AI for CS Leaders Spotlight: Suzanne Hitcho on Building an AI Operating Model for the Whole Business

Suzanne Hitcho has spent her career at the intersection of customer success, go-to-market, and value realization from Pfizer, Coca-Cola, and Disney to six years in B2B SaaS. So when she joined the AI for CS Leaders Executive Bootcamp, she wasn't starting from zero. She'd already stood up an AI center of excellence and a shared prompt library at her last company. 

In this spotlight, she shares what still shifted for her, and why she believes AI in CS only pays off when it's treated as a cross-functional operating model, not a set of siloed experiments.

This episode is for forward-thinking CS and go-to-market leaders who know AI is now part of their mandate, and who want a structured, strategic way to apply it without the stress of figuring it out alone.

Ready to join the next cohort of the AI for CS Leaders Program? The next one opens again in August. Get on the VIP waitlist here for an exclusive discount and first access.

Ways I Can Help You Level Up Customer Success:

1. Value Realization Framework Online Course:  Install a repeatable system your team can run: deliver value, prove outcomes, and drive retention and expansion. Self-paced with ready-to-use templates. Learn more.
2. Newsletter: Practical, revenue-driven CS strategies in your inbox. No fluff. Subscribe here.
3. 1:1 Coaching: Hands-on guidance to roll out value realization in your org. Book a free consult call.

For more information, visit my website: Explore more resources and insights. CS RevSpeak

Let's Connect on Linkedin:  Get weekly insights, templates and real talk on CS leadership. Follow Angeline on LinkedIn.

Until next time, keep driving success and speaking the language of revenue!

Transcript

0:40

Hey everybody, Angeline here. This episode is part of our AI for CS Leaders Spotlight, where we share real stories from the participants of my AI for CS Leaders Executive Bootcamp. Today's guest is Suzanne Hitcho, leader in customer success and go-to-market strategy. I'm excited for this conversation because Suzanne joined a program with a clear intention to sharpen her thinking, deepen her confidence, and build a practical point of view on how AI should show up in customer success. So today we're going to talk about why she joined, what stood out the most, and the shifts she's taking with her, and her advice for anyone considering to join the future cohort. Suzanne, welcome and thank you for taking the time to join us today. Thanks, Angeline. Happy to be here. All right. To kick things off, can you give us a quick intro? Tell us a little bit about yourself and your background. Sure. Well, thanks again, like I said, for having me. Excited to be here. I have been working for the past several years, about six years, for a SaaS organization in customer success and go-to-market strategy and value realization roles. So that's been a great experience. Prior to that, I worked in corporate. So I was at a large corporation such as Pfizer, Coca-Cola, and Disney. So I've come in with a very strong customer experience point of view and very focused on value realization throughout my entire journey, whether working in customer success or more on the sales and go-to market side and a value engineering role. So AI has been a big shift. We've been experiencing over the past few years, and I've become increasingly interested in that as well, and how we can better apply AI across the entire go-to-market and customer value journey. Well, thank you so much for walking us through what you've been doing in the past. Now, I wanted to highlight, I know that you chose to invest in this program for your own personal and professional growth as well. What made you decide to join the program and what made you decide it was worth the investment? Yeah. Like I said, AI is really pervasive. It's affecting every area of the business. It's a democratized technology, meaning everyone has access to it. So there isn't a lot of structure. It's a little bit of the wild west out there right now in terms of the application, everyone's accessing the LLMs, leveraging AI in the existing tech tools at their disposal. And I really felt like I needed a little bit more structure and guidance and even knowledge sharing with peers to figure out how are other people thinking about this, how are they applying it, and where can we bring some order to the chaos. So that was really the impetus behind why I was interested in diving in and really getting a little bit more structure around how to think about AI and apply AI in the right way. That's really great to know because I know that during the program as well, I love how you're sharing your own personal experience and implementing AI in your previous organization. So talk us through this. Before the program, how were you thinking about AI and customer success? And to be honest, I feel like for any leader who has been doing this prior to this year, you're already ahead of the pack. Because like you said, AI is everywhere, but it's still pretty much nascent and really very new. And so anybody who has started doing it is leading, like I said, leading the pack already. So what was going on? How was your, how were you thinking about implementing AI and customer success in your role? Yeah, well, first off, I was working more in a go-to-market across the customer journey capacity in my last role. So I had been in customer success for a while, but in my last few years, I had moved beyond that into more of the pre-sales area and value engineering, focusing on ROI and business cases and value consults with buyers for our product offerings. So I was really thinking about how AI was impacting every area of the business. With a systems engineering background, I was really thinking about everyone going out separately and trying to improve their processes with AI and how could we really get more visibility to what was going on. So one of the things I focused on was the opportunity to put together an AI working group or center of excellence, which was essentially just a monthly routine where we could bring the team together to really talk about what's happening in different areas of the business. What is our implementation team doing versus our product team, engineering? How is everyone thinking about AI and how are they already leveraging AI on a daily basis? Because they're in certain tools or, again, they have access to the LLMs through enterprise, chat, GPT, and how are they thinking about doing that? And then where can we just start to bring that energy together? Where can we bring and build that transparency together? So putting together an AI prompt library that everyone can reference and see and share what are the custom GPTs we can scale? Or what are use cases? Where are we having some problems? Where we really need a solution? Where we need to drive efficiency, growth, or innovation? So those are some of the things that we were initially focusing on over the last year. I love that. I love that you didn't join the program because you're just starting to kickstart something. You've done AI. You've implemented AI in your role in your previous organization before. So you bring a different lens, actually, to the group, having done this before versus some of the people who are like, okay, I'm just trying to figure this one out at this point in time. So I am curious, actually, what shifted after going through the program? Is there a specific aha moment for you across the modules and the sessions that we've had? Well, there were so many great frameworks. It's hard to narrow it down just to one. I loved, first off, in the beginning module, just looking at a maturity model. I think it's really important to be able to baseline where you're currently operating. And the maturity model, it's a standard four-phase maturity model, really gave that lens into, okay, let's assess where you are today. And then the structured guidance through the additional modules and layers of thinking about where you should start applying AI, what's the baseline, the ground level of applying the LLMs, and then how do you think about agents going forward? We always talk about agentic AI and how to apply that. So I think the biggest shift for me was it wasn't just a model for customer success, but it was really a model to think about applying AI to the entire business, really, across all functions and areas. The maturity model, to me, wasn't something that, you know, again, just was about the customer success. It was really about how do we all come together. Many of these workflows are cross-functional, so it's really important that we establish a common vernacular, a common understanding of where we all are operating together to really drive that level of transformation change we're looking to get across our businesses. So it's not something that you want to execute in silos. You don't want to execute AI in silos. You can get some efficiencies, but you're really not going to get the full value in the transformation unless you're able to, you know, drive those partnerships with other leaders in the organization and ensure you have the executive sponsorship. So those are all the key components. I think it was really about structures and frameworks, guidance and support for really putting the operating model of AI, if you will, lens on your business. I love that. You shared a lot of golden nuggets there around, you know, how you implement, how you need to get cross-functional buy-in, and how when you think about implementing AI, I mean, we were talking about AI and customer success, but in reality, if you go look at the whole golden market strategy, which you are, you know, this is your role, you're an expert in, it really is important that you're thinking about it and that whole pie, you know, not just bits and pieces to really make AI work efficiently for your organization. Now, I want to highlight a little bit your experience in the program itself. So for the listeners, right, just a little bit of context about how the program works. Every Monday, I release a new module in the learning portal. It's available for all the participants in the cohort. It's typically around an hour. Then I walk through concepts and frameworks, and then each one comes with an exercise so that, you know, you're not just watching, you're actually creating assets that you can use. Then on Thursdays, I host a live leadership application call. It's a working session where the participants of the cohort bring their workflows, get their questions answered, maybe troubleshoot some blockers in real time. For you, Suzanne, how did that format work for you? I love the format. I'll be honest, it's a lot of information, but it's great to be able to digest the material in an sort of async way. So releasing the content a few days in advance, maybe even further in advance, and it was released on a Monday, but maybe if we, you know, releasing it even a little bit earlier, it would be great to work on it over the weekend. I know the work weeks can get busy for folks, but regardless, I mean, it was great to get that in advance, to be able to work through it on your own. I felt like it was broken down and very manageable components. So you're not sitting down to an hour, but you're really watching little shorter snippets for each module, which was great. I really enjoyed the office hours, the leadership office hours, where we could bring the team together after everyone had a chance to, you know, digest the material on their time, you know, through their lens, and then be able to come into a group session where we could really talk about our different perspectives and what we're learning, what our questions were, and what we could take away. So I thought, overall, the structure was great, the pace was really good, and then the opportunity to revisit the material as well. So be able to go back to it and, you know, reassess, or if you need to complete some modules, be able to do that later. All right, I love the feedback. I'm going to think about releasing the modules early, because you're right, I think, I mean, like I said, it's one hour, I meant it to be bite sized as well. So it's not like one giant module, it's broken down. So you can take a break, you know, specific parts that make sense. But yeah, I'll just keep that in mind for the future cohort. But going back to you, right, I'm curious, what are you excited to apply next? As you look at AI in your, in your roller feature role, what lens are you bringing to the table? As you, you know, I'm sure every CS leader now is being tasked to use AI in one form or the other. How does that look like for you going forward? Yeah, I think you structured it really well by saying what are some quick wins and strategic bets. I think you have to look at it from both perspectives. With quick wins, you're looking at oftentimes, you know, efficiency and time savings, what are quick things that AI can do more efficiently and offload that activity to AI. I think that's really important. But also thinking about strategic bets. And one of the biggest things around the strategic bets, for me, of course, and I've spoken about it already, is really around value realization. So we are putting together a business case, and then, you know, their customer purchases our product and services, and then we get to a point post sale where we really want to manage to that value realization journey. So we have time to value moments, and we have different value milestones. But how can we do a better job of putting together a year over year value narrative of what is the customer realizing in terms of value year over year, whether they've been with us six weeks, six months or six years, we really want to be able to tell that value story and journey to support renewal and expansions. And I think that's the main one that I'd be really interested in, because that was, again, the last opportunity and role I was in, where I was really looking at it from what is that customer point of view. And I think we're seeing a lot of pivots in the industry anyway towards value, outcomes based pricing, value based pricing, those type of things. So I think it really fits with with where we are right now, and what I think we expect AI to be able to do in the long term. I have to say, I love that your your role actually explicitly talks about value or value realization or value transformation or value strategy. Because, like you said, I think that's where the industry is heading. I mean, I do believe customer success has always been built for that purpose. But somehow along the way, you know, we've had an identity crisis and thought that we are service or just, you know, helping customers be happy. But really, it's about helping customers get value. So I love that. I love that. And your focus as well on value realization, which, again, is a very interesting lens to bring on top of AI, right? Because at the end of the day, we want AI to work in service of the customers in service of your your team helping customers get to value at the end of the day, that's that's still the bread and butter of customer success value. So, Suzanne, I'd like to get your perspective a little bit, right, for anybody who might be thinking about, okay, I'm interested in the program, based on your experience, who is this program a good fit for? And why? Yeah, I think the program is a good fit for anyone that is forward thinking about their career about where they want to go in customer success, how they want to be more effective, and more strategic that we always talk about how do you be how do you how do you become a more strategic customer success manager or customer success leader. And we all know, again, that AI is really impacting everything we're doing right now. So the ability to get this kind of structure and frameworks to think at a deeper level about what you're doing, how you're doing it, what you should be focused on, I think is is just paramount to where we are right now, with the impacts of AI and not feeling that stress and anxiety. I'm just thrilled that I had the opportunity to take the course to get exposure to the frameworks to validate some of my thinking, but also to introduce me to new, new terms, new concepts. And I look forward to applying a lot of what I learned as well. I love the the adjective forward thinking, because I do believe like everybody in the cohort is forward thinking in their own ways. Everybody came there to invest in their personal development and professional development, obviously. But then also, like I said, just AI, being this new saying that is now part of our responsibility as customer success leaders. I love how you're getting really ahead of that, and really thinking, thinking forward as to, okay, how do I apply that strategically, like I said, in the organization. So Suzanne, thank you so much for being here and for sharing your experience so candidly. I really appreciate you taking the time and I know listeners are going to walk away with practical insight and a clear way to think about AI and customer success. If you enjoyed this episode and you're curious about joining a future cohort of AI for CS leaders executive bootcamp, I'll share details when enrollment opens again. I'm planning to open the next cohort for July and the best way to stay in the loop is to join the VIP wait list. I'll include the link in the show notes. Thanks for listening and I'll see you in the next episode.