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The Agile Brand with Greg Kihlström®: Expert Mode Marketing Technology, AI, & CX
#777: Cisco's Chang Chang on how AI is fundamentally reshaping the contact center
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- [00:01]
Greg Kilstrom
The agile brand.
- [00:10]
Podcast Announcer
Welcome to Season seven of the Agile Brand where we discuss the trends and topics marketing leaders need to know. Stay curious, stay agile and join the top enterprise brands and martech platforms as we explore marketing, technology, AI, E commerce and whatever's next for the Omnichannel customer experience. Together we'll discover what it takes to create an agile brand built for today and tomorrow and built for customers, employees and continued business growth. I'm your host Greg Kilstrom, advising Fortune 1000 brands on martech, AI and marketing operations. The Agile Brand Podcast is brought to you by Tech Systems, an industry leader in full stack technology services, talent services and real world application. For more information, go to teksystems.com to make sure you always get the latest episodes, please hit subscribe on the app you listen to podcasts on and leave us a rating so others can find us as well. And now onto the show. Is your contact center ready to become a profit center? Agility requires not just adopting new technologies like AI, but also fundamentally rethinking how we structure our teams, measure success and interact with customers. It demands a willingness to experiment, learn and adapt quickly in a constantly evolving landscape. Today we're going to talk about how artificial intelligence is revolutionizing the contact center, transforming it from a cost center into a driver of customer loyalty and revenue growth. To help me discuss this topic, I'd like to welcome Chang Chiang, Senior Director, Product Cloud CX Solutions at Cisco's WebEx Customer Experience Solutions. Chang, welcome to the show.
- [01:48]
Chang Chiang
Hi Greg, thanks for having me.
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Greg Kilstrom
Yeah, looking forward to talking about this with you. Before we dive in though, why don't.
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Podcast Announcer
You give a little background on yourself.
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Greg Kilstrom
And your role at Cisco?
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Chang Chiang
Sure thing. I've been with Cisco for a little over three years, currently leading our Cloud Customer experience solution products. Prior to this, I also led the webex app and messaging product. Prior to Cisco, I worked in product at Intuit and Mighty Audio, which was an early stage startup company.
- [02:13]
Greg Kilstrom
Great, great. So yeah, let's dive in here and going to talk about a few things today, but I want to start with just the current state of AI in context. So centers we hear a lot about AI's potential, but what are some tangible examples of how AI is already improving efficiency in ROI in contact centers?
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Chang Chiang
Absolutely. Lots of improvement already. We're seeing AI already handling routine inquiries, reducing call volume for human agents, and shortening wait times for customers. Additionally, AI assistants are actually helping human agents in their role by providing summaries to reduce after call work or context during any agent to agent Transfers as well as suggest responses or agent answers to provide the right information from knowledge basis to the agent to provide to the actual end customer as well. A good example, one of our large customers right now that is using our WebEx AI agent is already seeing 66% reduction in incoming calls and reducing human intervention at the end of the day, which is dramatically lowering operational cost at another customer. We're already seeing the work processing time going from a 24 to 48 hour turnaround down to just a few hours. They're quoting a 90% reduction in work time in some use cases.
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Greg Kilstrom
Wow. Wow. Yeah, that's. And you mentioned the cost reductions. I think that's definitely something that's talked about quite a bit, is cost savings. But some of the other things that you mentioned too are there's a customer experience angle here as well. So can you talk a little bit about that impact on customer experience and are there any surprising ways that AI is being used to enhance satisfaction and build customer loyalty?
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Chang Chiang
Absolutely. I think AI is really changing customer experience in terms of what can be experienced and delivered. I think everyone wants the always available type of experience. And by that what I mean is the instant, no, wait, 24, 7 support anytime you want it on any channel, any time zone. And so AI is starting to really enable that experience for end customers. And what really is even more so than that is the personalization aspect as well, to the point where AI will start to know me better than I know me. We've seen this already, right? Think of social apps, right? You can think about your TikToks or your, or Instagrams where they are using AI to serve content and you're kind of hooked, right? And so they already know you so well that they know what will keep you in. I think we'll start to see that also with AI across customer experiences. The same way brands can pull you pull end customers in in a way that they didn't realize, providing recommendations they may not realize they wanted at the first place. But that totally, you know, hits the note with end customers being proactive, right. Getting that text message or an alert before you even knew that you had a problem. Right. And so I think a lot of that personalization is also coming that will change the customer experience as well. To your second question around what's surprising, I think some of the things that I've seen that surprise me is the actual real time adjustment to sentiment and emotion. And so even with our AI agent, for example, if you ask it to slow down and break up a multi question A difficult question. It will slow down and actually go through discrete steps to go walk you through step by step something. And so I think that's really unique. I've also seen great examples in the broader industry around real time translation. Right. For multilingual support, which is amazing. And you know, for me, you know, not growing up in a full English speaking household, it just, it's just unlocked so much in terms of the possibility. And so I've been constantly surprised by how much AI can solve and how fast it's changing and how adaptable it can be also in real time.
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Greg Kilstrom
Yeah, yeah. And so, you know, lots of impacts from that end customer perspective. So lots of impacts on humans that way. But also let's talk about the evolving role of the humans on the other side of it, you know, the agents with AI taking over a lot of those routine tasks that, you know, and let's face it, that agents haven't necessarily loved doing. You know, it's not, it's not the, the most enjoyable part of the job either. But you know, how do you see the role of the, the human agent evolving and you know, what, what new skills are going to be essential for agents in this future where they're working alongside AI?
- [06:49]
Chang Chiang
Yes, one thing that we're definitely seeing and hearing is that a lot of people aren't talking about replacing human agents. Really. Human agents role is really being elevated and transformed. Like you kind of alluded to, moving from a transactional role to more of a trusted advisor handling more complex and emotionally nuanced interaction even with our customers. Today we aren't talking about how do we reduce human agent and how do we replace human agents. We're actually seeing, and we're not even seeing them in the requirements now or the outcomes that our customers are looking for. They're actually trying to see and do more with the current resources they have. Right. Actually going from providing life support from 9 to 5 all the way to providing life support 24, 7 as well. And so we're just trying to, we're really seeing this evolution and hearing about human agents becoming more of relationship managers solving complex problems. And that leads to your second question around what new skills? I think first and foremost, I think EQ and empathy will become even more important as these more transactional and easier problems get solved by AI. The tougher ones, at least for now, in the short term, the tougher ones will go to the human agents. And so they're going to be handling much more complex problems and having that empathy and being able to problem Solve with the end customers is going to be super paramount as well. The other thing that I also see is just more AI fluency. I do think that human agents will probably get even more involved with the AI and the AI agents that are out there in terms of training them, helping curate information for them as well. And so it'll definitely be a transformation and an elevation of their role.
- [08:39]
Greg Kilstrom
Yeah, yeah, well, and some of the numbers that you mentioned at the beginning, the cost reductions, the time to solution those massive in those cases reductions, and I would imagine some increases in customer satisfaction as well. Obviously that takes successful integration of all this stuff. What are some best practices that you've seen that have led to some of those great results when integrating AI into existing contact center teams and workflows?
- [09:13]
Chang Chiang
Yes, I would maybe break it up into kind of two parts here. One is just the overall approach. I think it's super critical or a best practice is super critical to start with actual experience you want to deliver, making sure the handoffs are seamless and, and actually following it from end to end. At the end of the day it's, it's a, a brand's end customer that's going to be ultimately affected by how good these AI solutions are going to be deployed. And so really understand the end flow is really critical. The other good best practice on the approach is think of replacing, not replicating. I think too oftentimes companies will try to take an existing process and just try to replicate it using AI and but I think AI actually gives us the opportunity to think of it differently and provide the same outcome in a different way. And so that is one other best practice that we've seen work in terms of some tangible steps. I would say four tangible steps in terms of what we're seeing work well with our customers. One is establishing some sort of cross functional AI committee. And this would include stakeholders, even human agents themselves. Right. And supervisors and everyone along that along the end to end journey to get involved and to weigh in on the approach and what use case to solve and actually testing out the experience itself. That's the first thing. The second tangible step is doing internal testing. Right. Prove the tech in a very controlled setting, gain all the stakeholder, buy in with that cross functional committee. And then third is using the learnings, very agile nature. Take those learnings, build upon it, iterate design, implement and then do a phase rollout. Start with the pilot, expand the more use cases and then get in more widespread full scale. And so this is kind of the tangible steps that I absolutely see that are what we've seen with customers work. Well, that said, a few pitfalls just to call out.
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Greg Kilstrom
Yeah, yeah, definitely.
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Chang Chiang
One thing is don't underestimate the change management process. Right. I mean we all know change is hard and so underestimating this will kind of, you know, always just anticipate and be aware that it is a longer process in terms of change. Second is not getting all the buy in. Right. And this is why that cross functional committee is super critical at the beginning is you want to make sure you get the buy in from all the key stakeholders if you really want this to be successful. Third is be clear on the outcome and objectives at the end of the day. And the fourth thing, and maybe the most important thing is don't forget about the data. Yeah, AI is only as good as the data that's feeding it and so you really need to have good data going in as well.
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Greg Kilstrom
Yeah, yeah, definitely. Yeah. The data piece, if you don't address that, you will be addressing it at some point early on. So yeah, definitely. Glad you brought that one up.
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Greg Kilstrom
I also want to come back to something that you briefly mentioned before but I want to, I want to dive into it a little bit more and you know this, this idea of always on customer engagement. You know I think we as we're all because we're all consumers when we're not working right. So it's like you know, we know our expectations as a customer but you know, from a, from a brand's perspective and from a, you know, a customer Service and infrastructure standpoint, you know, what does that look like in practice and how does AI enable it?
- [13:45]
Chang Chiang
Yeah, always on engagement means customers can interact with brands anytime, anywhere, any channel, and it's just seamless. The best way that I try to describe it is kind of like interacting with a friend or family member, right? You interact them through email, text, phone call at any time. You can switch mediums and the conversation picks back up where you last off. They have the full history and context of who you are and to the point and you know, when it's, you know, close friends and family, they, they know you and can anticipate what things you will like, what things you won't like. And so I see the same in terms of how an AI will enable this for customer experiences. Right. A brand will start to know their end customers in the same way of, you know, you reach out to the brand website, you get distracted, you come back, you text them later, then you get distracted. But then it may text you back and say, hey, did you, did you still want to follow up? Then you'll call and you may reach a human agent who actually knows that you had already visited a website earlier, you already texted. They have all that context. And so that's what I think an always on engagement is. It really is like working with someone that you know and that knows you very well. One of the things you know in terms of, you know, how AI really enables this is the real time context around the different touch points is super critical around channels. At WebEx, we have our AI agent and AI assistant that are built on top of our Journey data service, which basically captures all the rich data of interactions and active data points that happen between a brand and an end customer. And so this can help feed the AI, right, the AI agent or the AI system with all the past context so that when a end customer is interacting with the brand, they have that, that rich experience of knowing who that end customer is as well.
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Greg Kilstrom
Yeah, yeah. Talking about personalization, certainly, you know, that's a key component. I mean, I like the, I like the, that idea that you mentioned. As far as, you know, you should kind of think of it as a, that experience as, you know, a conversation that you may pick up from channel to channel or whatever, but your family member, your friend, whatever remembers the, the last conversation, at least in most cases they remember what you said. Maybe, maybe not always as much as you wish they would, but what role does personalization play in this? Always on engagement? And how can AI be used to deliver those experiences at scale Because I think that's the tough, or at least one of the tough pieces. And let's throw in the consumer privacy part as well. You know, how, how does all that happen?
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Chang Chiang
Yeah. Personalization to me is that magic moment in terms of always on engagement. Always on is great if you can always reach out 247 but the second that the brand knows who you are, why you reached out, or even, even, even, even better, before you even reach out, proactively resolves your issues for you that, that to me is, is a true personalized experience. Before I needed this, you already sent it to me. Right. Or before I had an issue here, you've already done it for me and taking care of it for me. And so I think this is where that always on engagement isn't just about a one way direction of an end customer reaching out to a brand. It goes both ways as well. And making that a two way relationship.
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Greg Kilstrom
Yeah, yeah. And so, you know, we've talked plenty about the human customer service agents. I want to talk about agentic AI now a little bit more. And you know, certainly that's everybody's talking about. I feel like it's, it's like the, the chat GPT of 2025, you know, like three years ago or whatever was, it was all, you know, that stuff and now everybody's talking about agentic. Certainly not only is it being talked about, but it's, you know, it's gaining traction. I mean there are, there, there are use cases and there are implementations. What are your thoughts on, you know, it's, it's a more autonomous approach. Not always completely autonomous, but it's more autonomous approach. And what are some potential, maybe benefits and risks?
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Chang Chiang
Yeah, Agentic AI really is about autonomous. Right. It's the ability of AI to process information, reason, plan and act and start to handle even more complex tasks, make decisions and even take actions. And I'm excited by it because it will free up humans to do more higher value work. Right. And, and ideally take care of some of the things that you don't want to spend time doing. I think even more exciting for me is actually this notion of the multi agent ecosystem where you have all sorts of AI agents interacting with one another. I mean to the point where you can have an AI agent on one brand interacting with an AI agent for another brand and taking care of an issue for you. Right. And so I think there's so many use cases where we all as end consumers spend time on things that we just don't want to spend time on. And this is where the autonomous nature of AI tech, AI can take care of those things. Right. And what's even more exciting is how the broader industry has enabled that. If you see what we're doing now with a 2A and MCP, just the unlocking and the ability for all these AI agents to actually communicate with one another and complete tasks is I think, a step in what I would hopefully describe as a benefit of getting more conflicts done more automatically so that we all can enjoy the things that we want to do. Right. And so I think that's the exciting part and the benefit part, obviously that comes with some risks. I think the biggest one that comes top of mind is the loss of control. Right. And mistakes made by AI agents can happen at large scale. And so this is where all of the correct guardrail security is absolute paramount. Being able to monitor and test and even here at Cisco like this is like first and foremost making sure things are secure. We take our AI and being very responsible with AI and have added multi layered guardrails just to ensure that there's always control over these agentic ecosystems and that they're secured by nature and that they're in a way that can be monitored and tested ongoing as well. And so, you know, those are some of the risks. But I think the benefits here are just so. There's so many different use cases where we can use agentic AI to solve things. I'm very excited about it.
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Greg Kilstrom
Yeah, yeah. And I mean it's, it's, I think it's moved very quickly. I mean, things, you know, things are always moving quickly, of course, but I think it's moved very quickly, very, you know, very recently. You know, you mentioned the MCP stuff. Like all of that is just, I think is rapidly changing how we're approaching things. But let's maybe look out, you know, a couple of years, two, three years. I know that may feel like forever looking out at this at the rate that things change. But you know, what's your vision for the future of customer service and you know, what are the biggest opportunities and maybe the biggest challenges that lie ahead?
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Chang Chiang
I will say I get this question a lot and it's really interesting because if I think back three years ago would definitely not would have imagined where we are today. Right. Or at least, you know, pre chat, GPT and generative AI days. And so it's going to be really interesting to see how much will evolve and change over the next two, three years in terms of an experience. I, I really do think that brands will be really empowered to engage with end customers and very hyper personalized journeys. Very proactive at anticipating needs to the point where as an end consumer every interaction you have with brands just seems almost what you would call perfectly timed. Where it was like right just at the right time. It's very intuitive to who you are and what your needs are and what your preferences are and that every time you interact with the brand it's even better than the last interaction as well. And so I think the technology and advancements that are going to happen are going to be limitless and I do think we'll get to a point where hopefully the days of bad customer experiences will no longer be a thing.
- [22:18]
Greg Kilstrom
I would love that. Well Chang, thanks so much for joining today and sharing your insights. One last question before we wrap up here. What do you do to stay agile in your role and how do you find a way to do it consistently?
- [22:31]
Chang Chiang
Thank you as well Greg for having me. It was a pleasure. Of course. In terms of staying agile in my role, I will give a slight different answer in terms of how I leverage Agile concepts in my own to do list and how I manage my own action items. I actually have a Kanban board set up with all my action items and notes and I just move them between the columns and reprioritize the cars and so that's how I've been leveraging the Agile concept just in terms of how I manage my daily to do list.
- [23:01]
Podcast Announcer
That's great.
- [23:01]
Greg Kilstrom
Well, thanks again. Again, I'd like to thank Chang, Senior Director Product Cloud CCX Solutions at Cisco's WebEx Customer Experience Solutions for joining the show. You can learn more about Chang and.
- [23:12]
Podcast Announcer
Cisco by following the links in the show notes. Thanks again for listening to the Agile Brand brought to you by Tech Systems. If you enjoyed the show, please take a minute to subscribe and leave us a rating so that others can find the show as well. You can access more episodes of the show@theagilebrand.com that's theagile brand.com and contact me. If you're interested in consulting or advisory services or are looking for a speaker for your next event, go to www.gregkillstrom.com that's G R E G K I H L S t r o m.com the Agile brand is produced by Missing Link, a Latina owned, strategy driven, creatively fueled production co op. From ideation to creation, they craft human connections through intelligent, engaging and informative content. Until next time, stay curious and stay agile.
- [24:10]
Greg Kilstrom
The agile brand.
- [24:15]
Tech Systems Advertiser
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