Brooke Lynch: 00:00:10.800 - 00:00:27.199
Hi everyone. I am very excited to introduce our next speaker, Ali Merchant, CEO of CallBotics. We are going to be discussing AI taking over the front lines. So, what that means for the role of the agent and the future of experiences and we're so excited to have you join us, Ali. Welcome.
Ali Merchant: 00:00:29.519 - 00:00:31.119
Thank you so much. Thank you for having me.
Brooke Lynch: 00:00:32.079 - 00:00:38.399
Of course. So before we dive in, as always, I'd love it if you could just share a brief introduction on yourself and your role at Callbotics.
Ali Merchant: 00:00:40.960 - 00:03:57.280
Of course. So, of course, I'm Ali Merchant, you know, I'm the CEO of CallBotics. Uh, to give you a little background about myself and how CallBotics came into existence, basically. So 17 years back I founded this another company called AM Infoweb where basically we help BPOs and enterprises with in-house contact centers uh set up their contact centers uh operate them scale them trans you know transform them uh and for when we started the company we were like five people today we are close to 2,000 people there and obviously you I have because when we started we were just five people. I have been through all the roles of agent, team leader, operations manager, and then, for a long, long time, I have been the CEO as well. Uh, that being said, I have lived all those roles, lived the realities of the contact center for 17 years, and how CallBotics came into existence. Uh so when obviously the AI era arrived ChatGPT came in we were all stunned what is happening how is this even possible and that's when we you know set up a dedicated team which we called CallBotics uh to build a platform which build a platform that does conversational AI and voice automation. So what we did was we filtered people out of that uh the other organization the best technical people the best uh leaders contact center leaders uh who at least had an experience of 10 years 12 15 years and we put them together we trained them and including myself I devoted most of my time there that uh let's build something good but at the end of the day our responsibility was to make sure that our we are getting the best solution for our clients right so we were also benchmarking other platforms deploying them for those for them uh but a very interesting thing happened wherever we had deployed CallBotics we saw at least 30% more resolution rates meaning you know AI agents were able to resolve 30% more calls and the CSAT or customer satisfaction was also so higher in those queues and that's when we knew we have something really really good over here and being an operator at heart a contact center leader at heart you know we wanted that and after deploying that so as customer zero was AM Infoweb right and the customers we had over there and firsthand as a contact center leader I saw how it changed my life our leaders life and how it kind of um you know made things really easy for us. So we wanted more and more people to be able to benefit from it. That's how CallBotics came into existence. So we said that so that a lot of people can benefit from it, we launched it as a separate company, a SaaS company. So altogether
Brooke Lynch: 00:04:00.959 - 00:04:43.440
Thank you for sharing that journey and really taking us along, because I as you mentioned, I mean, you've been in every role in the contact center space, so you really know how this technology and these tools benefit your team, the contact center, and your customers. So such an exciting time in the space, and really excited to talk more about how you've been able to leverage this technology so effectively. Um, and this session that we're focused on right now is talking about AI taking on the front line. You mentioned that, you know, you've seen 30% improvement, which is really exciting. Can you share some insight on what this new dynamic will look like, where AI is taking on the front line, and how it will differ from what organizations are doing today?
Ali Merchant: 00:04:46.880 - 00:12:15.920
I think that's a great question, right? Uh what and I'm sure you know a lot of leaders already know this and but there are obviously I come across conversation where leaders have a misunderstanding what it can do or what it means for it to take the front line in my humble understanding it basically means that almost every conversation first hits AI uh except for obviously a very few predefined set of scenarios where maybe due to compliance or you know certain strategic initiatives humans need to talk first.
And everything else you know has to go through AI first. So what the AI does is you know when a call comes in and when I say call and I mention conversations is because I think with most platforms at least with CallBotics we have this that uh obviously not a lot of advancement in terms of technology happened on the call side and hence uh that is where the maximum value lies today but the same capability can be extended to chat and emails, social media, right? So I say conversations generally, but you know, any call or conversation that hits a contact center, the AI first kind of listens to it, uh, understands the intent of the call, right? Then it kind of you know sometimes some use cases, some workflows we need to verify the customer. So it kind of verifies the customer, uh, fetches the data that it needs to have through the integration it has or the data that you have fed into the platform, and then basically resolves it just like a human, and all this happens in a very natural human way.
So we obviously in a we have tracked in a lot of scenarios we track you know like um if what happens is in a lot of we work with multiple global companies right so in some cases they don't need to mention if it's an AI agent uh that is you know basically having the conversation and in those scenarios we tracked if the customers actually knew it was an AI agent uh long story short less than half percent situations or or calls or conversations is where uh customers understood that if it was an AI agent.
So that's what it does and then there is and what we are seeing is approximately across companies different workflows around you know 80% of these conversations and calls are automated and 20% are then escalated to a human agent with full context with you know even suggestions as to what needs to be done on that call and these are generally you know those calls where um either it is very emotionally intensive call or it is very very complex call or multiple decisions need to be taken or multiple coordinations need to happen within the organization you need to kind of probably get up from your desk and ask someone right these are those kind of scenarios that we have observed so if I have to say that what does it you know mean uh in my understanding except for those exceptional scenarios most conversations most calls first hit AI and then you know there is defined rules situations where it escalates with full context suggestion to the human agent.
I mean, yeah, from our own research from at CCW Digital, we've found that most leaders agree that they believe that AI is going to take on the bulk of that interaction at the front, and then for anything that needs, you know, is potentially more complex or needs a little bit more attention, that will be escalated to the human. So, definitely see that as kind of the next step, and also it certainly supports the agent and the customer's experience.
Um, but I wanted to talk a little bit about challenges because your clients, I'm sure, are facing challenges, and AI can really support a lot of these things that are still kind of um, you know, obstacles in the contact center. So, in 2025, customers are still facing challenges like long wait times, repetitive conversations, and just generally disconnected experiences. So, what are some of the key challenges that your clients are facing right now, and how do you see AI really solving them?
I think the biggest challenge is you know I mean practically as an as a contact center leader right you know uh hiring people attrition training them making sure that the there is this consistency in brand right you know all these are like very real challenges and then on the customer side I mean in today's world where time is of the essence such long wait times for over a decade I myself have experienced this that whenever I'm calling somewhere I expect that either a IVR will happen which will be like you know this very uh the experience is overall not very good or you know it will be a self-service portal or at best it could be uh you know that maybe after 5 to 10 minutes of hold uh I get to talk to someone just think of this scenario you yourself are a customer I myself I'm a customer you know you call and immediately someone says hi this is Jenny how can I help you today that pure joy honestly that comes out of that uh I think you know uh is a very good challenge to solve so that is something you know that customers solve with AI agents uh that being said uh with that you know also are these very long you know conversations that happen.
We, as a contact center, ourselves know that a lot of times we do not you know we have this high attrition rate. So every time we have new agents in our organization right and they need to go through documents to provide that those answers but AI agents they are connected to these systems they are integrated with systems they have all the answers the answers are always consistent.
So that is the second thing that you know it kind of uh solves for them and then obviously you know cost has always been a very very large challenge with contact centers you have to do more and more with less and less over the period of time and uh we saw that you know with AI agents if even if you have offshored you save close to 65% on your call costs when if you're onshore you are saving close to 75 to 90%.
So I think obviously there are more many more challenges but these are the main main challenges these that our customers are facing and you know uh AI agents kind of solve them in a very big way.
Brooke Lynch: 00:12:17.920 - 00:12:59.600
Thanks for sharing. I mean, we definitely see so many of those challenges on our end, too. And AI certainly has the ability to really support the agent and help them, you know, elevate what they're doing, which we're going to talk a little bit more about in a few minutes. But I wanted to talk a little bit about our market study because we worked together on what I think was a really interesting piece. Um, and so we discussed the idea that a balance of AI and human might not be possible or even productive in some cases. Um, so how do you see AI and humans collaborating? What tasks do you think AI is really great at taking on versus where should the agent still remain kind of king?
Ali Merchant: 00:13:02.000 - 00:18:37.360
I think that's a great question you know uh because this is where we have observed that most organizations or you know leaders come and get stuck. We ourselves got stuck there too a little less than two years back when we were implementing it for our you know uh for one of our other companies. Uh when it comes to what should be automated within a contact center and what should be elevated at a higher level at a you know maybe 30–40,000 ft level I can mention but one thing at the outset that I feel we should mention is that it differs from every organization to organization you know we have to respect this is what I have learned with many many mistakes over the last two decades that you have to appreciate that every organization, every contact center is unique, their goals are unique, their workflows are unique, use cases are unique within that their strategy is unique. So this kind of you know you cannot have a one piece or one you know size-fits-all kind of an approach.
But that being said uh the larger challenge that we have seen is starting. There is so much anxiety within senior leaders as well as agents about AI agents and you know AI uh and we all have these conversations you know every day every call every conference that you know what about jobs and stuff like that right uh so I think and can it actually do the job so senior leaders are concerned if it can get the job done uh the agents are concerned what that means for them. So contact center leaders have this responsibility two major responsibility one to prove that it works and second you know the value that it creates and third that how it will positively impact all the stakeholders.
So that being said, you know, when we started off this journey a little less than two years ago, we made the mistake of trying to automate the most complex use cases or complex workflows. I would say that given that your first goal should be to prove the value and what it means for everyone and their roles, right? You should they we should start with repeatable rule-driven data-driven kind of you know tasks and then basically workflows where success and failure has a clear definition.
What happens is you know they say right that seeing is believing. Once leaders see that nothing terribly wrong goes there uh and what level of uh you know CSAT score increase they see uh the level of stability that comes within a contact center and then on top of that one of the most important things is that at the end of the day cost is a reality and the level of cost efficiency that comes in right so they are now happy relaxed and then you have your buyer and then you have your agents who see that this because of this you get your jobs become your job becomes more meaningful and you know you are now working on more meaningful work and because of that your overall pay designation respect everything is you know kind of increasing.
So I think that is what you know while your question was what is automated I would like to say this that you know it is important to start and you know start at this point uh and these could be you know calls like verification calls uh you know detail collection calls scheduling calls in some cases we have pushed customers that you know start with weekend queues or after hours queues but just start right so anything that is you know simple, repeatable, you start from there, automate that and then you know anything uh and it kind of takes care of bulk of the conversations and then you keep on you know just like you train your human agents you keep training your AI agents and they'll get better and better.
What gets elevated or you know transferred or escalated to a human agent will be things that require which will be like around 20% of the calls or conversations which will be like you know where multiple decisions are required or multi-stakeholder coordination is required or the intensity of the emotions or frustration is very high there are policy exceptions to be made or you know very delicate scenarios.
So I think uh that is what uh needs to be elevated to your humans and so everything and anything except for a few things gets to AI and then you know everything else the scenarios that I mentioned goes to human agents. I think the rule of thumb we generally ask our leaders and you know our customers or newer customers to follow is that uh if a question to an answer for five agents is the same it can be automated and if there is a lot of nuance it goes to humans. So uh in a funny way we always say that let AI take the first swing and then let's let you know humans take the meaningful swings.
Brooke Lynch: 00:18:39.520
Right
Brooke Lynch: 00:18:40.480 - 00:19:02.640
So we talked a little bit about the actual people in the process, and we want to make sure that AI isn't dehumanizing the experience because that's very important to customers, that it's really amplifying the people, so can you talk a little bit more about how AI is amplifying the customer experience and making it still human as we lean into tech.
Ali Merchant: 00:19:05.600 - 00:21:55.679
So I think you know I I'll put it this way right that first of all you know AI agents are not um they can just have a very natural conversation like a human be empathetic. We have use cases where you know let's say one of the use cases that we came across was first notice of loss. If your house was hit by a storm, you need to call your insurance company and let and let them know uh give that first notice of you know what happened and obviously it's a distressing time and still you know we have AI agents uh deployed there and they have that very human conversation.
So as I mentioned earlier as well if compliance allows your strategy allows and if you're not saying that it's an AI agent most less than half% of the times they actually understand in fact they're very happy there are no hold times uh the overall clarity speed at which they get answers is so fast that you know they're just happy and overall CSATs are increasing but that being said let's have a second scenario where we say that okay you have to say that it is an AI agent, right?
I as the as a customer, I am busy. I have my own personal challenges. You know, I am getting late to uh go and pick up my daughter or you know, I have to get somewhere. I have my own challenges, right? So, I am not most of the use cases and while I said that on uh these kind of sensitive use cases as well, it works really well. But let's say most use cases they are about either you know getting an update getting some information sharing some information right I just want that uh I do it in the less most less possible time which basically means no hold time and then you know I get the answers correct.
So as long as the AI is understanding the customers it's not making them repeat respecting their time and by resolving it as quick as it can right and then if required it is very there is a very smooth escalation to a human agent with full context so the they don't have to repeat themselves I think the overall experience becomes so nice that you know I as a customer and what we are seeing from CSAT scores and conversations and surveys that we are taking they don't really you know mind talking to an AI agent and as I said the AI agent also will do a lot of can also do uh very very natural conversations but I think trust is earned through that through experiences and you know not general theories I would say.
Brooke Lynch: 00:21:58.159 - 00:23:14.080
I agree. I mean, I like the point you make about the speed and how realistically most of us are just looking for an answer, and so whatever can give us that answer in the most seamless, intuitive way sometimes is enough. I mean, we do of course love engaging with people, with agents, but for simple issues that can be resolved very quickly, that is kind of the more empathetic choice. I mean, we talk a lot about empathy here at CCW Digital, how empathy isn't necessarily about being friendly or nice. It's really just solving the problem in the way that makes sense for the customer. So if that is just answering it really quickly, then that is kind of the most empathetic way to approach the conversation. So I completely agree. I think as we look ahead, it will be much more of this kind of dynamic where when AI makes sense, customers lean in, and then when they have, you know, a little bit more of a complex, deeper issue, that's when we um really rely on the agent. Um, as we wrap up the conversation here, you mentioned that the most important piece is just starting, and for so many people that can be incredibly daunting and overwhelming. So, what is one thing that leaders need to start doing today if they really want to begin preparing their teams for this AI-first future?
Ali Merchant: 00:23:17.919 - 00:26:29.279
I think the as you rightly mentioned from my earlier conversation that you need to start, right? And they need to first of all I think you know the most important piece I as a contact center leader know this that you know you need the right partner and then you know someone who can not just provide the platform but if required also give you access to information like for example uh wherever we make deployments right we you know provide our customers or our clients or partners with these documents like you know what will be the um the new skills that their people are going to require meaning you know and the designations that go along with them.
So for example the new designations will be uh these agents will be have to be retrained to become AI supervisors uh conversation designers you know AIQ analysts a large part of the role for those 20% knowledge-intensive emotion-intensive conversations will be you know exception resolution specialists and then training material around that right and uh kind they need to also create this cultural shift that you know AI agents and meaning AI and human it's a partnership and not you know against each other.
And then basically show them as I mentioned earlier as well how uh it will benefit them how it evolves their roles uh and you know hence they get paid better they get more respect they have more fulfilling roles. One of the things you know a very unique thing that we observe was leaders who went on this journey maybe one or two years back right they faced a lot of resistance within their organization even from their seniors from their agents everyone around them right but the good thing is once they kind of uh addressed the initial anxieties and they saw the stakeholders saw what value it created uh they kind of you know uh I mean I don't know of anyone who has not got a promotion after that.
Everyone is promoted. The organizations that are now looking to um you know deploy voice agents they are looking for those people and hence you know they are offering more and more pay and more and more higher designations. But then the existing organizations who have done it they don't have a pool from where they can hire people from outside. So to maintain them they are also you know uh paying really well and that long due respect that contact center leaders should have they do have but even you know now because they are becoming more proactive rather than reactive uh I think that is also one thing that we have observed.
So I think yeah largely cultural shift as well as you know uh training on these kind of newer roles is what we are looking.
Brooke Lynch: 00:26:31.679 - 00:26:42.880
Definitely such important really points to be focusing in on. So as we end off here, thank you so much Ali for joining us. Any final thoughts or anything you want to share as as we close out the conversation today?
Ali Merchant: 00:26:45.039 - 00:27:51.520
No, I think you know uh I think the AI uh technology is there uh over the period of time. I think adoption is what needs to happen. I say this not as the CEO of CallBotics but as a fellow contact center leader.
Not only do you create better value for your stakeholders but you know much easier life for lives for yourself because you end up building more reliable, more consistent, more faster and uh more dependable contact centers. Uh I would just say start on this journey. Uh and as a final statement to address the biggest uh anxiety that will it be human uh trust me from or trust me from you know lived experiences that ironically uh this path leads to more humanity.
Brooke Lynch: 00:27:54.880 - 00:28:03.520
Thank you so much, Ali. I think that's a great place for us to kind of close off here. Thank you so much for sharing your insight and joining us today. I so appreciate it.
Ali Merchant: 00:28:04.799
Likewise, I appreciate it. Thank you.
Ali Merchant, CEO of CallBotics and a long-time contact center operator, explains how AI is moving to the front line of customer interactions. In an AI-first model, most calls and conversations start with an AI agent that can understand intent, verify customer identity, retrieve data via integrations, and resolve issues in a natural way. Only a smaller set of conversations, typically complex, emotionally sensitive, or decision-heavy, are escalated to humans with full context and suggested next steps.
Ali emphasizes that CallBotics delivers higher resolution rates because it is built with deep contact center leadership input, not just technology leadership. He also highlights the practical realities driving adoption: hiring and attrition pressures, inconsistent answers from new agents, long hold times, and rising cost expectations. The core message is to start small, prove value quickly with simple repeatable workflows, and then expand. Finally, he frames AI adoption as a shift that can make operations more human by giving customers faster answers and giving agents more meaningful work.
Brooke Lynch: 00:00:10.800 - 00:00:27.199
Hi everyone. I am very excited to introduce our next speaker, Ali Merchant, CEO of CallBotics. We are going to be discussing AI taking over the front lines. So, what that means for the role of the agent and the future of experiences and we're so excited to have you join us, Ali. Welcome.
Ali Merchant: 00:00:29.519 - 00:00:31.119
Thank you so much. Thank you for having me.
Brooke Lynch: 00:00:32.079 - 00:00:38.399
Of course. So before we dive in, as always, I'd love it if you could just share a brief introduction on yourself and your role at Callbotics.
Ali Merchant: 00:00:40.960 - 00:03:57.280
Of course. So, of course, I'm Ali Merchant, you know, I'm the CEO of CallBotics. Uh, to give you a little background about myself and how CallBotics came into existence, basically. So 17 years back I founded this another company called AM Infoweb where basically we help BPOs and enterprises with in-house contact centers uh set up their contact centers uh operate them scale them trans you know transform them uh and for when we started the company we were like five people today we are close to 2,000 people there and obviously you I have because when we started we were just five people. I have been through all the roles of agent, team leader, operations manager, and then, for a long, long time, I have been the CEO as well. Uh, that being said, I have lived all those roles, lived the realities of the contact center for 17 years, and how CallBotics came into existence. Uh so when obviously the AI era arrived ChatGPT came in we were all stunned what is happening how is this even possible and that's when we you know set up a dedicated team which we called CallBotics uh to build a platform which build a platform that does conversational AI and voice automation. So what we did was we filtered people out of that uh the other organization the best technical people the best uh leaders contact center leaders uh who at least had an experience of 10 years 12 15 years and we put them together we trained them and including myself I devoted most of my time there that uh let's build something good but at the end of the day our responsibility was to make sure that our we are getting the best solution for our clients right so we were also benchmarking other platforms deploying them for those for them uh but a very interesting thing happened wherever we had deployed CallBotics we saw at least 30% more resolution rates meaning you know AI agents were able to resolve 30% more calls and the CSAT or customer satisfaction was also so higher in those queues and that's when we knew we have something really really good over here and being an operator at heart a contact center leader at heart you know we wanted that and after deploying that so as customer zero was AM Infoweb right and the customers we had over there and firsthand as a contact center leader I saw how it changed my life our leaders life and how it kind of um you know made things really easy for us. So we wanted more and more people to be able to benefit from it. That's how CallBotics came into existence. So we said that so that a lot of people can benefit from it, we launched it as a separate company, a SaaS company. So altogether
Brooke Lynch: 00:04:00.959 - 00:04:43.440
Thank you for sharing that journey and really taking us along, because I as you mentioned, I mean, you've been in every role in the contact center space, so you really know how this technology and these tools benefit your team, the contact center, and your customers. So such an exciting time in the space, and really excited to talk more about how you've been able to leverage this technology so effectively. Um, and this session that we're focused on right now is talking about AI taking on the front line. You mentioned that, you know, you've seen 30% improvement, which is really exciting. Can you share some insight on what this new dynamic will look like, where AI is taking on the front line, and how it will differ from what organizations are doing today?
Ali Merchant: 00:04:46.880 - 00:12:15.920
I think that's a great question, right? Uh what and I'm sure you know a lot of leaders already know this and but there are obviously I come across conversation where leaders have a misunderstanding what it can do or what it means for it to take the front line in my humble understanding it basically means that almost every conversation first hits AI uh except for obviously a very few predefined set of scenarios where maybe due to compliance or you know certain strategic initiatives humans need to talk first.
And everything else you know has to go through AI first. So what the AI does is you know when a call comes in and when I say call and I mention conversations is because I think with most platforms at least with CallBotics we have this that uh obviously not a lot of advancement in terms of technology happened on the call side and hence uh that is where the maximum value lies today but the same capability can be extended to chat and emails, social media, right? So I say conversations generally, but you know, any call or conversation that hits a contact center, the AI first kind of listens to it, uh, understands the intent of the call, right? Then it kind of you know sometimes some use cases, some workflows we need to verify the customer. So it kind of verifies the customer, uh, fetches the data that it needs to have through the integration it has or the data that you have fed into the platform, and then basically resolves it just like a human, and all this happens in a very natural human way.
So we obviously in a we have tracked in a lot of scenarios we track you know like um if what happens is in a lot of we work with multiple global companies right so in some cases they don't need to mention if it's an AI agent uh that is you know basically having the conversation and in those scenarios we tracked if the customers actually knew it was an AI agent uh long story short less than half percent situations or or calls or conversations is where uh customers understood that if it was an AI agent.
So that's what it does and then there is and what we are seeing is approximately across companies different workflows around you know 80% of these conversations and calls are automated and 20% are then escalated to a human agent with full context with you know even suggestions as to what needs to be done on that call and these are generally you know those calls where um either it is very emotionally intensive call or it is very very complex call or multiple decisions need to be taken or multiple coordinations need to happen within the organization you need to kind of probably get up from your desk and ask someone right these are those kind of scenarios that we have observed so if I have to say that what does it you know mean uh in my understanding except for those exceptional scenarios most conversations most calls first hit AI and then you know there is defined rules situations where it escalates with full context suggestion to the human agent.
I mean, yeah, from our own research from at CCW Digital, we've found that most leaders agree that they believe that AI is going to take on the bulk of that interaction at the front, and then for anything that needs, you know, is potentially more complex or needs a little bit more attention, that will be escalated to the human. So, definitely see that as kind of the next step, and also it certainly supports the agent and the customer's experience.
Um, but I wanted to talk a little bit about challenges because your clients, I'm sure, are facing challenges, and AI can really support a lot of these things that are still kind of um, you know, obstacles in the contact center. So, in 2025, customers are still facing challenges like long wait times, repetitive conversations, and just generally disconnected experiences. So, what are some of the key challenges that your clients are facing right now, and how do you see AI really solving them?
I think the biggest challenge is you know I mean practically as an as a contact center leader right you know uh hiring people attrition training them making sure that the there is this consistency in brand right you know all these are like very real challenges and then on the customer side I mean in today's world where time is of the essence such long wait times for over a decade I myself have experienced this that whenever I'm calling somewhere I expect that either a IVR will happen which will be like you know this very uh the experience is overall not very good or you know it will be a self-service portal or at best it could be uh you know that maybe after 5 to 10 minutes of hold uh I get to talk to someone just think of this scenario you yourself are a customer I myself I'm a customer you know you call and immediately someone says hi this is Jenny how can I help you today that pure joy honestly that comes out of that uh I think you know uh is a very good challenge to solve so that is something you know that customers solve with AI agents uh that being said uh with that you know also are these very long you know conversations that happen.
We, as a contact center, ourselves know that a lot of times we do not you know we have this high attrition rate. So every time we have new agents in our organization right and they need to go through documents to provide that those answers but AI agents they are connected to these systems they are integrated with systems they have all the answers the answers are always consistent.
So that is the second thing that you know it kind of uh solves for them and then obviously you know cost has always been a very very large challenge with contact centers you have to do more and more with less and less over the period of time and uh we saw that you know with AI agents if even if you have offshored you save close to 65% on your call costs when if you're onshore you are saving close to 75 to 90%.
So I think obviously there are more many more challenges but these are the main main challenges these that our customers are facing and you know uh AI agents kind of solve them in a very big way.
Brooke Lynch: 00:12:17.920 - 00:12:59.600
Thanks for sharing. I mean, we definitely see so many of those challenges on our end, too. And AI certainly has the ability to really support the agent and help them, you know, elevate what they're doing, which we're going to talk a little bit more about in a few minutes. But I wanted to talk a little bit about our market study because we worked together on what I think was a really interesting piece. Um, and so we discussed the idea that a balance of AI and human might not be possible or even productive in some cases. Um, so how do you see AI and humans collaborating? What tasks do you think AI is really great at taking on versus where should the agent still remain kind of king?
Ali Merchant: 00:13:02.000 - 00:18:37.360
I think that's a great question you know uh because this is where we have observed that most organizations or you know leaders come and get stuck. We ourselves got stuck there too a little less than two years back when we were implementing it for our you know uh for one of our other companies. Uh when it comes to what should be automated within a contact center and what should be elevated at a higher level at a you know maybe 30–40,000 ft level I can mention but one thing at the outset that I feel we should mention is that it differs from every organization to organization you know we have to respect this is what I have learned with many many mistakes over the last two decades that you have to appreciate that every organization, every contact center is unique, their goals are unique, their workflows are unique, use cases are unique within that their strategy is unique. So this kind of you know you cannot have a one piece or one you know size-fits-all kind of an approach.
But that being said uh the larger challenge that we have seen is starting. There is so much anxiety within senior leaders as well as agents about AI agents and you know AI uh and we all have these conversations you know every day every call every conference that you know what about jobs and stuff like that right uh so I think and can it actually do the job so senior leaders are concerned if it can get the job done uh the agents are concerned what that means for them. So contact center leaders have this responsibility two major responsibility one to prove that it works and second you know the value that it creates and third that how it will positively impact all the stakeholders.
So that being said, you know, when we started off this journey a little less than two years ago, we made the mistake of trying to automate the most complex use cases or complex workflows. I would say that given that your first goal should be to prove the value and what it means for everyone and their roles, right? You should they we should start with repeatable rule-driven data-driven kind of you know tasks and then basically workflows where success and failure has a clear definition.
What happens is you know they say right that seeing is believing. Once leaders see that nothing terribly wrong goes there uh and what level of uh you know CSAT score increase they see uh the level of stability that comes within a contact center and then on top of that one of the most important things is that at the end of the day cost is a reality and the level of cost efficiency that comes in right so they are now happy relaxed and then you have your buyer and then you have your agents who see that this because of this you get your jobs become your job becomes more meaningful and you know you are now working on more meaningful work and because of that your overall pay designation respect everything is you know kind of increasing.
So I think that is what you know while your question was what is automated I would like to say this that you know it is important to start and you know start at this point uh and these could be you know calls like verification calls uh you know detail collection calls scheduling calls in some cases we have pushed customers that you know start with weekend queues or after hours queues but just start right so anything that is you know simple, repeatable, you start from there, automate that and then you know anything uh and it kind of takes care of bulk of the conversations and then you keep on you know just like you train your human agents you keep training your AI agents and they'll get better and better.
What gets elevated or you know transferred or escalated to a human agent will be things that require which will be like around 20% of the calls or conversations which will be like you know where multiple decisions are required or multi-stakeholder coordination is required or the intensity of the emotions or frustration is very high there are policy exceptions to be made or you know very delicate scenarios.
So I think uh that is what uh needs to be elevated to your humans and so everything and anything except for a few things gets to AI and then you know everything else the scenarios that I mentioned goes to human agents. I think the rule of thumb we generally ask our leaders and you know our customers or newer customers to follow is that uh if a question to an answer for five agents is the same it can be automated and if there is a lot of nuance it goes to humans. So uh in a funny way we always say that let AI take the first swing and then let's let you know humans take the meaningful swings.
Brooke Lynch: 00:18:39.520
Right
Brooke Lynch: 00:18:40.480 - 00:19:02.640
So we talked a little bit about the actual people in the process, and we want to make sure that AI isn't dehumanizing the experience because that's very important to customers, that it's really amplifying the people, so can you talk a little bit more about how AI is amplifying the customer experience and making it still human as we lean into tech.
Ali Merchant: 00:19:05.600 - 00:21:55.679
So I think you know I I'll put it this way right that first of all you know AI agents are not um they can just have a very natural conversation like a human be empathetic. We have use cases where you know let's say one of the use cases that we came across was first notice of loss. If your house was hit by a storm, you need to call your insurance company and let and let them know uh give that first notice of you know what happened and obviously it's a distressing time and still you know we have AI agents uh deployed there and they have that very human conversation.
So as I mentioned earlier as well if compliance allows your strategy allows and if you're not saying that it's an AI agent most less than half% of the times they actually understand in fact they're very happy there are no hold times uh the overall clarity speed at which they get answers is so fast that you know they're just happy and overall CSATs are increasing but that being said let's have a second scenario where we say that okay you have to say that it is an AI agent, right?
I as the as a customer, I am busy. I have my own personal challenges. You know, I am getting late to uh go and pick up my daughter or you know, I have to get somewhere. I have my own challenges, right? So, I am not most of the use cases and while I said that on uh these kind of sensitive use cases as well, it works really well. But let's say most use cases they are about either you know getting an update getting some information sharing some information right I just want that uh I do it in the less most less possible time which basically means no hold time and then you know I get the answers correct.
So as long as the AI is understanding the customers it's not making them repeat respecting their time and by resolving it as quick as it can right and then if required it is very there is a very smooth escalation to a human agent with full context so the they don't have to repeat themselves I think the overall experience becomes so nice that you know I as a customer and what we are seeing from CSAT scores and conversations and surveys that we are taking they don't really you know mind talking to an AI agent and as I said the AI agent also will do a lot of can also do uh very very natural conversations but I think trust is earned through that through experiences and you know not general theories I would say.
Brooke Lynch: 00:21:58.159 - 00:23:14.080
I agree. I mean, I like the point you make about the speed and how realistically most of us are just looking for an answer, and so whatever can give us that answer in the most seamless, intuitive way sometimes is enough. I mean, we do of course love engaging with people, with agents, but for simple issues that can be resolved very quickly, that is kind of the more empathetic choice. I mean, we talk a lot about empathy here at CCW Digital, how empathy isn't necessarily about being friendly or nice. It's really just solving the problem in the way that makes sense for the customer. So if that is just answering it really quickly, then that is kind of the most empathetic way to approach the conversation. So I completely agree. I think as we look ahead, it will be much more of this kind of dynamic where when AI makes sense, customers lean in, and then when they have, you know, a little bit more of a complex, deeper issue, that's when we um really rely on the agent. Um, as we wrap up the conversation here, you mentioned that the most important piece is just starting, and for so many people that can be incredibly daunting and overwhelming. So, what is one thing that leaders need to start doing today if they really want to begin preparing their teams for this AI-first future?
Ali Merchant: 00:23:17.919 - 00:26:29.279
I think the as you rightly mentioned from my earlier conversation that you need to start, right? And they need to first of all I think you know the most important piece I as a contact center leader know this that you know you need the right partner and then you know someone who can not just provide the platform but if required also give you access to information like for example uh wherever we make deployments right we you know provide our customers or our clients or partners with these documents like you know what will be the um the new skills that their people are going to require meaning you know and the designations that go along with them.
So for example the new designations will be uh these agents will be have to be retrained to become AI supervisors uh conversation designers you know AIQ analysts a large part of the role for those 20% knowledge-intensive emotion-intensive conversations will be you know exception resolution specialists and then training material around that right and uh kind they need to also create this cultural shift that you know AI agents and meaning AI and human it's a partnership and not you know against each other.
And then basically show them as I mentioned earlier as well how uh it will benefit them how it evolves their roles uh and you know hence they get paid better they get more respect they have more fulfilling roles. One of the things you know a very unique thing that we observe was leaders who went on this journey maybe one or two years back right they faced a lot of resistance within their organization even from their seniors from their agents everyone around them right but the good thing is once they kind of uh addressed the initial anxieties and they saw the stakeholders saw what value it created uh they kind of you know uh I mean I don't know of anyone who has not got a promotion after that.
Everyone is promoted. The organizations that are now looking to um you know deploy voice agents they are looking for those people and hence you know they are offering more and more pay and more and more higher designations. But then the existing organizations who have done it they don't have a pool from where they can hire people from outside. So to maintain them they are also you know uh paying really well and that long due respect that contact center leaders should have they do have but even you know now because they are becoming more proactive rather than reactive uh I think that is also one thing that we have observed.
So I think yeah largely cultural shift as well as you know uh training on these kind of newer roles is what we are looking.
Brooke Lynch: 00:26:31.679 - 00:26:42.880
Definitely such important really points to be focusing in on. So as we end off here, thank you so much Ali for joining us. Any final thoughts or anything you want to share as as we close out the conversation today?
Ali Merchant: 00:26:45.039 - 00:27:51.520
No, I think you know uh I think the AI uh technology is there uh over the period of time. I think adoption is what needs to happen. I say this not as the CEO of CallBotics but as a fellow contact center leader.
Not only do you create better value for your stakeholders but you know much easier life for lives for yourself because you end up building more reliable, more consistent, more faster and uh more dependable contact centers. Uh I would just say start on this journey. Uh and as a final statement to address the biggest uh anxiety that will it be human uh trust me from or trust me from you know lived experiences that ironically uh this path leads to more humanity.
Brooke Lynch: 00:27:54.880 - 00:28:03.520
Thank you so much, Ali. I think that's a great place for us to kind of close off here. Thank you so much for sharing your insight and joining us today. I so appreciate it.
Ali Merchant: 00:28:04.799
Likewise, I appreciate it. Thank you.
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