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.