We’ve all been sold the dream of AI transforming the customer experience, but what if the most common approach is actually making it worse?
Agility requires more than just implementing new technology; it demands a deep understanding of the human interactions that technology is meant to support. It’s about adapting your tools and processes to enhance human judgment, not just automate it.
Today, we’re going to talk about moving beyond the hype of AI in customer experience. We’ll explore how to ground an AI strategy not in the technology itself, but in the real, human moments that define a brand, and discuss why empowering your frontline team might be the most critical, and overlooked, component of a successful CX transformation.
To help me discuss this topic, I’d like to welcome, Michelle Cooper, CMO at NiCE.
About Michelle Cooper
Michelle Cooper is a seasoned marketing executive with extensive experience in leading marketing strategies and initiatives across various industries. Currently serving as Chief Marketing Officer at NiCE since June 2025, Michelle previously held multiple senior roles at SAP, including Executive Vice President of Global Field Marketing and Brand Experiences, where a focus on cloud growth was instrumental in achieving a significant increase in revenue. Throughout a distinguished career, Michelle has directed marketing efforts that encompass brand experiences, demand generation, and customer advocacy, with notable achievements in the Americas and high-growth sectors. Previous roles at Gelco Expense Management, Rightworks Corporation, Oracle, and Texas Instruments have further solidified expertise in building strong marketing functions and driving market engagement. Michelle holds a B.S. in Marketing and Management Information Systems from Longwood University and is pursuing further education at Kellogg Executive Education.
Michelle Cooper on LinkedIn: https://www.linkedin.com/in/michelleleecooper/
Resources
NiCE: https://www.nice.com
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Transcript
Greg Kihlström: We’ve all been sold the dream of AI transforming the customer experience, but what if the most common approach is actually making it worse? Agility requires more than just implementing new technology, it requires a deep understanding of the human interactions that technology is meant to support. It’s about adapting your tools and processes to enhance human judgment, not just automate it.
Today, we’re going to talk about moving beyond the hype of AI in customer experience. We’re going to explore how to ground an AI strategy in not just the technology, but in the real human moments that define a brand. And discuss why empowering your frontline team might be the most critical and overlooked component of a successful transformation.
Greg Kihlström: To help me discuss this topic, I’d like to welcome Michelle Cooper, CMO at Nice. Michelle, welcome to the show.
Michelle Cooper: Greg, thank you so much for having me.
Greg Kihlström: Yeah, looking forward to talking about this with you. Before we dive in though, why don’t you give a little background on yourself and your role at Nice?
Michelle Cooper: Absolutely. So I’m the, as you mentioned, I’m the CMO of Nice. I’ve been in my position about eight months. Um, so it’s been a whirlwind of a, of a, a cycle, um, but it is so great to be on kind of the front lines of really helping our customers transform their customer, uh, customer experiences.
Greg Kihlström: Love it. Well, yeah, and we’re going to talk about, uh, quite quite a few things here, but want to start with the really the strategic look at things and kind of reframing this AI and CX strategy. And so you’ve stated that many AI initiatives and CX fall short because they’re designed around technology instead of those customer moments that I mentioned in the intro. Can you unpack that a little bit? You know, what what does a customer moment first AI strategy actually look like in practice for an enterprise?
Michelle Cooper: Yeah, absolutely. And to your, to your comment, I think a lot of companies are kind of approaching this AI era from a technology, right, from a tool perspective. And and yes, the tool and the technology that you you pick and select is is critical in your journey, but where you really need to start is in thinking through like what are the customer, um, moments that matter. What are the business processes that you’re trying to, um, evolve? What are the outcomes that you’re ultimately trying to get to? And a lot of times we see, you know, organizations start with the technology first versus the the outcomes. And I really think that’s the, that’s the the the opportunity and also the challenges that as companies really build their AI strategy and journey, that they really need to be thinking through and and taking into consideration.
Greg Kihlström: Yeah. Well, and and a lot of leaders in, you know, figuring out their strategy, a lot of them are seeing this as a way to automate a lot of things, you know, increase efficiency and thereby potentially reducing head count on the, on the front line. You’ve argued for just the opposite, really, using using AI to empower them. How do you make the business case for investing in AI to support that human judgment rather than simply replacing it?
Michelle Cooper: Absolutely. And and I think that yes, the technology absolutely affords an efficiency opportunity, but if you’re only thinking about it that way, um, you’re you’re missing a huge, you know, huge opportunity. For us, we we think about the AI as a as a way to be able to help our customers understand when those moments of at the moment of interaction and engagement, how do you make sure that whether that’s an AI agent or a human agent that you’re giving them the context of the intent, a historical perspective, you’re guiding them with, um, you know, uh, information about that customer. You’re recommending the next the next best action. So it’s not about just automation for automation’s sake, but it is really focused on how and when you’re able to deliver a better customer outcome. And a lot of times, yes, there’s cost savings, yes, there’s efficiency, but it’s really more about what are those interactions and those special moments that you can really create for your customers, you know, in that that that that that moment, that instance that it really at the end of the day makes a difference between them continuing to value and select your brand or to possibly make another decision.
Greg Kihlström: Yeah, and and some of that at least requires really enabling that frontline to be able to, you know, serve serve customers in the moment, right? And so when we talk about using AI to help those employees to to show up better, what what does that look like, you know, on a typical day for a customer service agent? You know, what what specific information or capabilities is AI able to provide them in real time that they may not have had before?
Michelle Cooper: Absolutely. And being a customer service agent is uh, I mean that is a heroic, heroic job and and effort, right? This it’s not easy. So the the technology really helps them become, to your point, much, much more effective and empowered. Um, so a typical day might look like instead of toggling in between multiple systems to to be able to really understand why the customer is there, to being able to do that in one platform, um, to being able to give them, um, an understanding of who they are, what they care about, what solutions they have, um, maybe some historical intent, um, in regards to their their previous interactions, and then being able to power them with real-time coaching, um, recommendations, um, information on sentiment to really help personalize that experience and deliver, you know, the best, you know, possible customer outcome and ultimately get to resolution the fastest. The other thing that is really important these days is that now with AI, not only is it AI in context of co-pilots and real-time coaching and agent assistance, but it’s also being able to automate tasks with AI agents or agentic agents to be in the in the in the background to be able to ultimately get to that that resolution. And I think we’re kind of seeing like the whole journey change. You might start with an AI agent, right? And and start your customer journey and your interaction there. You may then go from an AI agent to a human agent, and that orchestration layer and that passive information with that intent is so critical in making sure that from the the moment that they interact to the the moment of resolution that that really is seamless and is as personalized as absolutely as possible.
Greg Kihlström: Yeah, because I mean it it does seem like that that is one of the key points that can really make or break that. You know, I always I always use the example of, you know, when you call up your bank and you have to keep giving them your account information over and over again, no matter who you get transferred to. It’s like, yeah, yeah, so it’s-
Michelle Cooper: And that’s really the new battleground, right? Is is really thinking about how you’re going to orchestrate your AI in a new operating model as as you go forward.
Greg Kihlström: What do you see as maybe the either single biggest or you know, one of the biggest mistakes that you see organizations make when they try to implement AI tools for for frontline teams? You know, is it technology? Is it training? Leadership? You know, where where where do the the biggest failings seem to be?
Michelle Cooper: Often times we see the the biggest challenges is just trying to take AI and automate their existing business processes, right? And and almost treating it as a technology project versus a transformation. And I think one of the things that is so powerful about AI today is you can completely reimagine the way that work gets done. What’s handled by AI agents, um, versus human, how to make those, how to balance, you know, the the handoff, um, and the orchestration between those two worlds. So I think that for me is is the thing that we see most is you have to go into this with a complete new orientation about rethinking the work that you do and how will it be done going forward in this new environment.
Greg Kihlström: Yeah. And and of course, you know, when it comes to measurement, I’m sure there’s a lot of traditional metrics that don’t go away because you adopt AI, but you know, let let’s talk about, you know, when when the goal is to empower employees and improve quality of human interaction, are there either new KPIs or different KPIs that should also, you know, either be added or or prioritized when we’re looking at it from this lens?
Michelle Cooper: Absolutely. And you already see a a lot of the industry starting to pivot. There’s to to rethink, you know, some of the traditional metrics like average handle times, right? Average call times, right? And those were really predicated on efficiency and but now it’s really more focused around resolution quality, um, customer effort, um, you know, first call to resolution, how quickly can that happen and and being able to really measure those things and to make the correlation between how those ultimately impact, you know, brand trust, reduce customer churn, increase loyalty or NPS. And and I think when you just look at the the research in regards to how when you can move the needle on an NPS score, you know, just how much that really correlates to ultimately to, you know, customer loyalty and and and you know, revenue, right? Whether that’s protection of revenue or expansion of revenue, it it really allows you to tie and link everything that you do from a customer experience perspective in a contact in a call center back to really the the growth, you know, um, priorities, you know, of of that specific business.
Greg Kihlström: Yeah. And and of course, you know, one of the things that that you touched on already, but um from a from a measurement standpoint is we are ideally we are improving the employee, you know, the employee experience. So that that contact center customer service agent, they are spending less time rooting around to things. They’re ideally dealing with less frustrated customers because we’re able to know more and know more quickly and and all of those kinds of things. How do you connect that, you know, something like an improved employee experience to the customer, you know, so something like customer lifetime value, you know, how how how do you recommend doing that?
Michelle Cooper: Yeah, absolutely. So it’s interesting that one of our customers, Lufthansa, actually right now, they’re already automating 70% of their tier one and tier two interactions with agentic AI agents, right? So it allows them to be able to handle, you know, higher call volumes, to be able to to action and and ultimately resolve those, you know, interactions in a in a much, much more, you know, efficient, um, efficient way. But what it allows you to be able to do is to shift some of the things and and some of the work that your call center agents used to do that were very, very time consuming to be able to shift them to higher value, you know, opportunities in and interactions. And I think that allows them to be able to focus their time and energy on those again, I come back to this word moments, those moments that absolutely matter most to their consumer. So I think there’s more satisfaction in in in being able to to feel like you control the work that you’re doing and and seeing that direct correlation between the customer outcomes and customer satisfaction and also equipping them and enabling them with, you know, co-pilots and knowledge and recommendation engines. Um, simple things like a lot of their time would have historically been, um, spent on just capturing the notes and the resolution and the next steps. All of that is automated today with AI and allows them to really free up their time to to focus on what matters most and and that’s their customers.
Greg Kihlström: Yeah, yeah. And then so looking forward, you know, it it’s definitely seems like there is going to be increased personalization. I mean, you know, even even just empowering the frontline employees with more information and more more fullsome information is is helpful. Is there a line, you know, in in the bank example that I that I gave, it’s like I don’t want to say my account information out loud five times for many, you know, it’s it’s sensitive information. You know, that that carrying that kind of stuff forward is helpful and and makes it feel more secure. To in some cases, do you know, customers may feel like that level of personalization may also be intrusive or or something like that. You know, how do you how do you balance that helping the customer by bringing that stuff forward and by personalizing the experience while still not making them feel comfortable about the level of personalization?
Michelle Cooper: Absolutely. I think the the to your point, the personalization is so powerful and and I just actually read recently a stat that says, you know, it really is kind of the competitive edge. I mean, it’s like two X, right? When you can absolutely find, you know, from a uh, customer loyalty perspective, when you can find that right balance. Um, I think what we advise our customers on is is really being very transparent about the data, right? That you have. You want to be proactive in the way that you use it, but you you don’t want to, you know, you know, be creepy about how you use it to target. So you want to be really, really thoughtful about, you know, being very transparent around how and where you’re using it and to not overuse it. But I do think at the end of the day, the opportunity is that we as consumers, all of us want to feel like we’re understood. We we want to be able to get to, you know, whatever we’re trying to solve for faster and that personalization absolutely, the benefit of it when it’s done right, allows us to really feel connected and and have that trust with those brands that that we select and ultimately choose to to do business with. So it I think is an is a is a industry, you’ll see this, you know, continue to evolve, but I think we all have an opportunity to be really, really responsible and it starts with that transparency on how and what and and where you’re using it.
Greg Kihlström: Yeah, yeah, love it. Well, uh Michelle, thanks so much for joining today. I got a couple of last questions as we as we wrap up here. The first one, if we were having this interview one year from today, what is one thing that we would definitely be talking about?
Michelle Cooper: Um, I believe we will not be talking about AI as a tool or as a feature. I think that will be table stakes for every organization and company. But I really do believe the the the conversation will shift to AI as an operating model. Now, how do you begin to think about managing a hybrid workforce where you have AI agents and human agents seamlessly working together? And then how do you orchestrate that work and and the the handoffs as you go through the the customer journey. So I think AI becomes much more, the discussion will pivot and become much more around what’s the operating layer, an operating model that company need companies need to be able to really manage in this new environment.
Greg Kihlström: Yeah, yeah, love that. Great. Well, uh last question for you, uh what do you do to stay agile in your role and how do you find a way to do it consistently?
Michelle Cooper: That’s a million dollar question. Um, but for for me, it’s it’s carving out time to learn. Uh, you know, I think that the market’s changing so fast, technology’s changing so fast as as you know in marketing just in customer experience in general, but I think you absolutely as a leader have to carve out time and and make sure you’re making that a priority. Um, the other thing for me is I try and corporate AI into my daily life. I think to to be able to embody it, you’ve got to be a practitioner of it. So making that a priority for myself and and our team, um, as we move forward. I have this mantra about being an AI first marketing organization. Um, and it it starts starts with me and and really embracing that. And then I think the last thing is that, you know, as a from a mindset perspective, as leaders, we all just need to be able to to to recognize that we’re going need to learn and pivot and fail very quickly. In this environment where things are changing so quickly, we just have to be able to be able to react and pivot and and some of that comes with with learning, you know, as as we move through this new environment.
