“If AI Replaces Humans, We’re Doing It Wrong”/w Jhon Finch

John Finch: So think of it as a circle of forever improving and always adding to its knowledge by having these conversations, understanding which conversations are the best conversations and how that continues to improve and learn and get better. So it's taking all this voice, conversation, intelligence and being able to now provide outcomes based on that. There's a lot of talk about AI and how AI is replaced. And we really don't think that that's information to provide assistance to the humans that are actually answering a live customer inquiry.

Tamil: Welcome back to CX Insider podcast. I'm your host, Tamil, and today I'm joined by my co host Greg. And we're joined by very special guest John Finch from Ringcentral. Hello John.

Greg: Hello.

John Finch: Thanks for having me.

Tamil: Glad to have you here. Okay, so John, can you tell us a bit about yourself? Your role in Ringcentral and being based in San Francisco, the heart of Silicon Valley, shapes your perception on innovation and

John Finch: customer experience in San Francisco and in Silicon Valley. For my entire professional career has been something that's given me an edge up, I think, in terms of seeing this evolution of technologies come about, um, being in the space, particularly in customer engagement, customer service, contact center or whatever you want to call it, we keep seeing these innovations rolling through. And with AI now it's become something that is, um, very prevalent obviously, and it provides that next wave of innovation. And we've kind of really hit or gone beyond a tipping point of what that's going to mean. So being here talking to people, um, and just listening to other organizations, especially AI based organizations, which is a big thing here obviously in San Francisco, um, with OpenAI and other companies that are based here, really provides me with access to this innovation. Not only just from a work perspective, just friends and colleagues and other people that I've known throughout the years who are working in the same level of technology. And we all share notes and discuss sort of the future. So being a part of that is super cool to me and just that entrepreneurial spirit that exists throughout. And I think even though Ringcentral is a big organization, um, in comparison to a lot of companies, we are still operating very much like a startup, especially in this world of AI and innovation on a regular basis. And you kind of see that with how we've innovated, especially in the last couple of years and continuing to move ourselves forward throughout 2026.

Greg: That's awesome. And a major topic that runs through everything that CX right now is how organizations are striking. That balance between the human element and the AI element. When it comes to all customer let's, yeah, customer conversations, let's call it. Um, from your perspective where you see AI becoming more integrated into those conversations, what do you see as the sort of exciting opportunities but also potentially the challenges also?

John Finch: Yeah, it's a great question and I would answer it in multiple ways. I think um, the first way which is also kind of the most important right now is there's a lot of talk about AI and how AI is replacing humans. And we really don't think that that's the case. I personally don't think that's the case either. I think there's going to be shifts in how people are working. Um, but really AI is built to help humans not only get better service but also the humans on the other side working in the organization, the employees, the customer service agents in a full time contact center or even those that are answering customer inquiries and maybe in a less formal way are going to see the benefit and the value of AI. And it's going to be in a couple of different ways. I mean the first way really is like you know, missed calls, missed opportunities and leveraging sort of the incoming inquiries. Either customer service sales oriented revenue generating activities for businesses of all sizes. A lot of times the older technologies like IVRs and phone trees, these things aren't providing organizations with really what they need. They're difficult to maintain and manage. People are calling in and using them, are always mad about the doom loop that they get into with that solution. So it's never a really good situation on either end. So everybody ends up hanging up and no one knows what really happened. So gaining more credibility and the ability to answer these calls and make that a healthy experience for the caller and provide that opportunity to the business becomes one. We have a product called Aehr that we announced in general availability last summer. Um, we've got thousands of customers using that product today. Um, very fast growth and the value is definitely there and it's easy to set up, easy to use and it really is improving revenue for, for smaller organizations. We've got um, healthcare, uh, organizations of all sizes, especially using this to be able to triage and intake uh, appointments and get these calendared and scheduled without having a human have to do that and fumble through a lot of activities. We've seen them improve in revenue, um, customer satisfaction goes up. These are missed opportunities that improve. Like $1.7 million for a small company which is huge, a small healthcare company and regionally based in the Denver area. They see significant uptick in that. And then there's even you know, Public service organizations, right. Part of the government, um, being able to direct calls to the appropriate agencies based on location and helping kind of drive all of these calls that they get, about 40,000 of them per year into the right spot. So that's just one example. The other example is just helping the agents inside the organization, providing them with information in real time that really gets them the answers they need by the minute. So that it's listening to the call it's taking from information that it's gathered during other conversations that are led by humans and customer humans, um, to gather that information and provide that to the human throughout that assistance. So a customer service agent, full time or part time has the answers at their fingertips actually just right there. They don't have to click on anything, it's just coming up in real time and they can glance at it and review that information and communicate that to the customer and move on. Right. And you know that it's accurate, it's timely and it provides first contact resolution. Right. Which is always a key performance outcome that, uh, a key performance indicator and outcome that, that customer service, uh, organizations and companies of all sizes are looking for. So we really see it in revenue generation, customer, uh, service, you know, making customers happy, um, and continuing to differentiate themselves as businesses by never really losing those opportunities. Those are just a couple of examples

Tamil: that's really interesting and I guess you've kind of sort of answered the next question and how we're going to see collaboration between your human agents and your AI and how they're going to work together essentially in real time, palette, tools and um, everything a little deeper.

John Finch: Yeah, didn't mean to jump ahead. This stuff excites me though because I think.

Tamil: No, no, that's really good.

John Finch: Inside that question is the key. Right. And inside of it it's the envision of AI and human agents working together. Right. And that's what it's about. I think there are cost cutting elements, right. And we're seeing a lot of these things happen. But at the end of the day from good customer service, we like to say customer service should be effortless. It means that you just know it's happening. You're at a place, you're interacting with a place or brand or a business. And by the time you hang up the phone, that outcome leaves you kind of with a breath of fresh air. You didn't have to try too hard, they didn't have to try too hard, it just happened. And so I think of AI is adding that lightness, like air, um, to the whole Component. Right. Of that service level. Right. And so, you know, things that you handle in brick and mortar at a hotel and things like that, and even once you make the appointment and you know, get your billing organized and sort of, um, understand your pre visit, you know, activities that must be done when you're dealing with a healthcare agency or organization or dental office or doctor's office, you know, that's one thing, and then the brick and mortar is kind of the other experience. But you want that holistically to come together nicely. And I think AI, uh, can help organizations do that holistically without having to worry about the technology, without having to struggle through what is it that I need to make this happen. I think going through and working with a vendor like RingCentral as an example, and there are others out there, um, but I like to say we do it best because we do. Um, but at the end of the day, companies have these choices where they can implement this without thinking about it. And it's run by business users. And I think that's the most significant thing is being able to turn this on, not have to have a degree and name your favorite old company that used to build hardware and textbooks and trainings and certifications and monthly rollouts and upgrades and things like that. So all that stuff is gone. And AI is sort of surpassing what even is with SaaS, right. As a business. Um, so we don't see SaaS going away, but we see SaaS really being complemented by this. And SaaS is the communications layer, then AI is on top of that and using the data from conversations between humans, like all of us today, to be able to take action on their own and be autonomous. That leads me into this thing we want to talk about that we're announcing. That's coming up on March 10th. I know this podcast will come out, um, after that time, but we're announcing something pretty big in our, uh, portfolio. And, um, we announced aehr, as I mentioned earlier, uh, in last summer, right. As a ga. We announced it earlier in kind of controlled availability, if you will, or early access in February about a year ago and have seen great adoption. So we're introducing sort of the next level of that technology, which is called AER Pro. Um, AIR stands for AI Receptionist and AIR Pro stands for AI Representative. And I know that's a little confusing, but think of it sort of as the next level of capability. It really is an agentic voice, uh, first agentic AI solution or agent that can handle calls, similar to aehr, but more, more deeply so to work autonomously to solve a problem. Beyond booking an appointment or transferring a call to an individual, or gathering information based on FAQs or information that's in a database or a knowledge base, it can fully act as though it were a human agent to transact. So you think about it from the perspective of being able to build this to actually answer the phone at the front end, triage the conversation, have a human like interaction with the caller or the customer or the prospect, and then be able to provide them with effective information, verify their identity and then move through information and back office systems such as with healthcare EHR systems. Right. Healthcare record systems. Other elements that are necessary to do this transaction. Book an appointment, look up medical records, identify billing and then schedule an appointment, Help them close out that conversation and move them into the next phase of uh, coming in and visiting with the facility. So we're announcing this AI or Air Pro, I should say, which is the voice first AI agent and it has a studio, which we call AirPro Studio, to be able to build, deploy, test and observe the improvement of this agent throughout its life cycle. And so it goes very, very deep in terms of being able to answer customer inquiries and go even further into other capabilities that we'll be announcing beyond March as well. So early adopter program March 10th. Super excited about this, um, and really provides organizations with something, you know, sort of beyond what they can get today.

Tamil: Wow, that's huge. That's quite huge. And we're excited for that launch. Congrats. That's big. Um, and I guess that sort of leads me on. Bring Search Central works with huge voice and text databases. So how does that scale of data change what's possible for the customer engagement?

John Finch: Well, I think what you're going to see holistically is there's a couple of different things. So as we've talked about, we have pre built agents, right. So you've heard us talk about air, right, We've talked about, um, and that's sort of the automation piece. Air Pro is also an automation component. So think of this as before, during and after the call and who's involved. So at the beginning of the call, the automation customers are calling in, being able to get the information, solve their problems without ever talking to a human. If there is a need for a human to be involved because AI for whatever reason isn't able to solve that customer problem. Obviously with AIR Pro, you know, efficacy or containment we call it, you know, it's probably going to start at, you know, 70 to 80%, which is pretty darn good. So only that 20% of calls could, as it's continuing to learn and tune itself, go to an agent. But that handoff is seamless. But if a physical human agent answers the call, then we have something called ava, which is a personal assistant that provides that assistant assistance I was talking about to that agent to give them information on how to solve the problem. Right. So that same AI on that single RingCentral platform is providing the same level of information to the agent as though it would have used it itself to solve the problem. Now, during that conversation, everything's being transcribed and recorded, that voice data is coming through. So our third component of this solution that all works together, sort of think of it as in a circle, and we call it the power of, and it's always improving, is an, uh, agent we call ace, which is conversation intelligence. So it's taking all this voice, conversation intelligence and being able to now provide outcomes based on that. So improvements for customer service, operational insights. Um, it's also doing and acting as part of the tuning of both the AI for AIR Pro and AIR at the front door so that it gets smarter as well as that same agent, which is that personal assistant, which we call ava, to be able to have access to that same information to provide assistance to the humans that are actually answering a live customer inquiry. So think of it as a circle of forever improving and always adding to its knowledge by having these conversations, understanding which conversations are the best conversations, and how that continues to improve and learn and get better and better and better at its job. Containment goes up, humans less likely to have to answer calls. Still high touch point. Customer service agents will talk to humans and that process continues throughout.

Greg: And John, maybe a follow up from myself on this topic is what we're talking about here is some incredible technology from a capability perspective for the business, for the customer service agents, and ultimately for the customer. But the question I have is, you know, as, uh, technology continues to evolve, we talk about SaaS as a platform and obviously AI here, it's evolving so rapidly and with that, so is customer expectations. You know, what the customer expects to be a customer experience, even if they know they're interacting with some sort of AI technology. What are you seeing on that side in terms terms of customer expectations, what their interactions are looking like? Is it generally a positive sentiment? Is it growing? What are you seeing from that side of things? I think that actually follows on to the success of the technology. You know, what are the people saying?

John Finch: Effectively 100%, Greg. I mean, this is the challenge right so as we, as we go through this, um, evolution of innovation, um, we as technologists and companies that are building solutions to solve problems, are putting these in market incrementally. Right? So you think back, I mean, IVRs have been around since my grandfather was at Bell Labs, right, as an engineer, right. So, you know, call it a long time ago. Um, and IVRs were the technology that sort of front ended every conversation unless somebody physically answered the phone on a switchboard. Right. And that changed very quickly in the 60s. So as we got to these IVRs, they created an experience which in some cases were good, but were really meant to sort of triage. They didn't have to hire, you know, a single agent to handle X number of inquiries that were coming in, right? You couldn't staff and hire all these people that were answering all these inquiries. You had to triage them somehow. And the IVR was the place to do that. Um, but the IVR created a perception almost to your point, right? You get in that doom loop. It's jokes and commercials for years. Um, there was incremental ideations and innovations that happened with IVRs that got them m a little bit better with speech recognition and natural language speech recognition, but it's never quite there, right? It was always a little bit, not, not, not on top of it. Then we came out with the digital voice bots, right? Or the digital bots, I should say. And then in some cases there were voice bots, but they were very kind of, you know, robotic. Um, they provided sort of a promise to what you could have. But if you went to a website as an example, and you were like, oh, my gosh, they're open. I missed customer service, but they're open. I can have a conversation, get my answer. You get on there and you go and you invest this time. Your heart's in it. Then suddenly it's like, I can't answer that question. It's like the first one you ask, and it's like, we're closed. And our office hours are Monday through Friday, Central time in the U.S. um, you know, uh, from 8:00am to noon, you're like, got to work. Central time is, you know, an hour ahead, two hours ahead of me. And like, wow, I'm doomed forever with this customer service inquiry. So it was a little disappointing. Um, and now we've gotten to a point where we've made this promise of, of 24 7, right? And then the expectation gets set of 24 7. And we started to introduce things like Omnichannel, right? So meet your Customers what they are, provide them with the omnichannel experience. If it's voice, you know, digital across, you name your favorite digital, um, channel like Facebook chat or, you know, Apple Business chat, whatever it might be, right? WhatsApp, all of these solutions, you could start to converse with your organization that you're trying to do business with. But at that same token, it's like if no one's there to answer that inquiry, no one's there to answer that inquiry. And then you get into that same doom loop. Now with AI, it truly is there, right? So what I was explaining with the data and the information and by AI agents and human agents and humans and AI agents working together, having conversations together, listening to each other, learning from each other, um, providing data across multiple sources for the organization and giving this a human approach, a human like interactive approach where it listens, it's processing fast enough, where there's not annoying delays. That's the promise and that's what is here today. I think that that will just continue to improve. And so the sentiment of customers that are using this and even the skeptic that I am with perfection, this works. And organizations that I'm calling for personal business myself, I can tell if they've got more advanced technologies like this in place. And you know, M airlines and some of the bigger carriers have some technologies that they've spent a lot of money probably developing internally themselves and you know, most other organizations don't have access to. Now we've democratized this in a way where every organization can have this at an affordable price that's going to be based on usage, right? So it's consuming based on the transaction, it's driven for outcomes and it really provides something that is, you know, easy for organizations to um, predict what their use is going to be based on traffic that they've seen. But they can also cut costs in other areas now because they can take on this technology and not have to manage it or build it themselves. So that's kind of where I see that evolution coming. And it's going to take some time for everybody to get on the bandwagon. But I'll tell you what, once people kind of realize how much easier this is and getting your Problem solved, probably 100 of the time, I truly myself would rather text into something than I would have a phone conversation with an agent because the agent's typically going to fumble through a lot of things. There's a lot of, um, you know, white, uh, space in the conversation. They're trying to fill it with Annoying questions like, how's your day? You know, it's like things like, like you just want to go. And so this, I think, has that promise of getting that thing solved so you can move on. And you have an effective, um, you know, high level of interaction with a brand that you're hoping for.

Tamil: You're promising quality.

John Finch: Yeah, that's it. It's quality. It's quality and it's reliability. And it's like, I'm going to have the same experience across the board, and I have to worry about it. Something gets screwed up on my bill.

Tamil: Worry about someone having a bad day and then giving you bad customer service

John Finch: or you being cranky, interacting with it, because you know the AI is gonna be like, oh, you know, it's okay. I'm still gonna act nice to you no matter what.

Tamil: But I wanted to ask. A lot of companies still view contact centers as a cost center.

Greg: Really?

Tamil: And so in your view, what needs to change in order to become a true profit center?

John Finch: You know, it's always been this promise, right? It's a great question. I think it comes down to the fact of not adding to the stack of cost right now. It's really about making some choices. Right. And so it kind of comes back to my whole notion of working with humans. Um, to be honest, the balance is to be able to schedule the right humans for the right interactions along with the AI to solve as many problems as possible. I use those terms like efficacy or containment in being able to handle the inquiries. Right. So as you design, build, deploy, and then optimize, optimize with insights is the key to making that agent better. And so as it gets closer to being able to have that capability to truly step in for agents at a larger scale, the more efficient it's going to be, the more likely an organization is to not have to have, number one, a contact center seat for a human agent. So you could shed some of those. And then secondarily, um, you then don't have to employ as many people. And you can even think about shifting these individuals, which we've seen with a lot of our customers, into other, more advanced roles, right? We've seen a lot of our customers that are using AIR take someone who's a receptionist, the front desk. And now that person doesn't have to sit and answer that phone anymore because AIR is answering all these. These inquiries that are coming in. So she goes and she acts as a program manager on the projects within the company, which is more satisfying for her. So individuals inside the organization, I think now have, huh. What we've always sort of talked about is people can move on to other opportunities within their organization to work on the business at hand versus work on answering incoming calls.

Greg: I think it's a really good sort of rounding off point really about this whole conversation is that when we're talking about technology like AI and products RingCentral offer, we are talking about a shift in organizational operational expenditure, aren't uh, we just over time, just like you say, the shift of people into roles that really require people's input and creativity and thought and allowing technology to take that role within the organizations of today that can be taken over in terms of process and um, you know, handling let's say simpler tasks in certain aspects. Not necessarily, but simpler tasks in certain aspects and just allowing people to, to better represent the organizations they work with. Because I think the one thing that I want to get your thoughts on at the end of this is we talk about AI making impacts on the profit center and things. But I guess you know, do you believe that human interaction, so where when humans do talk to humans, it, there is something quite unique about that to a certain degree when it comes to customer experience and you know, the impact that we as people make on other humans. Do you think that's still true?

John Finch: I guess absolutely. I mean if you put yourself in as a consumer, right. Which we need to do on a regular basis, um, all of us that are, that are working in this space is you know, to really think holistically about that, that experience. Right. So if you, if you go. I'm just going to use hotel as an example. Right. Because I love to travel, I take a vacation, I want it to be really nice and I want it to be. It's back to that word I used earlier which is effortless. And I think that that becomes the key to this. Right. So when you're having sort of a more advanced um, interaction with a human that can provide that white glove ish type of experience, meaning those individuals are knowledgeable, you can have a great conversation with them. They're not there just churning out um, calls or inquiries that are coming in. They're actually there to service you and have those deeper conversations. That's the white glove high touch value add. I see in the human being involved in that conversation with the human. The human to human is definitely the white glove uber ultimate like experiential, effortless element experience that you want to have as a human consumer. Um, and I think that organizations, even if it's over the phone, can still offer that for, for customers. Because at the end of the day, customer service is a differentiator for every single business period. No matter what technology is being used. If your technology is not up to date, if you're not able to have the individuals that work in your organization or represent your organization do so in a positive, effortless, knowledgeable way, then that's not going to differentiate you on the good side. It's going to differentiate you so your competitors can eat your, your customers for lunch. And that's the biggest thing that I encourage for anybody. At the end of the day. It's, it's getting that white glove treatment and it's figuring out how to look at the holistic customer experience from purchase all the way through to deployment, all the way through to checkout. You know, whatever it is, whatever product or service or solution or hotel or doctor appointment or dentist appointment or surgery that you need to have or new curtains.

Tamil: I've loved this conversation. It's just been really insightful. I think we have time for a few quick fire questions. I'll start with one and then Greg can give another, uh, one. Okay. So you mentioned you like, quote unquote, bougie holidays. So do you prefer a ski trip holiday or a beach holiday?

John Finch: It depends on my mood, but I would always go for the beach holiday first. But I love to ski.

Tamil: I love a beach holiday, too.

Greg: Okay, so if you are on the beach, what's the drink that you order? Let's assume it's midday, so it's acceptable. Uh, what is that first drink that you would order on your holiday?

John Finch: Usually a cold, light beer. Like a Corona with a lime.

Tamil: With a Corona with a lime?

John Finch: Yeah, yeah. That's just, you know, now I want one happy hour somewhere.

Tamil: Sa.