The AI-First CMO's Guide: What to Break, What to Build, What to Bolster

Speaker A: Welcome to the get the podcast that's all about recruiting and leadership in B2B SaaS marketing. I'm your host Erica Seidel. I recruit CMOs and VPs of marketing for B2B SaaS companies from scale ups to larger companies. My tagline is that I place the make money marketing leaders, not the make it pretty ones. This season on the get, we're looking at how AI is reframing and reinventing the CMO role, especially as relates to hiring, getting hired and leadership. Today we do a deep dive on what it's like to go from a CMO role in a bigger company to a CMO role at a smaller company for an AI first build. And we look at advice for chief executive officers who are hiring CMOs today. My guest today is Suresh Balasubramanian. Suresh is CMO at Qualio, the quality and compliance management platform for the life sciences industry. Suresh previously held marketing leadership roles at Meridian Link, Qualys, Elevate Security, and also the Myers Briggs company. He also held a GM role at Adobe. So he has a really broad perspective. Suresh, welcome to the show.

Speaker B: Thank you Erica. Glad to be here and appreciate the intro. I was looking forward to a great conversation.

Speaker A: One thing I wanted to talk with you about is that you were previously CMO at Meridian Link, which is much smaller than Qualio. You can maybe tell me about the delta between the two of them. So what made it the right move for you to go to Qualio and switch from a, from a bigger company to a much smaller company?

Speaker B: Yeah, Merlink, uh, was, I would say almost an order of magnitude bigger. So it was closer to like almost 200 million-plus on a trajectory of about 333 million. I Ah, think it also has to do with the time frame that we're talking about. You know, nowadays everybody talks about, you know, ChatGPT and post ChatGPT. You know, everybody remembers November 2022 very well. Uh, but I think uh, for me the exciting thing was, you know, we had done a tremendous amount of growth at Maritimelink, growing from kind of the 200 to sort of doubling in about two and a half, three years. I would call it in a more traditional way where we would use more of the traditional demand gen Playbooks and there's a messaging, positioning, refresh. I was then advising a bunch of different, um, portfolio companies for one of the venture companies that I'd known really well for almost 15 years, uh, worked with them and to me the catalyst for this, which was really The AI transformation. I saw an opportunity where the amount of things that you could do with AI were just very, very interesting and the pace at which companies could adopt those things were interesting. And for me it was an interesting, it was very much a, uh, coincidence opportunity where I saw a smaller company that was ready to move much faster, that still had all the traditional challenges of we need to tell a different story, we need to rebuild our engine. But I saw an opportunity to implement a lot of the AI, uh, things in a much faster path. Yeah, what I could have done at Meriden Lake, which is a much larger organization. So when I looked at those two things, it was sort of an interesting, you know, opportunistic timeline to say, like, yeah, you know what, maybe, maybe I can take all the things I knew that works really well and then come in here and then kind uh, of drive growth at an, at a much higher scale using some of the latest technology.

Speaker A: Right?

Speaker B: So that's, yeah, that's what was interesting. Plus, compliance is something I've always been involved in from a security standpoint. And I got to do it in a new vertical like life sciences. I'm like, no, I'm a continuous learner. So this is like, oh, I get to, I get to get smarter. In other new industries.

Speaker A: Was it hard to convince them that you could kind of scale down? Because I know in my recruiting practice the biggest thing often that people look for is ability to kind of work at that scale, at the scale the company is at. And if a company wants to scale from like 20 million to 100 million, they yo, yo, back and forth between, oh, the candidate that's really great at 20 million, which is where they are now, and the candidate who's done the scale up to 100 million or beyond or whatever. So did that come into play in the process of looking at this role?

Speaker B: To some extent. But I think that also then gets counterbalanced with, you know, you kind of look at it from a, uh, from a role perspective or you kind of look at it as you get through the individuals that come through the process and then you sort of really double click into evidence. Right. Everybody says I'm, um, a hands on person. Everybody says I work with a small team. But I think where it gets interesting is when the company and the candidate can sort of really match up and say, like, you know, okay, I want to see real evidence, not just saying it, but have you done it? You know, maybe it's a, uh, it's a take home exercise or maybe it's a conversation you have with them. And because when you're in the thick of the conversations, you can quickly tell if somebody is just sort of gpd their answers or they've actually done it. I think the key thing when you're downscaling is you get the benefit of somebody who has seen larger scale, which is absolutely vital.

Speaker A: Yeah.

Speaker B: And then you want to see evidence if they are able to switch gears, I like to call it, you know, do they have enough gas left in the tank to do another run from that 25 to 50? Because just because a person has done the 25 to 50, it doesn't mean that they may not want to do it again.

Speaker A: Right.

Speaker B: You know what, I did it. Uh, now I want to go this way. But there are a few people that, well, like, you know, I did it, I enjoyed it. Now I see the environment is different. Like in my case, the environment was different with AI. I was like, I want to do it again and I've got gas in the tank. So I think that's a good way to calibrate for both sides, actually.

Speaker A: And it comes out in the conversation. Something I'd like to ask people is just what is something you'd like to be hands on with and what is something you do not deign to do?

Speaker B: And that usually is telling.

Speaker A: Yeah, yeah, that usually is telling. Yeah. What do you outsource and what can you do yourself? Can you step in and run a sales call? Can you step in and I don't know, send an email or blast or, you know, something like that? So where are AI teammates showing up in your org chart or slash and where like humans with new titles that wouldn't have existed a few years ago showing up in your org chart.

Speaker B: Now this is the exciting part of this role that I'm in. And at a company where experimentation is highly, you know, not just allowed, but highly encouraged, right. We very much look at our funnel in kind of the traditional bowtie model. So a good place to start if anybody's looking at retailing is really look at those points of friction all the way through. You know, we used to talk about the marketing funnel, right? Like then you had folks from companies like Mining by Design that said it's not just about the initial part of the funnel, it's the bow tie. You know, in a regular SaaS business, how do you retain and grow value? So we very much look at the whole bow tie. And I started doing that here when I got to got to qualia and you just look for points of friction. You look for areas where either things are just not flowing fast enough for the velocity that you want to build into, or you're finding people that are just doing a lot of manual tasks or you don't have enough people to do it so they're like, oh, you know what, I need to hire two more people. To me, that's almost like, especially now, you know, you look for those areas and say, how can we do this better? Not just improving the process flow through automation. Like, for instance, we did, uh, an entire rebuild of the top of the funnel lead qualification. So we didn't just improve the process marginally, but we built an AI agent that takes everything that comes in, does a 7, 8 source perplexity Gemini content search, maps it to our ICP and scores them on the fly. And it gives you a red, green, yellow flag. And we only pass the green and yellows to the BDRCs. We don't even pass the reds. So to me, that's an example of it's not a simple task. It's an agentic workflow. We tested it and then we put it in production over a quarter. We did the analysis. So that's the other thing is like, you don't want to just put a bunch of AI stuff out there. You have like, no idea. Like, okay, I saved money on not hiring more people, but I have no idea to tell you whether those things were valuable. Right. That's another big thing. As marketers, you know, we love to measure everything and we are held accountable for things. So this was a great example where this project worked where I was able to look back and saved almost six hours a week of, um, BDR time by not calling on the reds and just finding out that they are not a good fit. So in our organization, AI teammates are starting to pop up. You know, we built a little sales ops analyst and we called her Marian. And Marian responds to simple questions so you don't have to plug a human about it. So yeah, uh, the best way to think about this is look at your friction points and start building agent workflows and experiment with them. But before you do that, have a clear idea of what success looks like and make sure the success is defined in terms of hours saved or some new something new enabled so that this is something that you could never do before.

Speaker A: Are there any new people or new human job titles that have cropped up or is it more like these agentive workflows are supporting the, you know, the typical marketing, you know, people in the, in the org chart?

Speaker B: I think the Only one that has sort of come up more recently, I would say more recently. The sense like maybe the last 18 months is the GTM engineer, right? Like I think that one that I think any of us who spend in a marketing capacity in LinkedIn definitely come across that in a way. I think it has come about because the older models of rev ops or marketing operations, campaign managers that are digital marketers, having those roles separate made uh, sense in the older world. Older world means before the AI, uh, technology really took over because they were running on systems that were siloed and required expertise in those systems to be able to operate and to extract value out of them. So that's why you needed to have those roles as separate people who were trained up, groomed in that way. And then, and it had its moments and then it had its challenges as that world collapsed into like, look, there is no reason you need to have two separate roles to do this. You know, the campaign strategy ideas and digital marketing versus data analysis, especially with AI has gotten so much easier to do. I think there's a natural evolution with the role of GTM engineer. Somebody who has a little bit more of an engineering problem solving mindset but they're not 100% engineer. They understand campaign strategy, campaign architecture. And you definitely see that role starting to really pop up and people kind of growing into the role from either side. So if you either have an operations person that has a uh, digital marketing bent, they cannot come in through that, or you have a digital marketer that is good on the numbers and operations side, they grow into that. So I would say that's probably been the one sort of net new role that has emerged I would say in the last 18 months. Everything else is sort of a uh, better, more hands on version, more AI savvy version of a product marketing person or content marketer or a dimension leader etc. Uh, I think those are roles that, whose scope and characteristics have evolved. But a true net new role I think is GTM engineer. I think.

Speaker A: Cool, thank you. Let's change management. So often, you know, when you, when you come in as a new cmo, you know, it's like you look at people, process and technology and when we talked earlier you talked about like inverting that playbook. Can you talk about that? Is it tech first or people first? And you know, how did you, how did you tackle this role?

Speaker B: That's been the biggest area of surprise for me. I would say the last 12, 18 months, you know, I've done many change management. Usually I get brought in to drive change because uh, the status quo wasn't just not working. So usually the remit is to rebuild the marketing engine. Please get the pipeline generation out of the doldrums we're in. Let's make it much more responsive. And in the past, I would say the last three or four roles I pretty much used a very similar playbook subject to certain size changes of like, okay, let me do a 30 day assessment of the people that are in seats. I know what good looks like, what great looks like, I know what this organization needs. And then let's do a uh, change out, change out, bring the right people in with 60 days and then look at in parallel process. Let me get the people and process in place correctly. We'll use existing technology, we can do a little bit of experimentation and then go for overhaul of like, you know, okay, we need to bring in a new ABM platform or we need to do this or that, right. So it was a, that sort of staging of change management worked well. It usually produced results that within like about six months, you know, we get to a certain amount of predictable pipeline with all that thing. This last time around I think it uh, literally was like turned on its head because I walked into an environment where I had access to incredible technology that was just producing amazing results right from the get go. Because you didn't need to be an expert in a particular tech stack to get value out of it. Because of how fast AI had moved in there, there was a need to hit targets in a much shorter timeframe than before, uh, again back to that velocity. And so I almost changed the, I kind of recognized that and then that's an important attribute we can touch on later. So how do you recognize which playbook to employ? Because it's not, it's definitely not a one size fits all right. So it's sort of like you kind of have to read the situation a little bit and apply, apply the right playbook in there. But this one definitely was a change management turned on its head. I had to move fast in looking at technology first. So we looked at things like Clay or things like revamping of our counter enrichment process, et cetera. And I didn't need a whole lot of new people, new process to do that because we had technology that was ready to deploy. With the new systems you can just bring them in either because the system itself was fairly automated or we didn't need to have a huge amount of professional services and set up like the way you used to for enterprise systems. So it was helpful to sort of get the tech in there. And in a way the process, it was not so much about building old processes. The process itself changed. Like for instance, the agent example, uh, I gave you. It's no longer about automating that process to make it better. We have a completely new process. So it's no longer about somebody fills a form and a BDR calls them, qualifies the opportunity, that whole process is gone. Like somebody fills a form, they could just get an automated email from us because they're not a good fit. And so it didn't make sense to sort of bring people first process. We kind of went the other way then. It's like, now that I have a, uh, more AI first system in place, what's the right set of people to bring in that have that mindset so that the change is more durable? Right. So it's almost like you bring stuff in, it starts sticking, growing its legs. But then if you bring in people that are still stuck in the traditional mindset, they're either going to undo it or they're not going to be successful. Right? So to make the change durable, you bring in people that have an AI first mindset. AI native workflow, hands on thought process. They take that stuff and then they help it make better. Right. This is the first time I'm trying this. I'm calling it the inverted playbook, maybe the new new. Right. It's like the playbooks may be different moving forward just because of what we have available to us.

Speaker A: So you're trying to get this AI first mindset, but of course everybody's trying to prevent AI slop. So how do you message what you're trying to do without sending mixed slopes signals?

Speaker B: I think it is super, super important to continue to reinforce, you know, the following, right? Which is, hey, we highly encourage AI. You should be using it every day. Use it to do analysis, use it to gather data, use it to help you through the thinking process. In a way, AI is like having access to the hundred best product marketers and their brains. When you're starting to do like computer research, right? Like, so it's kind of like use it with that mindset. But every output that AI produces is just that, it's an AI output. Don't outsource your brain. You can just copy, paste a document and send it to somebody or send it to your manager. 12, 15 pages of content. They're not going to go through that. They're not employing you to push a button in an AI system. They're Employing you to bring your insights, your experience, your analysis on top of that. Right. So you kind of do that in a trickle down fashion. So if you're a leader, cmo, uh, or a marketing leader, make sure that your first line managers or reports to you are enforcing that, uh, so that when they send you stuff, it's their thought process, you know, it's their distillation and encourage them to do the same for there. And the fast follow is not discouraging AI use, but it's really about the right AI use so that the slop doesn't compound itself.

Speaker A: How do you kind of keep your sanity and navigate all the FOMO that it's out there? Because I feel like you say you're on LinkedIn, you see all the stuff that people are writing and producing or AI is producing for them and everybody's like kind of bragging about their usage. Does your brain never feel like it's going to explode with all the stuff that like you could be doing differently and like you're, you're rethinking, creating new processes? Is that, is that hard?

Speaker B: First of all, noise is everywhere. It's really hard to not pay attention to that. But I would say that for those of us who've been doing this for a while, and even if you're not been doing it for a while, remind yourself that these technological waves are just that they are technological waves. Obviously some may be cresting faster, some may be coming at you faster, but at the end of the day, you know, even for those of us who've been working, let's say for 10, 15 years, you know, you saw the cloud wave and then you saw the mobile wave and then obviously the uh. Yeah, and everybody would say like, yeah, you know what this is, this is a little different. It feels, it feels different. Yeah, every wave has its own little differences and some may feel more overwhelming than other and uh, things like that. So first is just remind yourself that, look, things are going to come at you, more things are going to come at you. But what you need to sort of keep in top of mind is what is my role? Like if you're a chief marketing officer, your role is make sure that you're understanding the market, you're able to represent your organization in the best possible way, understand your customers, the buying behavior, and go to metrics. Nobody can argue against successful execution against metrics. Right. No matter what the FOMO manifests in many ways because you, you may believe that you're doing everything right and uh, you may get an email from a board member or from a CEO, like, hey, I just saw this wonderful thing. Like, they're doing this. Like, look, why are we not doing this stuff? Like, you know, can we do this? And, you know, it is possible that it'll. It'll sort of knock you off your balance a little bit. But the way you sort of recenter yourself is go back to like, reminding yourself, like, okay, what is my core role and how do I define success in my role? And make sure you're continuously delivering successful things and telling others about it. I think that's the big point. As marketers, sometimes we get so caught up in just doing things or reacting to things, we often find it hard to market ourselves. Including me. I'm guilty of that. I don't quite often talk about things that we've done that have gone well. Make sure that you're maintaining a steady drumbeat of how marketing is succeeding at these things and how is it doing things? So go back to the basics. Nowadays it is helpful to take everything in. And now we have, we have a helpful handy AI agent. You just dump it into your AI agent. Say like, hey, I just got these three emails from my CEO. What is it talking about? Use that a little bit to your advantage too, and say like, help me understand what this is all about. Have we seen this before? So kind of fight the battle. AI battle with a little bit of AI help on your side. Have you grown a little sidekick? Do some. Burn some fable tokens and come back and have an intelligent response. But don't just send it as it is. Put your thoughts in there and say, thanks for sharing this. Here's the three ways in which we can use it. It's all about centering yourself, going back to the basics. How marketing success is defined has not really changed. So kind of stick to that and be strong in your, uh, conviction that that's what matters. Be fluid in how you handle things that come in. There is no stopping this or slowing this down.

Speaker A: And I love your characterization of the role. It's one thing I ask people often when I interview them is just like, how would you characterize the role of the marketing leader? And it's an instant way to see kind of their level of altitude, you know, because you said you went right into, like, the markets. So it's like, you know, the chief market officer kind of viewpoint, and everybody articulates it differently. And that's so fascinating to see that. Uh, let's talk about hiring. Like, how do you evaluate somebody's skills and how important do you think of AI fluency, call it versus industry experience and how are you hiring?

Speaker B: First thing is, across all roles, at least for us, AI fluency is a must have. We as a company have decided to completely roll the dice on this. We see AI native and AI mindset folks really as the key to our success. Right. Because we see that as a way for everybody to punch about their weight. So you hire somebody with like, let's say three to five years experience. They had AI native thinking that demonstrated that they're actually punching like at uh, 5% of usability. I see that across the board, even without looking at new talent, just across the board, just enabling the teams to do that. That's already happening and I would recommend that to others as well. I think smaller companies and smaller, I mean like say, you know, 500 employees and below can probably move a little bit faster. I think they are all definitely moving faster than larger organizations in terms of this AI, uh, first mindset as a, as a hard screen. Because smaller companies, I think it's, it's survival, it's, it's life or death. You bring in a bunch of people that are operating the old mindset way, you're just going to keep over no matter which function it is in marketing, definitely. But larger organizations can use this as a way to catalyze change. Right. Because the change has to start somewhere. Most people know that product development teams are already using AI very heavily, all the different tools. But the product development teams are often not, um, they're not going to go out and convince a lot of other teams to use AI because they're happy building their own stuff, no slight against them, they're just doing their work and they're getting more productive. Whereas if you look at a, uh, marketing team or a sales team or a product team, these teams tend to work much more cohesively together. So changing one organization can definitely percolate and impact positively other organizations. Right. There's more connective tissue there. So I would say that if you're looking at recruiting people today, certainly for companies that have either AI as a mandate or they're making AI, uh, products, if you're building AI enabled products, there's no reason you wouldn't be bringing more AI thinkers into your organization because you're hoping that your customers make that change. And how are you going to ensure your customer going to make that change if you're not ready to make the change? Right. So it's a little bit of a, you have to walk the walk and talk the talk There, So that's an initial bar you bring in. But I think the bigger question you're asking is like, okay, so how do I know, like if I'm talking to somebody, uh, you know, they send me a resume. And you know, nowadays it's easy to just AI wash a resume, throw in a bunch of keywords, and the next thing you know, it's like, it's hard to tell, right? I found that, uh, these kind of situations, it's almost back to that earlier question. It's like people that are hands on can be easily discerned by just a few questions, even as simple as like, hey, tell me the last interesting AI project you worked on or an agent that you built. And I even tell them that it doesn't have to be work related. And the worst somebody could say is like, well, you know, I really want to do it, but my company has all these like data restrictions and I can't really use AI at work. Well, yeah, but if you truly are the kind of person you're looking for, you would be hacking on the site and building your own little AI agent. And there's a general curiosity that we would look for, right? So that excuse, like my company's data policy prevents me from like, that's probably a good yellow flag or red. Uh, but I would say, yeah, somebody that's curious, hands on, they built something, they're able to talk about it. They'd be like, okay, so what pain point were you experiencing and what did you do about it and how did you go about it and how do you know it's successful? Right? So simple questions. And if they've done it themselves, you would easily, you can easily tell and you can tell from a few questions. So I look for definitely people that are not just about improving processes, but they've really reimagined it and they're kind of coming in with that fresh mindset. So I would say, you know, certainly if you're building, uh, marketing organizations, let's say for example, if you're building a, if you're hiring a product marketer, I absolutely want to see what they have done from uh, competitive analysis and research. Have they built their own little agent that does a continuous market analysis, brings content and how have they used it? Uh, you know, most companies do they have some version of gong calls or outreach calls, you know, have they built something to analyze those things? So for each of the functions, there's definitely early evidence that somebody is actually thinking differently that you can use in an interview process to flesh out Worse times worse. I sometimes pull up my cloud cowork and I just show them like say hey, this is what, this is how I post my chief of staff. Plug in. And then we start riffing and I'm like, okay, I know this person is hands on, right?

Speaker A: This is interesting because I know some investors are saying show me what you're building in AI, which you know, pros and cons. Hopefully they see something. But on the other hand, some people like you say their work is multiplicative. It's ac. Not just marketed but uh, m marketing. But uh, it, you know, touches sales and success, etc. So you, if you just see one person's clawed instance, you may or may not see as much of that, that kind of connective tissue. But interesting that you share your own and you ask them to riff. I like that.

Speaker B: But it's like you have to have certain amount of context around the stuff, right? So I would say for product marketing I think the industry expertise is very helpful. Um, if you're on the demand gen side, I would say it's less of a hard requirement on the industry expertise because there are ways to layer on buyer Persona types, archetypes, channels that are, uh, that you reach certain archetypes, et cetera, that transcend industries. And I think there you want the expertise to be more around experimentation. You know, how good are you at experimenting across multiple channels? You know, when are you ready to kill something because it didn't work. So I would say it depends on the function.

Speaker A: So let's talk about advising CEOs now. So like if you were advising a CEO hiring a CMO today, what would you tell them to look for that might not show up clearly on a resume?

Speaker B: I think it is absolutely reasonable when you're talking to candidates to expect both a level of the craft of marketing and marketing leadership, but also very recent AI hands on experience. Even at the CMO level. If the CMO says look, yeah, I've got a team that does that. Um, I mean I, I'm in cloud co work every day, right? Like, and I would still be in cloud co work even if I'm at a, at a $200 million organization. I think there's a mindset that you definitely want to look for because no matter what size you're at, you want to, you want to sort of have a leader that has that transformative mindset that you can, you can rely on to drive change. Because as we talked earlier, if you bring in a good leader at the marketing function, there's an uh, opportunity for you to drive that change in through sales, through customer success, through product. Because they tend to work with those. Right. So it's a good way to sort of introduce change in one function and drive it out. So I would definitely say, you know, look for that mindset, look for some hands on skills. Examples would be very helpful. Not just AI for AI sake. It's like, you know, what, how did you know what you deployed worked? What substantially improved. Certainly at a CMO level, they should be able to step back and talk about projects at a larger scale in terms of their transformative power and what results came out of that. I would say over the last 12 months there's enough of this technology that's gone into these organizations for us to see some tangible improvements. So it's not so much like, oh yeah, we just put this in place, we don't know yet. Right. Like that's not really a defensible position anymore.

Speaker A: I like that. And your point that even at a, uh, $200 million company, $500 million company, you should be seeing that hands on. So another way to put it is that, you know, a lot of CEOs are pushing for AI everything, you know, when teams are already, you know, kind of overwhelmed. And So I think CMOs can be caught team unless they have all these AI native people on their teams. And so what should CEOs expect from their CMOs in that kind of situation?

Speaker B: I think there should definitely be, um, a very solid dialogue on that front and not a monologue. I think the CMOs should feel very comfortable setting the expectations of success going back to that metrics because that relationship still needs to be grounded in the business fundamentals, independent of AI. That's the first order of business which is you should still be able to have a conversation. The CEO. And the CEO should be able to have a business conversation in terms of the outcomes that they want to drive, the kind of projects that they want to do, and then how will they know that if it's successful, they should be able to have that 15, 20 minute conversation without the use of AI. That's business fundamentals. Like uh, CEO should be able to say, yeah, you know what, these are the markets or challenges we have. This is the kind of growth I want to drive. This is the kind of ROM looking for. And the CMOs should be able to talk about it in just sort of business terms. The AI then becomes more of that. Grease the wheels or the, you know, the accelerant. Like that allows the organization as a whole to achieve those, those, uh, objectives either at a faster rate or on a more efficient scale. That's the way to think about that. Right. So. And then give grace on both sides. Right. Like, you know, don't bring in a CMO and then expect them to do one in 30 days just because you dump them in the role. And then, you know, done with a lot of the AI stuff, it's not the magic pill. I think it needs to be used thoughtfully. You could absolutely deploy something in 15 days and have it be slopped, or you can deploy it in 30 days and have it take root and have a drive change that is more sustainable. Clearly there's a middle ground there. If somebody said, I'm going to take six months to do this AI project, there's something wrong, but something in one week, uh, two weeks versus four weeks, I think it's okay. I think it's, uh, I would say have good expectation managing conversations on both sides and be ready to handle FOMO, because that's going to happen. Like the LinkedIn stuff's not going to go away. But I would say it's good to have the business conversations. Those kinds of minimums have not changed. That also becomes a nice catalyst to drive change across the other departments. Hiring with that mindset, I think that's a nice side bonus as well because this leader can then help you drive that transformation.

Speaker A: Well said. This is fabulous to have you on the show. Thank you so much for joining Suresh.

Speaker B: Thank you. I've enjoyed the conversation

Speaker A: that was Suresh Balasubrahmanian. Now that you've heard from Suresh, think about how you can balance business knowledge with AI fluency in your role. Thanks for listening to the get. I'm your host Erica Seidel. The GET is here to drive smart decisions around recruiting and leadership in in B2B SaaS marketing we explore the trends, tribulations and triumphs of today's top marketing leaders in B2B SaaS. For more about the GET, visit thegetpodcast.com if you like the GET, please share it and please leave a review to learn more about my executive search practice which focuses on recruiting the make money marketing leaders rather than the make it pretty ones. Follow me on LinkedIn or visit theconnectivegood.com the get is produced by Evo Terra and the team at Simpler Media Productions.