be integrated back into the systems they care about, their CRM or other systems that they might be working with, keeping them in those systems to make sure they're tracking that information as well. So the integration with their existing systems, their existing

processes is essential here. It's critical to make sure that they can continue to do business the way they want to, but also communicate with their customers in the way the customers want to communicate with them. How can AI make this process easier, better, faster? AI has the opportunity to really take, especially if you look at a small business, they are most of the time multitasking, right? They're dealing with customers. They're also dealing with things inside of that business.

And so they don't always have the opportunity to answer the calls or answer the key questions, things of that nature. They might actually lose some of those customers that are calling in. AI has the ability to be a force multiplier and answer the phones as an example 24/7 for them, answer specific questions and then transfer that information along with the caller when appropriate to the right person who can help them and get that

to be a more efficient rocess. Damon, I've heard you use the term virtual workforce. What? Is that virtual workforce is essentially a way to harness AI technology to do things that you would like a human be able to do what they may not be available. If you think about humans in your environment, they're not only answering calls and texts and things of that nature, they're doing things also. So you want to automate those repetitive tasks.

And so AI can take a lot of that over, can start to automate that, whether it's answering the phone in some cases we talked about whether it's possibly answering questions about locations, hours, things of that nature. So really use AI in a very smart and practical way to get into it and automate those tasks. That's where you start to see the AI virtual workforce emerge. And we'll see more of that as we

go into the future as well. We hear a lot about AI agents and agentic AI. Is a virtual workforce the same thing? It's a part of it. So if you think about virtual workforce and agents, that's the tip of the spear for answering calls, automating mundane tasks, things of that nature. And what Agentic does is takes that information and takes action on that, right? So if you need something to happen in somewhat of an autonomous fashion, that's where a gentic AI can come into play.

So for example, if you want to pull something out of ACRM and then insert that back as you're talking to a caller, that would be an example of a scientific AI on the front end. And then it will get more sophisticated as we go forward and and do more sophisticated options and advanced actions as well. And so how is that different or the same from the virtual workforce? It's part and parcel to the same thing. Virtual workforces will just mature over time.

So to be able to again, automate those tip of the spear tasks and then also to automate other tasks that are smarter, right, that require connecting to multiple different systems, require, you know, multiple different pieces of input. That's where a gentic AI really has power is in connecting those things together and automating A workflow to satisfy a particular problem that might dip in and out of five or six systems, as

an example. And then how does the virtual workforce relate to that workflow that you just mentioned? Virtual workforce will be at the front end of that. And so an example of that is a receptionist be able to answer the call, understand the intent of the caller, answer some simple questions, and then potentially transfer that person over in the future. We see that getting more and more sophisticated, whether you can actually take actions as opposed to just answering the

call. That's how the two fit together.

You've just released an AI receptionist. Tell us how that works. Air receptions is something that anybody can add into their telephony system that will answer phone calls for you. If you think about it, Michael, the most challenging part of AI as as it relates to customer communications is the voice section, right? So that's what we took that one on. 1st.

What this allows you to do is put that at the front end or frankly at the middle or even at the end of your telephone call and answer that, answer that call, answer questions and transfer that over to the appropriate person on your side with the intent also summarized. So imagine, you know, before you're just getting a call from someone out of the blue, you don't know what they're calling about.

We can capture that information and transfer that over to someone where they can actually understand what this person's calling about. Are they upset or not? Not what they're actually looking for. And you can automatically know how to come out of the call and how to better handle that in that call. So the virtual receptionist interacts with the caller and feeds information back upstream to a person who may or may not interact with that caller. Is this correct?

Yes, in many cases that's correct. And we can also extend that a receptionist to answer again, common questions, right? So if you want to help that AI learn over time by feeding it information that it should answer as you start to observe what's happening and start to observe that. But yes, ultimately it probably ends in some human interaction. And the idea is to augment the human interaction with the caller and make that at resolution as speedy as possible.

So to some degree, the virtual workforce is an autonomous process that interacts with the caller. Absolutely, on its own. It will, with your permission of course, answer those calls, answer those questions. But it can be, and it does operate within its sphere of influence, autonomous from someone else actually having to manually take that call or take an action. And so there's a set of boundaries that are built in. You mentioned scope or sphere of action.

Correct. That's a really important part of this actually, Michael, is what we don't want to do is just wire an AI receptionist to an LLL, right? That would be a bad idea because it might actually give some bad information or something that you weren't expecting it to.

So making sure you tune the air receptionist to give the proper information only with the guardrails you wanted to and starting with a very scoped set of of responsibilities and building up from there is is the way to to help it learn with your system. So the set of boundaries is vitally important here. Absolutely.

It's probably the most critical part of this to make sure. And again, what I always tell people is or something practical, start with something that's a simple problem that's repeatable, that you can solve over and over again that you feel good about an AI receptionist talking about. And then build up from there as you start to see how those reactions are going as you go forward. Damon, what benefits does a virtual workforce bring to go

To's customers? So it starts with really the ability to have any interaction handled 24 by 7. So if you've got your employees that are doing something else and they can't answer the call, that's number one. The other thing is ensuring that you can free those employees up to do higher value things, more beneficial things and look at other opportunities within within your environment. So if they're doing the same thing over and over again, now

we can free them up to do that. And then I would say the other thing is really just making sure that because you're answering swiftly and giving them feedback right away, really enhancing customer satisfaction from the end user perspective, they're getting information they need faster than they would have previously. This notion of improving customer service for the caller is really important.

Can you elaborate on that? With an AI receptionist or or AI, you have the ability to guarantee the response that the, that the user or the caller in this case is getting. And so that gives them the ability to automatically have their call answered at all times. So that that's number one is, is a primary benefit. And then to get a guaranteed answer. And what that is and if they need to be have a guaranteed way

of getting interaction. So those are all three things that customers are looking for that immediate response. They want that immediate interaction. People don't wait anymore to get feedback from companies they want to do business with, and this gives them that immediate feedback. How is this different or more beneficial than traditional customer service channels? Traditional customer service channels always need a human intervention and this is not meant to replace that human

intervention. What this does is helps you scale your business, right? And so that's where it's special is again, if you're a, if you're a small customer, part of what you're doing is just, you know, the business of making sure that your business is done and scaling it, making sure you can answer all those calls, making sure those they were having to have an agent behind every single call.

And again, freeing up those agents to do more, higher interaction, better sales process, better service process, things of that nature. That's really what this is about is augmenting your human workforce so that they can do things that are higher value again to the to the company on the back end. So there is an efficiency benefit to the go to customer and a service benefit to the end user that's calling in. Correct, You definitely get a

benefit both ways. In terms of accuracy, in terms of of how fast the call is answered, in terms of how fast it's responded to, which will by itself gain you a higher satisfaction rate. Damon, let's talk about

deployment. What is involved with implementing or deploying this kind of system? That's a critical decision factor. Small customers have not had the ability to, you know, capture something off the shelf, like implement that on their own. So the AI receptionist, as an example, introduces the ability to have a small and simple operation that you can feed things like K BS knowledge base articles as an example.

We can feed FAQs into, right? We can start to actually put questions in there, things of that nature. So it makes it very, very easy and practical to get up and going off the ground. And then I think the other thing that's really important about this, Michael, is you can observe the system over time as well. So that's a critical differentiator also is it's, yes, it's easy to get up and running, but can I see how it's actually doing? Can I, can I see how the

customers are responding to it? Can I listen to the calls? All the above is there. And so you can tune that as you go. Both of those things are critical factors in implementation. When you say see what the system is doing, can you elaborate on that? Yes, one of the most critical things with any communication system is is you can run analytics and and you can start to see things like word cloud of

was someone angry, right? Did someone, you know, say something that they shouldn't have, right? Are they happy? And so digging into that and seeing what those interactions actually consisted of and listening to the call if you need to. So that gives you the ability to run quality metrics against your environment, which usually is reserved for very large

corporations. That is one of the biggest barriers to entry to having anybody, whether it's an agent or an AI interface, in this case answer calls, is understand that quality behind the scenes. And because of the AI, I'm assuming that this turn around is very fast. Almost immediate the call is recorded if you want it to be and then the call is is brought forward.

And then we, we actually use AI to do a summary analysis of that and it almost immediately you will see what happened and you can drill into that and diagnose what, what occurred with that interaction. Damon, what's involved with deploying this kind of system? The key here is to making the system easy to deploy and so making it practical to deploy. So what you would do is you would just start feeding in knowledge base articles. It can crawl your website

information, information. You can even put simple keywords in there to say if you hear this, then say this, or if you hear this, transfer this to an operator or transfer this to a salesperson. So really it's it's very practical to set it up, it's very practical to have it learn with you and only the things that you feed into it will it actually be able to respond back to. What about integration with existing systems and existing business processes? A couple of things.

First off, it's very important to be able to integrate with your human employees, right? We talked about the ability to capture the sentiment of a call and make sure that gets transferred onto a human. That's an important part about this. But the other thing is the ability to integrate with your systems. So if there is information we capture, right, be able to integrate that back. And that's one of the things you want to look for is how does it integrate with the system that

you're mostly in? And usually that's ACRM. So making sure you've got the proper CRM integration, making sure posting that proper integration into the system is a critical component to make sure that you don't have to go back and forth between systems as you're as you're moving forward and working with your human employees. You've mentioned the data several times and the training of the system. Tell us a little bit more about

what kinds of data are used. Simply put, any kind of data that is in a written format, in a digital written format, you, you can feed into the system. So again, you know, FA QS, knowledge base articles, those types of things. But the other thing is the, the notion of observability and the ability to, you know, go in and tweak and optimize the system. That's critical. Like to see what's happening with these interactions, see what's happening there.

And then you can either tweak the documents accordingly. You put some additional prompts in there for that. That's something that's, you know, part of as an example of what we've done is we built that into the interface. You can just feed those documents in. You can, you know, you can tweak those those questions if you want to and all those kind of things. That's all part of the data that goes in to make sure you can get

a quality response back out. Do you have recommendations or best practices for folks that are just starting out? Start with a simple practical issue you're trying to solve. So if you're getting the same call for the same thing over and over and over again, that's very tangible, it's very understandable. And you can usually put the information you want an AI receptionist to say back to the

customer very, very quickly. So again, in the case of go to, we've allowed you to come simply come in there and put simple questions, simple answers. When you hear this, you can respond with that. And as you do that, what you'll find is you can tune that very quickly to the other things you want to do. You'll gain reliability, you'll gain trust, right? You'll gain the ability to get more confidence and then train that AI receptionist as you move

forward. But starting with something very practical and something very simple is a great way to get started and and and makes it very real for businesses to get a handle around. Starting small enables that trust level to grow because it is new. I'll give you an example, Michael, of where we've seen something really work really well is so I have a medical shop that I work with and, and they have an after hours answering

service. And after hours answering service is literally writing down each person that calls and then they're faxing that information in to the office the next day. Nothing wrong with that. That's happening today. But the air receptionist can do the same thing. It can actually take those calls. It can capture what they called about it, capture the person's name, depending on what you want it to do. And that's a very practical

thing you can start with. That makes it easy for you to to work on and tune and adjust as you go forward.

Can you talk about the collaboration between the virtual workforce and the people working at the company? It's absolutely critical to make sure that the AI workforce can communicate and can talk to and work with your human workforce. So you might want to, in some cases have the AI workforce at the beginning of a call. You might want to have them towards the end of a call, for example, if you wanted to ask for a post call survey or something of that nature.

But making sure that you can transfer the calm intent, right, automate those responses that the that you want to as a business and make sure that we're not replacing the human because the human touch is still needed. And I don't see that going away anytime soon. But making sure you're augmenting what the human is doing by by taking those common repetitive tasks out of their, out of their view so they can go do something more special.

That's the kind of interaction, the kind of speciality and specialist week that AI can bring to the market. You're really talking about redefining some of your processes to accommodate this new aspect, this new virtual. Team, yes, great way to look at it. As you take those mundane tasks out of your workflow, what can those employees be doing that provides better value to the company, that provides, you know, higher quality interactions with the customer? Because those things will always

be there. People will always be needed. But taking some of those things that you know, in some cases can be frustrating because you're answering the same question over and over again. Automating that and then making sure you can work with the human. At the end of the day, those are critical aspects to making sure that we have that human to AI interaction nailed. Do you have any advice on on this notion of redefining the roles to work successfully with digital workers?

What can you do to delegate administrative tasks as an example or things again that you don't want to do? So One really tangible example of this is if you take a call, at the end of the call, someone needs to summarize the notes into the CRM as an example. And what I can do for you very quickly is summarize those notes for you. Now you can of course go in and edit those if you want to, but having to be posted in for you automatically is a summary that you can accept or you can edit later.

That is an example of an administrative task and an overhead that you probably don't want your employees to have to worry about. As they do that, then they can actually start to put their time and attention towards other things. So I think it's critical to look at those, at those parts of it and then figure out what the opportunities are that maybe you haven't been able to look at before with your employees that that they can now lean into.

So again, you're really starting with simple labor saving use cases. Correct. Exactly. What about privacy and security

concerns? First of all, make sure that you're using cloud systems and AI systems that have published security policies with, with, you know, encryption, fail safes, things of that nature. Can't say enough about that. And making sure that those things are happening. Usually that's happening with the commercial vendor, but you want to absolutely double check that that's that's the case. You also want to make sure that you tune the AI to respect your

privacy policy. So if there's things you don't want the AI to ask, if for example, if your medical, you probably don't want to ask for certain patient information, you don't want to ask for things like Social Security number. So tuning your security policies with the AI to make sure that it doesn't ask for things that you don't want to get access to.

Make sure that not only is the technology safe for you to use, but you're keeping your customers and your business safe from anything else that might come in and be captured accidentally as part of the system. So you protect the company and then also the users because there is a, there's a natural curiosity about how AI will

handle our data and our privacy. And so you can secure that by making sure that your customers understand it and you're transparent with them about what you're capturing and what you're not through your AI systems, which is a critical component of success. Damon, where is all this headed?

We will see a much, much better personalization and the ability to interact with people as if they were talking to a person. So imagine as an example, if you called and do like, let's say an automotive dealer as an example. I know you own a, you know, 2024 Toyota 4 runner, right? I can actually bring that information in and, and ask and say, are you calling about that particular vehicle, right? Or I can call, I can ask about something that's very, very personal towards you.

And so I think that's one thing you're going to see the latency will improve. So the ability for you and I to talk and an AI to talk exactly like we are at the exact same pace will be very, very critical. And then I think the other thing you're going to see is we talked a little bit about agentic AI and the ability to take actions

on your behalf. And so as tools emerge, become more integrated with your different systems, being able to take more actions on your behalf and make that more seamless. And that's really where you'll see a force multiplication for businesses where we can take it can take common actions, not just answer common questions, but take common actions that might span different systems in your environment. Those are things that are happening.

Many of those are there today. It's only going to get better as we move forward. Exciting times ahead.

Absolutely. Making it practical for all customers to be able to adopt is what our missions all about. Damon Covey from Go to Thanks for taking time to chat with us today. Thank you, Michael. Great to be here.