The B2B Roundtable Podcast

About The B2B Roundtable Podcast

The B2B Roundtable is a podcast about what dashboards miss in B2B revenue systems. Most GTM teams manage what their dashboards can measure. But the numbers don’t always explain why growth is slowing, buyers disengage, or revenue isn’t keeping pace. Hosted by Brian Carroll, GTM advisor and author of Lead Generation for the Complex Sale, the show features candid conversations with B2B leaders, operators, and thinkers about what’s really happening beneath the numbers, what they’ve learned, and what they changed. Learn more at https://www.markempa.com

Publisher

Brian Carroll

Category

business · business · business

Language

en

Explicit

No

First episode

13 Sept 2016

Latest episode

6 Oct 2026

Latest episodes

28 episodes in the feed.

1. 

   6 Oct 2026

   Why GTM Alignment Breaks Down and How to Fix It with Martha Mathers

   About This Episode Everybody talks about GTM alignment. Sales, marketing, and customer success all working together around the customer. But actually making that happen changes how teams work together, and that’s where most alignment efforts quietly stall. In this episode, Brian talks with Martha Mathers about where GTM alignment breaks down and what it really takes to fix it. Martha starts with pipeline first and top of funnel second, because pipeline is the one thing sales, marketing, and success can all agree on. From there she walks through mapping the journey from the customer’s side, what happened when a new sales team at OPEXUS kept jumping straight to the demo, what thousands of sales conversations taught her, and why she listens first (and says as little as she can) when she steps into a new role. Here’s the thread running through the whole conversation: the problem you see when you walk in usually isn’t the whole problem. About Martha Mathers Martha Mathers (https://www.linkedin.com/in/martha-mathers-505985/) is a B2B marketing and go-to-market leader who has led marketing at Bloomberg Industry Group, BigTime Software, and OPEXUS. Her experience spans marketing, sales, customer growth, and leading cross-functional GTM teams. What We Cover Why Martha starts with pipeline before top of funnel Getting sales, marketing, and customer success working around the customer journey What changes when you think beyond the funnel and include expansion Enablement as the connective tissue across GTM What Martha learned from listening to thousands of sales conversations Using AI to learn from more data and conversations, not just create more content Why experience can get in the way when a leader walks in thinking they already know the answer How much consensus it really takes to make change in a large company Making change a step at a time instead of trying to do everything at once What marketers need to learn outside of marketing if they want to eventually lead the business A Few Things Worth Taking Away Pipeline gives sales, marketing, and success something they can agree on. Start there and work backward. Look at the journey from the customer’s side. That’s where the gaps between teams become easier to see. Listen to what customers and salespeople are actually saying. You may find that the story being told in the market isn’t the one marketing thinks it’s telling. Experience can create blind spots. Martha’s approach is to ask questions before assuming the answer that worked somewhere else will work here. Big companies take more consensus than you think. Knowing who needs to be involved is part of making the change. Change doesn’t have to happen all at once. Sometimes the better question is, “What is the change I can make this week?” A Few Lines That Stuck With Me “I’ve seen many leaders come in and assume by telling stories of everything they’ve done in the past, they will be able to fix the problem ahead of them.” “I listen first, ask a ton of questions, and share honestly as little as I can.” “Those are all different owners and different initiatives, but at the end of the day they all go back to the same account.” “We have a tendency to lead with the shiniest thing we can.” “I tend to value it, you know, more from an intelligence perspective than perhaps a content creation perspective.” “What is the change I can make this week?” Resources Mentioned Matt Heinz, whom Martha credits with the line “an MQL can’t buy you a beer” Gartner’s research on the B2B customer journey (https://www.gartner.com/en/newsroom/press-releases/2026-03-09-gartner-sales-survey-finds-67-percent-of-b2b-buyers-prefer-a-rep-free-experience) Chapters 00:00 Why GTM alignment breaks down 00:56 Where GTM alignment gets disconnected 02:33 Why pipeline should come before top of funnel 03:45 Aligning GTM around the customer journey 05:17 Expanding customer relationships after the sale 06:49 Why enablement is the connective tissue of GTM 10:30 What thousands of sales conversations can teach you 13:26 How AI can improve GTM alignment and enablement 15:53 The biggest mistake leaders make with GTM alignment 19:36 Stakeholder consensus and leading GTM change 23:34 How marketing leaders can prepare for the CEO role Transcript Brian Carroll (00:01) Welcome to the B2B Roundtable. I’m Brian Carroll, So everyone talks about GTM alignment. That’s from marketing, sales, customer success, all aligning around the customer. But actually making that happen changes how teams work together. And so the question I wanted to ask is: what really works? How do we actually make this happen in reality? And that’s why we have our guest today, Martha Mathers. Now, Martha has been the head of marketing at companies from Bloomberg Industry Group to Big Time Software to OPEXUS And I wanted to talk with her because she understands this. And something I saw her talk about recently in a panel discussion on YouTube is that for her, they started by focusing on the pipeline first and top of the funnel second. So, Martha, welcome. Martha Mathers (00:53) Thank you so much, Brian. I’m really excited to be here. Brian Carroll (00:56) I wanted to ask you when you think about companies that you’ve worked with, where do you see GTM alignment getting the most disconnected? Martha Mathers (01:05) Yes, a great question. And I think it can happen in a couple different places. To your your first point, I think in terms of beginning with pipeline, I always think about where are those places where sales and marketing come together could be success as well, thinking about all of those combinations. But what is the thing that everybody cares about? As a our friend Matt Heinz once said a long time ago, an MQL can’t buy you a beer. I believe that is that remains true. And now there are all kinds of debates about MQLs. But from a pipeline perspective, that is something that marketing can typically see their way easily to sales needs and must have in order to hit their number. And often with expansion motions, you have success thinking about quite a bit as well. And so I always start there. Can I see where pipeline is coming from? Can I see how marketing is contributing to it? and just depending on where I’ve been in the stage of the company, OPEXUS was one without a go-to-market function. And so we started by building pipeline and thinking about how each capability would begin to execute against it. I’ve been in other organizations that are bigger and at greater scale, but they don’t have that shared understanding. So just establishing that layer first of where does pipeline come from and where should it come from, and how can marketing contribute is is something I try and do as early as possible when moving into a new. Brian Carroll (02:33) Well, it as you were talking about thinking pipeline first and top of the funnel second, was there something that changed for you that made you look at it that way? Martha Mathers (02:41) Yeah, I I think there’s, you know, the debates that you can often have as a marketing leader with a head of sales around the quality of an MQL. And it at the end of the day, it’s finding that common currency and that that lingua franca in terms of I may be very excited about what’s happening on LinkedIn. And that matters a ton. Don’t don’t get me wrong there. That helps a ton in terms of brand awareness and reach and just how someone thinks about your company. and As does every dollar and investment that brings a a new kind of contact or buying group in the door. but that was something that sales didn’t necessarily care about unless they’d maybe been on the ground at an event and had a good quality conversation. So by starting with pipeline and showing where a marketing investment actually turned into a quantity of dollars that maybe then turned into a quantity of dollars booked was something that we could hold hands around and agree on. And then once I had that data layer, I can back my way into how to invest at different points in the funnel to get the pipeline that we need to grow the business. Brian Carroll (03:45) what’s it take to get sales, marketing, and the post sales teams all working around the buyer journey? Martha Mathers (03:54) Yeah, one thing that we did at OPEXUS was we really had a lot of missing capabilities when I started, as well as a couple of other executives. And for us, it was starting with a customer and starting with the customer journey. That’s something that you’ve you’ve heard, we’ve both heard Gartner talk about quite a bit over the years. Brian Carroll (04:14) Yes. Martha Mathers (04:14) and I had the I had the opportunity to do a good bit of research around too. It’s not mapping your sales and marketing and success activities. It’s really considering that journey that the customer is is navigating throughout. And so I think if you can start there and think about what brings a new buyer to us, what engages them in a conversation, what makes them consider our solution, and then how do we get started and onboard someone? Those are all different owners and different initiatives, but at the end of the day they all go back to the same account. And so I I always look at start with that buyer, map those key touch points, understand if you have the data to get underneath what’s happening at each and every one of those stages. And then those places where you can build that strong cross-functional coordination and handoff, I think become much more apparent, both in sharing information across teams, but also pinpointing the areas. for example, just a kind of quarterly business review where there could be sales marketing. and success implications. Brian Carroll (05:17) Well, and after someone becomes a customer, this is an opportunity I hear a lot of companies miss, So do you have any advice or things you’ve learned that helps expand customer relationships? Martha Mathers (05:31) Yeah, most recently at one of the larger companies I’ve been with, we began the work to design and build out a customer marketing capability. I think often those expansion motions can be, you know, added onto demand gen float and all of a sudden you’re you’re pulling someone in a couple of different directions, starting with different buyers, depending on the size of the company that often Brian Carroll (05:53) Mm-hmm. Martha Mathers (05:53) can make sense as well as how the company grows. But in this instance, we were struggling a little bit with some retention issues in one part of the business and had just a ton of new products to sell in another part of the business. And so we looked at, you know, how do how do we move away from thinking in funnel terms to thinking in bowtie terms? and what is the role that marketing can play from getting somebody onboarded to into the product and using the product? and then once you have those signals of strong health. How do you start to lay the groundwork to grow that relationship? Can be at scale really easily if you if you have those kind of natural expansion points that are customer activity based, but it can also be a very sophisticated and maybe kind of detailed account-based motion in terms of thinking about exactly what the expansion path can and should look like for a specific account. Brian Carroll (06:49) And connecting all these pieces together, I’ve heard you say that enablement is the connective tissue around GTM. So what does great enablement look like? Martha Mathers (07:02) Yeah, I I have seen enablement live in all different all different places. And at the end of the day, I don’t think it really matters where they live because enablement really just like the customer has to work as that that connective tissue. You can build great messaging from a product standpoint. You can have all star reps and fantastic renewal conversations, but if that messaging never leads leaves product marketing, if nobody is studying what those best reps are doing, those stories get a little bit lost along the way. And so I think of enablement as really taking the most valuable assets you have across all of all of GoToMarket, curating them, and figuring how how do we get these in people’s hands, how do we make them better? How do we use data to learn and iterate and ensure that we’re continuing to put the most powerful resources we have as a company. in every go to market operator’s hand. Brian Carroll (07:59) So as you’ve had the experience over your career, can you maybe think of a story of where something wasn’t really working great and that you needed to work with the team to fix where there were misalignment or issues? and where revenue is getting lost between the seams. Martha Mathers (08:17) One thing I go back to is you know, starting with the customer journey, so many of us see so much turnover across go to market, but in particular with sales teams. when I was at OPEXUS we had a relatively new sales team that we had brought on board and we were really trying to ramp up not only their company skills but their selling skills, and finding that we were quick to jump into the product, quick to jump into a demo, and so we Started with that customer journey and worked backwards to say, how do we create the right plays for every stage from qualification to discovery to demo, all the way through into the post-sales experience? It was a a fun project to dive into because we needed data from all over the company. So, you know, helpful to have a good RevOps person doable even if you don’t, because we were looking at those touch points and those. questions and what could we curate from all the conversations that we had to design a playbook that then informed our content strategy, helped with discovery questions, helped with the demo narrative that you would put in front of anybody all the way through to our retention plays. And so really impactful initiative in terms of aligning the whole go-to-mo-to-market motion from start to finish. It allowed us to really pinpoint helpful things like exit signals when you’re moving from one stage to the next, and Brian Carroll (09:39) Mm. Martha Mathers (09:40) really start to learn and see a lot more about that customer journey and those key transition points. And actually, just to take it a little bit further, was a really helpful place at which we started to think about: hey, so many of these conversations that we’re having with existing customers point in one of three directions. So that allowed us to kind of take what had been a new business focused effort and migrate it into an account expansion effort. Brian Carroll (10:07) Wow. And so as I’m listening to you, what what I’m hearing you did is you started with the data and that gave you the areas to focus. And and then from there you started listening and and talking to the frontline team to see where things were breaking down and then use that to help inform what you’re doing. Is that what what I’m understanding correctly? Martha Mathers (10:28) I I think well summarized, yes. Brian Carroll (10:31) Okay, very good. So one of the things you’ve talked about is you’ve listened to thousands of sales conversations. And this is something that is near and dear to my heart because I think this is something a lot of marketers we have the ability to listen, but I don’t know how much time you know spent there. So I wanted to say, what did that teach you? What did you learn? Martha Mathers (10:55) Yeah, I think we now are are lucky to have just so much great technology at our fingertips that can make that listening act that much more powerful. But you know, more more recently have spent a lot of time listening in terms of we want our ICP to look like this. How do those conversations stack up? and I think you can find, you know, multiple flavors of very helpful feedback, some of which is, wow. I didn’t know we were positioning our product in this way. And that’s probably not exactly what we want to do because our competitor is stronger there. On the flip side, I think you can uncover gold in terms of customer pain points that you didn’t know necessarily were the the thing coming up as frequently as they were, and those talk tracks that your star reps use that you wish and hope you could curate and build into your pitch deck and every other reps talk track as well. and so listening to all those conversations, there’s a little bit of good, bad, and ugly in terms of what do I want to take in scale? What is gold that needs to make its way back to product and into the hands of every single rep? And what are the things we need to course correct so that we Brian Carroll (12:01) Mm. Martha Mathers (12:01) can put together more compelling stories, more compelling content, and and position in a way that just sets us up for greater success. Brian Carroll (12:11) As you’ve done this, is there any surprising things, ahaas or counterintuitive things you took away from listening to all these conversations? Martha Mathers (12:20) It’s a great question. I think, you know, sometimes in in marketing and vice versa as well, it’s easy to say, you know, we’ve built this great story, but nobody is is sharing it or or telling it. And I think, you know, thinking about the reality of catching someone on the phone and having a quick 10 minute conversation, especially for an earlier career marketer, is a really impactful moment of just listening to yes, you can design the perfect. Choreography, the perfect story, but your ability to deliver that isn’t always exactly what you want it to be. So in in terms of really uncovering one, how do you flex that narrative and and teach people that storytelling arc? If you can plant a narrative, you know, plant it here and there. but also all the way to wow, we really thought that we should lead with this, you know, AI-powered XYZ platform. But every other competitor is doing that or no buyer cares about that. It’s really about the fact that you reduce risk by XYZ or you can increase revenue by a certain amount. Brian Carroll (13:26) It’s interesting as you talk about the what’s resonating with customers and hearing the words they say and how that can be applied back in. And you said the word AI and I was just wondering, you know, right now, where do you think there’s opportunities as as you think about this whole process of getting alignment? Where can AI help or where have you personally used it as is part of this enablement or to help you be more effective at getting alignment? Between all these teams. Martha Mathers (13:56) Yeah. And maybe two different flavors to that in terms of internal Brian Carroll (13:59) Yeah. Martha Mathers (14:00) versus external. I think on the external side, we all, you know, as we innovate and build incredible new products, we have a tendency to lead with the shiniest thing we can. and I’ve worked with teams, you know, across multiple companies to say, but what is the thing, what is the problem the buyer is is struggling with? And I think that’s rarely they need AI. Now on on the flip side of that, there are some in house legal buyers that I’ve worked with who have company mandates that they need to be using AI. and in that case, thinking about how you can position your solution in a way that solves their problem and helps them get work done can be impactful. So, you know, I I I think you just have to be careful not to introduce yourself just like everybody else in your category is and to figure out exactly how it can it can impact impact your your buyer. On the from an internal perspective, I think it’s just incredible how much information that myself, my leaders can consume at scale. everything from you know quickly looking in Salesforce to be able to do a a quick and dirty win-loss analysis To your point, curating the thousands of sales conversations with different types of buyers and and really having those insights to to dive more deeply into. I tend to value it, you know, more from an intelligence perspective than perhaps a content creation perspective. Brian Carroll (15:28) Mm-hmm. Martha Mathers (15:29) where I think it while I think it can be powerful there, I think it can also generate some not so great outcomes as well. and so I tend to coach teams towards where can it make you smarter, where can it help you examine the data in new ways and perhaps give you a running start. but really, you know, encouraging individuals to put that human touch on on things that require more creative capacity. Brian Carroll (15:53) Yeah, I agree with what you’re saying in terms of from the content standpoint, avoiding the sameness and looking at how do we have our voice and do things that are uniquely human. And as you’re talking about the the research side of things, the enablement side of things, I was wondering as you’ve reflected back on all all the learnings you have, where do you think that companies make the biggest mistake when it comes to trying to get Alignment. Martha Mathers (16:22) good question. I have to think about that one for a minute. I I think often there are hiring decisions made. You know, this person will be able to, you know, get alignment because they have done it before. and I’ve seen many leaders come in and assume by telling stories of everything they’ve done in the past, they will be able to fix the problem ahead of them. Brian Carroll (16:46) Hmm. Martha Mathers (16:47) I tend to personally think a lot more about why is the problem the way it is and push deep into kind of questions before I do anything. I I, you know, time creates lots of biases and hypotheses, and I really try and push those into the back of my head so that I can sit down perhaps with the head of sales just push to understand. Tell me about your experience with my team. Tell me, you know, what the good, the bad, the ugly is. Help me understand what better would look like and what your team needs. And I think that often, one, it helps build trust just because you’re not racing in with a beautiful deck of here’s what the future will look like. but two, it I think it can help uncover education opportunities as well once you are ready to deliver that that roadshow deck as well. And so I listen first, ask a ton of questions, and and share honestly as little as I can so that I can then take that information back and come back with something that that actually has a prayer of of solving the problem. Brian Carroll (17:52) Well, I appreciate you talked about looking at the evidence and really trying to understand what is the problem, you know, rather than trying to jump in as you’re talking about trying to fix it. And I think there’s something we all could take away from that because you know, maybe the problem you see isn’t actually the problem. and I was wondering if you had any advice for someone who may not have done that. Maybe they’ve had a successful track record and they’re stepping in a new role. So Is there any advice you’d want to give to peers who are listening out there on how they might be able to tackle this going forward? Martha Mathers (18:26) Yeah, if I if I think a little bit about a playbook, it’s you’ll probably walk into a lot of data. Some of it might be good data, some of it might be bad data, but take what you have and see what you can gather from it. And then I I really overinvest in building out you know, what are this, what’s the set of things that I would like to learn from this person? it could be where it could be completely unrelated to marketing in terms Brian Carroll (18:48) Mm-hmm. Martha Mathers (18:49) of where do your customer conversations start. What do you wish that you know had over the course of a discovery conversation? Where would you like to see more leads come from? why do our customers churn? you know, what have you what do you think of our competitor? But you could go in any direction. I tend to build out that detailed list and just think about I can probably learn something different from Brian than I can from this person, than I can from that person. Each of those things will give you a great angle on the business. And then as you go and synthesize and think about the pieces you picked out from each person, each one of those has value. Not no Brian Carroll (19:25) Mm-hmm. Martha Mathers (19:25) one of those will be a hundred percent correct. And so that synthesis activity in terms of thinking about how to move forward is beyond the questions where I also spend a ton of time. Brian Carroll (19:36) Well, and as as I’m listening to you, I was wondering, looking back over your career, is there’s an area that you underestimated about making this kind of change and and doing it at a scale? Martha Mathers (19:49) That’s a great question. I think, you know, I’d I’ve had experiences at companies from 10 million up to many billions. and if I’m coming from more of a mid-market company to a larger one, I always underestimate the amount of consensus required to to kind of push things forward, which it probably seems obvious to anyone that’s only lived in large enterprise. but that That whole act of ensuring you’ve identified all of the stakeholders who will have an opinion, who want to weigh in, and making the time for that. Everything from product naming to positioning a new solution to how you show up at an event can just have such a wild range of opinions that I think you can almost never overplan or over gather input thinking about the approach that you want to take. Brian Carroll (20:43) And I imagine and this is implied in what you’re saying, but this consensus also is about getting people on board with change and this whole Martha Mathers (20:53) Mm-hmm. Brian Carroll (20:53) notion of change management. Is there some things that you’ve taken away on what’s been effective and helping support change? Martha Mathers (21:02) I actually recently had one of my leaders point out to me something that I think actually is quite crucial to my approach. I tend to generally avoid a big bang type of change and look more for how can I incrementally build in the direction that I know that I need and want to go. And so I I think especially if you’re trying to quickly build credibility with a large team, thinking about, okay, what is the change I can make this week? And then maybe, you Brian Carroll (21:30) Mm. Martha Mathers (21:31) know, another week later it’s another change. And I’ve applied that everywhere from how I’ve run leadership team meetings to how I’ve approached marketing planning, to how I’ve approached, you know, naming at a company like Bloomberg Industry Group and and thinking about just all the opinions and things like that that matter and are critical. And so to me it is, it is really, you know, how do you design a journey where every step of change, you know, They feel it. They may not love it, but it it feels like a digestible move forward. And then all of a sudden you look back, you know, the the past six months and you can point to some massive moves that you’ve made for the business. Not doesn’t work for everybody, but that is, I think, an approach that I that I’ve used again and again. Brian Carroll (22:17) Yeah, and as you were talking about, this is something people underestimate is how long it takes to drive change. And I really liked what you’re saying is what incremental changes can we make? How can we move forward and answer or ask that question? What’s the next best step? What should we be focused on now? Is that what you’ve been saying? Martha Mathers (22:39) think that’s exactly right. And sometimes it is pretty thoughtful in terms of if I know the path from A to B, you know, exactly what that looks like, I try and break it down into the ten things that will take me there or the five things, depending on the the size of the change. I think big bang changes can make sense given the time and the place, but they can also be pretty disruptive in terms of the things that you need to get done day in and day out. And so I the question I would, you know, guide many to is think about, you know, how quickly do you need to move? How big is the risk of disruption? and does the does the pain of the change, you know, outweigh it? And if it’s risky, thinking about how you can move a bit at a time can be, you know, a a much more practical approach in terms of just aligning your team and bringing them along with you and empowering them to drive small change as well. Brian Carroll (23:35) Well, I’ve loved talking with you. Martha, that as I’ve talked to a lot of different leaders, something about you that stands out to me is how you bring the strategic perspective to how you’re operating the business. And one of the things that I wanted to ask you about from a marketing leadership standpoint is the path to being the the top. most leader in an organization, the CEO and B2B companies typically doesn’t happen by going through marketing. And I wanted to ask you, why do you think that is? And for those that may want to move into the topmost seat, what do they need to be doing differently to do that today? Martha Mathers (24:15) Yeah. I think, you know, if I think about that journey overall, one of the best experiences I’ve had in my career was managing sales and marketing together for a couple of years. it was great in terms of the customer’s experience as well as sales and marketing alignment, but it it also expanded my perspective. It was certainly helped by having that leadership seat. I don’t think that’s a must-have. That could just be Ensuring you’re added to pipeline calls or forecast calls or diving deeply into the sales process. Similarly, if there is a retention priority at your company, how can marketing support? Many marketers spend a lot of time thinking about the product roadmap and you know how to what should be on it. Maybe try and gain some exposure to how to prioritize what goes on it and how it’s resourced and that sort of thing. And then I would also say just being constantly curious from a financial perspective and understanding the financials of the business and exactly how and where sales and marketing spend fits in is another area that can help. So pushing if if I sum that up, looking Brian Carroll (25:23) Yes. Martha Mathers (25:23) for areas where you can expand your skill set, expand potentially your ownership through cross-functional initiatives. then approaching the business with that constant curiosity would would be my my top takeaways. Brian Carroll (25:37) Well, thank you, Martha. I’ve loved this conversation. I’m really glad you were able to join us today. Martha Mathers (25:43) Thank you so much, Brian. It’s been a lot of fun. Brian Carroll (25:46) Thanks everyone for listening to the B2B roundtable. We’ll see you next time.

2. 

   14 Sept 2026

   Stop Automating the Past: How AI Is Changing the Way We Work with Liza Adams

   About This Episode Most GTM teams are using AI to make existing work faster. But faster isn’t the same as different. And the teams that are actually pulling ahead aren’t automating the past — they’re reimagining the work itself. In this episode, Brian talks with Liza Adams about what separates teams that are getting faster with AI from teams that are actually changing how they work. Liza shares the story of Megan, a senior marketing leader who used AI agents to orchestrate across marketing, sales, and CS until her work outgrew her title entirely. That story illustrates the bigger idea behind the conversation: what happens when you reimagine the work first, then redesign the roles and the org around it. About Liza Adams Liza Adams (https://www.linkedin.com/in/lizaadams/) is the founder of GrowthPath Partners (https://www.growthpath.net/), where she helps B2B GTM teams move beyond AI productivity into AI-driven transformation. She spent 25 years leading GTM teams at companies including Smartsheet and Juniper Networks, and has worked with AI and machine learning long before ChatGPT. She is passionate about elevating the strategic value of marketing and helping leaders use AI to become business leaders, not just functional leaders. What We Cover The AI adoption plateau and the three patterns that cause teams to stall Why your belief about what AI can do is the cap of what your team will ever build Using AI as a sparring partner vs. a validation tool, and the research behind why it matters The difference between what’s hard for humans and what’s just historically hard How AI doesn’t care about your org chart, your silos, or your titles What CEOs are starting to want from CMOs and why most marketing leaders aren’t set up for it Why reimagining the org chart starts with reimagining the work, not the other way around A Few Things Worth Taking Away AI for productivity should be the floor of our expectations, not the ceiling. If we only make old work go faster, we can project how it automates the human out. But if we use AI to do something different, we’re innovating, and when the business grows, humans are essential. People aren’t stupid. They just need to see what’s possible. Talking about AI capabilities is different from showing someone a workflow that pulses the market 24/7 and surfaces which customers are about to churn. Humans that use AI as a sparring partner outperform pure human teams and pure AI teams. But humans that use AI to validate their beliefs actually perform at a lower level than an all-AI team. In the RACI model, AI will never have the A. It will never be accountable. It will never lose the job for you, pay the fines for you, or go to jail for you. Don’t start with “what does the org of the future look like?” Start by reimagining the work. When you reimagine the work, the roles become clear. When the roles are clear, the org chart follows. A Few Lines That Stuck With Me “The cap of what our teams will ever build, do, and use AI for is limited by what they believe it can do.” “AI transformation can’t happen when we’re in a hamster wheel.” “AI will never lose the job for you, it will never pay the fines for you, and it will also never go to jail for you.” “It’s like hiring a bunch of actors before you even know what the script is.” “AI is making the mechanics a lot easier. I think our biggest challenge now is us.” Resources Mentioned AI Is Cannibalizing Human Intelligence. Here’s How to Stop It. (https://www.wsj.com/tech/ai/is-ai-smarter-than-humans-cyborg-956e0f0e) by Vivienne Ming (Wall Street Journal) What Harvard Learned From 776 Professionals Using AI (https://enterpriseaiexecutive.ai/p/what-harvard-learned-from-776-professionals) (Harvard/P&G research on AI and cross-functional collaboration) Chapters 00:00 Why Getting Faster With AI Isn’t Enough 03:20 Why Teams Hit the AI Adoption Plateau 07:43 AI as a Teammate, Not Just a Tool 10:10 Using AI as a Sparring Partner 12:35 What Work Is Only “Historically Hard”? 18:12 AI Can Do the Work. Humans Own the Outcome. 19:32 From Org Charts to Work Charts 26:19 What CEOs Need From CMOs Now 34:33 Reimagine the Work Before the Org Chart Transcript Brian Carroll (00:00): Well, I see this a lot in sales and marketing teams. People are using AI, some are using it really well. They built workflows, they built custom GPTs, they’re getting faster and better. But there’s a big difference between getting faster with AI and actually changing how your organization works. Welcome to the B2B roundtable. I’m Brian Carroll. And my guest today, Liza Adams. She’s the founder of GrowthPath Partners. And she spent 25 years leading GTM teams at companies like Smartsheet, Juniper Networks, and she’s worked with AI and machine learning long before ChatGPT. And now she helps teams figure out how AI can actually change the way they work. Something Liza recently said that stuck with me is you can’t reimagine the future by automating the past. Liza, welcome to the B2B roundtable. Liza Adams (00:50): Hi Brian. I’ve been looking forward to this all week long and it feels like every time you and I get together we’re always laughing. So I’m still kinda laughing over here. So always a pleasure. Brian Carroll (01:02): I’m so glad to have you on today. And it’s funny, I’ve had multiple people tell me, Brian, you should talk with Liza Adams. And it was fun to be able to say, Well, guess what? We’re talking this week. Brian Carroll (01:16): So the question I wanted to ask you first is what’s really separating teams that are changing how they work from teams that are just getting faster? Liza Adams (01:25): Yeah, you know, the biggest aha moment for me is really mindset, right? Like I’ve always said that the cap of what our teams will ever build, do, and use AI for is limited by what they believe it can do. So if we primarily think that this is gonna be just a chatbot or a fancy search engine. Guess what? That’s all we’re ever going to use it for, right? And I do have a lot of empathy because if that’s what we believe, and our companies are expecting us to build fully agentic workflows that cross functions, guess what? There’s a big grand canyon between those two beliefs, right? And that’s just one. You know, there’s also this mindset around AI used for productivity, making existing work go faster. And I actually believe that that should just be the floor of our expectation of AI. Because if we simply make old work go faster, you can almost project how it can automate the human out. But if we actually use AI to push our thinking so that the outputs are better, so better, not just faster, but better. And then better yet, if we actually use AI to do something different, meaning reimagine the work. We now are innovating, do things that weren’t possible before. With innovation, you know, we have a better shot at growing the business. And when the business grows, humans are essential. Right? And I actually can’t see a business continuing to grow without needing more humans. But if we simply improve productivity, then we can see how humans are not as essential to the business. Brian Carroll (03:14): Something I’ve noticed with companies is when they do start using it, and every company has to varying degrees, there’s this AI adoption plateau. And I wanted to talk to you about it because I hadn’t really heard that until our conversation. So what does that look like inside a real company? Liza Adams (03:34): Yeah, a few things come to mind and again, Brian, you and I have talked about this before the show, right? That I don’t have best practices because I do believe best practices are still being written and they’re evolving and they’re moving so quickly and oftentimes the shelf life is relatively short. But what I do have is pattern recognition, having worked with and continuing to work with a lot of go to market teams. So I’ll share with you my thinking on what I’m seeing. Time and time again, and some of these patterns, you know, tell me what generally might work and what generally is going down the wrong way, right? And I think again, the mindset, right? Like what you believe AI can do is the cap of what you will ever build. So if we don’t shift that mindset, there’s a plateau there at some point, right? The other thing is, being able to see what’s possible. So people, I know this so well now, people aren’t stupid. They just need to see what’s possible. I mean we can talk to them till they’re blue in the face, that you can build agentic workflows across functions. And then these agents can use tools, it can use our browsers, it can you know, navigate our systems and our laptops and put files in the folders. But those are features of AI, those are capabilities of AI. We actually have to show them what’s possible, right? So you know show them how it can pulse the market consistently and give us insights 24 by seven and be able to tell us what is still aligning with positioning and what isn’t. Like show them what that looks like, right? Show them how we can use signal from various sources, and those various sources might have lots and lots of data. AI can collect all that, synthesize it, give us insights and anomalies, and determine which customers are about ready to churn, or which customers are giving us enough signal that they’re probably a good candidate for an expansion. So think about those workflows, not just the capabilities. Until they see what’s possible, there’s gonna be a plateau, right? So the whole notion of inspiring people, what’s possible, sharing you know, these use cases, sharing these workflows, everybody doing it, because the ideas are brand new, right? No one’s ever navigated this before. So we need like absolutely the rising tide lifts all boats in many instances. The other place where I’m seeing a plateau is where we do workshops and we do trainings and things like that. So we inspire people, they get going, but then we go back to our day jobs. And what happens is I’ve always said, you know, AI transformation can’t happen when we’re in a hamster wheel. So we actually need to give people the space, the time, the safe space and time to learn, right? Because this isn’t a one and done, do a workshop, do some training, and check mark, you’ve transformed. It doesn’t happen that way. It truly is a change, human change management journey, right? We need to consistently reinforce. You know, people need to keep trying, need to keep using it. And then at some point it becomes a habit, right? It becomes a behavioral change. And unless we have that kind of environment in the company, then I believe that we do hit the plateau again. So I think between those three things, those are roughly the three things that I’m seeing across GoToMarket Teams. Brian Carroll (07:26): Any tips or things you’ve learned about that in terms of that plateau? If someone’s like, I think we’re at a plateau now where they might be able to maybe hit the reset button a little bit. Liza Adams (07:37): Yeah, so this is actually kinda interesting, but I’ve used it on many, many teams now. There is this prevailing perception that AI is primarily a tool. And in a lot of instances, you know, we use it in that way. But if we actually shift the thinking and kind of reframe that a little bit, I generally use the superhero analogies because I love superhero movies like The Avengers or The Justice League, where you have different superheroes working together as a team. Each one has different superpowers or complementary in nature and they overcome each other’s weakness. And then when you bring them together, they basically defeat evil and save the world. In the world of AI and humans, I believe the same thing that humans and AIs have highly complementary superpowers, right? And I’ve given this example time and time again, and I use myself because I have super bad memory, Brian, and you know, as I age, it’s not getting better. I think I killed a lot of brain cells in college drinking beer, and then now it’s just affecting me. Brian Carroll (08:49): Ha ha ha. Liza Adams (08:50): And as a human, I can’t be my best self every day. Like today I’m having a great day, right? But you know, some days I’m overwhelmed, I’m frustrated, I’m overworked, you know, I’m sad or I’m sick, and in those days I can’t be my best self. AI, on the other hand, has super good memory, much, much better memory than I do. And it also is not affected by its environment. It doesn’t care what’s happening around it. It continues to analyze data. It continues to write a blog or whatever we’re asking it to do, right? So in those days where I’m not my best self, AI is helping me overcome those weaknesses. However, on the other hand, AI doesn’t have Liza Adams’ moral compass. Brian Carroll (09:36): That’s right. Liza Adams (09:37): It has Google’s and OpenAI’s and Anthropic’s moral compass, but it doesn’t have mine. It doesn’t understand my passions and my goals. It doesn’t understand my clients’ challenges. So I have to guide it, right? And I have to guide it to align with my intent. You know, AI is a mirror of whoever’s using it, intent. And so, you know, when you think about humans and AIs working together, I really do believe that we can overcome each other’s weaknesses. So I tend to use AI a lot as a sparring partner. Where it’s a thinking partner. It’s not to just validate my thinking or confirm my thoughts, right? It’s actually there. Like I have a digital twin in Claude, and I have a digital twin in ChatGPT. It’s there to actually find my blind spots. It’s there to help me understand different perspectives, how my beliefs might be perceived by others who may not believe in the same things that I do. And it’s there to challenge my beliefs and assumptions. So you know I think when we think about AI in that way, we begin to go outside of what we would normally think. Right? Because now we have more diverse points of view, we’re more empathetic to different kinds of people. And then ultimately the output is a lot better. And I don’t believe that I’m the only one saying this because there’s this American neuroscientist. Her name is Vivienne Ming. And she wrote about this in the Wall Street Journal maybe a couple of months ago. And she did a study of humans using AI. And she determined that humans that use AI as a sparring partner outperformed humans, pure human teams working together, and pure AI teams working together. However, humans that used AI to simply validate their beliefs actually perform at a lower level than an all-AI team. So, Brian Carroll (11:42): Wow. Liza Adams (11:42): because if you’re simply using AI to validate your thoughts, you’re at risk of confirmation bias. And you’re going just down this rat hole, just your belief, right? But when you use it as a sparring partner, it expands the aperture and it allows you to think more deeply about it. Brian Carroll (12:01): I really like that. And I was thinking about even my own experience. That is something I’m like, what am I missing? What didn’t I think about? But a lot of us are using AI individually as that sparring partner. And I was curious, how do you get from the individual getting good at AI to taking the individuals and helping the whole team or organization get better from how the team collectively uses AI? Liza Adams (12:29): Yeah, so back to my superhero analogy and also reimagining work, right? Because I think it will connect us from benefits to just one individual to ultimately benefits across teams and even across functions and organizations. When I think about reimagining work, you know, doing things that weren’t possible before, I start with what was really hard for humans to do. What was hard, what was really expensive, or just really difficult to do manually at scale, right? But then now with AI, those are no longer hard. Those are now historically hard, right? So for example, and I mentioned this earlier, you know continuously pulsing the market 24 by seven. Understanding what competitors are doing, what the analysts are saying, how customer behaviors are changing. Because we constantly need to keep track of ensuring product market fit, right? If all of a sudden the market shifts, you know, in the past we might do that like once a year. Maybe if we’re lucky, we pulse the market quarterly, and the product marketing person looks at what’s happening and has an analysis. Well, things are moving so quickly right now, anything that you made decisions on last quarter is no longer valid, right? But it was hard for humans to go 24 by 7 looking at the market at what the market is doing because we need to sleep. And we also don’t have a lot of humans and don’t have a lot of money to pay those humans to do pulsing the market. So that’s one. So now AI makes that possible, right? The other one is what I mentioned where lots and lots of sources of data. And then there’s lots of data within each source, trying to figure out what all of them are saying to give a signal about the customer. Hey, is this gonna churn? Is this going to be good for expansion? That kind of thing. That’s really hard to do because the human, even our tools today, are not equipped to do it super well. So, but now AI is able to do it, right? Anytime, you know, what’s hard today is like the handoffs between teams. Marketing campaign brief with messaging, handing off to sales with sales enablement, handing off to CS with customer onboarding. Every time you have a handoff across those functions, something falls through the cracks. And then when there’s a change, some of those changes don’t get handed off. So think about the customer experience, right? Customer goes from being served by marketing to sales and then CS. Guess how, it’s like playing a game of telephone. By the time it gets to CS, nothing has been relayed. A very small percentage has been relayed all the way to CS, right? AI, on the other hand, can hold full context end-to-end because it doesn’t care about our silos, it doesn’t care about our functions, doesn’t care about our titles or roles, it only cares about outcomes, and it shares all that data and insights all the way across. So, what was hard for human beings? So the question becomes: is it hard or is it just hard historically? Because I would contend that if we ask that question of our workflows today, a good percentage now we could put in the just historically bucket. And many of the workflows that I just described begins to pull us together, right? It’s no longer just a productivity tool for Brian or Liza. This is now something that impacts marketing, sales, and CS. You know, when we’re pulsing the market, figuring out whether we still have product market fit, guess what? That’s a strategic decision that impacts the entire company, not just the product marketer. When we now begin to see which ones are going to churn or which ones are ready for expansion, that’s not just helping Brian, right? That’s helping the entire organization figure out upsell, cross-sell opportunities. So, you know, I just think there’s so much power in AI that the first place that we need to look at are things that we skipped in the past, because it was hard for us because we’re humans, but now it’s less hard because AI has a different set of superpowers. Brian Carroll (17:08): That is a great takeaway. And the things you talked about are the things that don’t easily show up on the dashboard. It’s the stuff that gets missed we can go deeper in and make it better. Previously a lot of the work was spent on collecting the data. Now we can spend more time sense making. What are we seeing? How can we do that? And that’s the part that I see you talking about this reimagining. Liza Adams (17:31): Yeah, and you know, spot on Brian. AI helps with the connection, AI helps with the synthesis, begins to give us insights that we may not have originally identified, right? But ultimately we are the, we still judge. We make the final call, right? So use AI to help us get all that stuff. But you know, someone told me that in the RACI model, you know, responsible, accountable, consulted and then informed. AI will never have the A. AI will never be accountable, right? That human being will always be accountable. Even if AI did the work, the final judgment is still on us. And I’ve always said, you know, AI will never lose the job for you, it will never pay the fines for you, and it will also never go to jail for you. So Brian Carroll (18:28): Ha ha ha. Liza Adams (18:29): Which I still love because if it did, then why are we here? Right. So Brian Carroll (18:34): That’s right. Liza Adams (18:35): I love the fact that there’s vulnerabilities and AI is imperfect because we are still ultimately accountable. And when we’re ultimately accountable, it forces us to guide AI responsibly the whole way. Brian Carroll (18:48): And a lot of the work that comes through AI could be transformed just by someone signing off and saying I’m accountable for what this says. Because they ultimately are. It’s just that sometimes people skip that step. Liza Adams (19:03): That’s right. That’s right. Brian Carroll (19:05): You touched on this earlier, which is this idea of the organization. So moving from an org chart to more of the work chart, how work’s happening and I wanted to see if you could share how you’ve seen a company actually start working this way. Liza Adams (19:22): Yeah, I hinted a little bit about it already. So org charts, as everybody knows, it’s highly siloed. We’ve got marketing, sales and CS, even in marketing, right? We’ve got digital, we got brand, we’ve got demand gen and field marketing and partner marketing, you name it, right? And then it is also very hierarchical. You’ve got your CMO and then your VPs, directors, managers. AI, in the world of AI, as I mentioned, it doesn’t care. It doesn’t care if you’re CMO or analyst, and it doesn’t care if you’re sales, CS, or marketing. And in fact, there’s the study from Harvard. They took 776 P&G professionals. And they were cross-functional. And when they gave these professionals AI, the observation was that they began to care less about the boundaries of their jobs. Because AI didn’t care, right? Brian Carroll (20:24): Right. Liza Adams (20:25): Yeah, so it only cared about the outcomes. And in fact, I’ve written about this. There’s this woman named Megan. I was with this team for about six months. Megan was the senior director of integrated campaigns and demand generation. So she had a number of agents, AI agents, to help her with campaign strategy, campaign planning, and campaign execution. And then she orchestrated them. And then she’s like, why am I stuck stopping in campaigns because at some point I need to enable sales, right? So she actually created this sales enablement agent. And then she’s like, well, why am I stopping at sales? Because at some point, this product that this campaign is promoting will be sold to a number of customers, and CS will actually have to support that product. So she created this CS onboarding agent. Lo and behold, she is now orchestrating a full go-to-market agentic workflow that goes from marketing, sales, and CS. And the result of this is Megan has essentially worked herself out of her senior director of campaigns job. She is no longer that, she is now the senior director of go-to-market strategy and architecture. Her job is very different today. Like in the past, it was the typical create a campaign brief, bring everybody together, cross-functional team meetings so that everybody aligns on that brief, execute on the assets, look at the campaign performance, determine what needs to be tweaked. Now, what she’s doing, she’s building and training these individual AI agents. She’s guiding them. The agents are doing the work, right? She is judging the work. She’s guiding the insights. Then she’s determining whether or not to shift strategy based on what the agents are finding out. So her work has become more strategic, more judgment focused, more guiding. And more orchestrating now across functions rather than campaign development, launch, execution, and performance management. So that is a very real example of how AI has changed not just the individual, but also the function and the role of that individual. Brian Carroll (22:55): I think that’s something people are gonna wrestle with, especially those who want to hold on to what the org chart was. What you’re just illustrating is that AI enables us to overstep what the org chart is because, like you said, it doesn’t care. And what I love is how she was able to frame this out in a way that it’s solving the problem, which is orchestration, and now moving into that role helping orchestrate. Liza Adams (23:24): Yeah, and you know, the great news about what she did is AI didn’t care about the silos. She didn’t care about the silos. She still worked with a specialist, right? But she didn’t care about the silos. And guess what? The customer doesn’t care about our silos, right? Like in fact they don’t want to know the sausage making and I’ve had some enterprise customers say, I feel like I’m dealing with three companies rather than just one company. Because every time we hand off from marketing to sales to CS it feels like three different companies, right? But now with AI, we have such an opportunity to create that seamless experience all the way across, which really leads to I think AI is making the mechanics a lot easier. I think our biggest challenge now is us. It’s humans, right? We have egos, we have politics, we have ingrained cultures, we have fears and all sorts of things. We also have KPIs that line our pockets very differently. And we’re measured on those KPIs, and they tend to be highly functional in nature, right? And what I’ve just described is outcomes-based. But guess what? We’re still KPI’d in marketing on MQLs. We’re still KPI’d in sales based on closed deals, and we’re KPI’d in CS based on renewals. Brian Carroll (24:50): Mm-hmm. Liza Adams (24:51): We all know that each one of those departments can achieve those goals and the customer might still be dissatisfied. CSAT could still tank because they feel like the experience is not good. It’s kind of like, I love college basketball, the guards being KPI’d on assists. The centers KPI’d on rebounds and the forwards being KPI’d on points. Well, each one of those, you could have rock stars on each one of those and then still fail as a team, right? And an average team could actually be winning because they know how to work together. And they’re KPI’d based on wins, not on individual performances. Same thing in our world. And I think a huge part of this now that AI is making the mechanics a lot easier, we need to almost get out of our own way. And let it happen, right? But I have a lot of empathy, I have a lot of compassion because that is not going to be easy. Brian Carroll (25:52): Something you touched on is just how AI is changing roles. AI is changing what CEOs want from CMOs as an example. And I was wondering if you could speak, one, because you’ve been in that seat, but also you observe it. Like what are they looking for now? Liza Adams (26:10): Yeah, a little bit of a backstory on this one, Brian. You know, my last CMO role, we were acquired by PE, we all turned over and I was like, do I have it in me to do another one? Well, I didn’t have it in me, right? I’m like, I’m old and tired and I think I’m ready for my next chapter. And I’ve always wanted to serve on boards in my post operator role. And I thought that would be a way for me to continue to contribute. And then I found out there are only 41 marketers on Fortune 1000 boards, and less than 3% of all board members have marketing experience. So I’m like, well, it’s not gonna work out for me. The stats aren’t in my favor. And so I dug deeply on why we’re not on boards and many, many reasons, and some of them legitimate, some of them unfounded, but one of the biggest reasons is that we’re perceived to be tacticians rather than strategists, right? Like people see our websites, our ads, our email campaigns and our events, but they don’t see the deep customer understanding, the segmentation, targeting, and positioning, the product market fit, and all those things that have to be in place and our ability to build trust, all of those have to be in place for these tactics to flourish and thrive in market. Right, so a huge part of my passion is really about elevating the strategic value of marketing. AI is not my passion, AI is a means to an end. And you’ve now heard in what I just talked about how AI is making us more strategic, right? It’s not just about the tactics of marketing, we are now in a much better position to be business leaders rather than functional leaders. And that’s now what I’m seeing with some CEOs that I’m working with. They’re not just looking for marketers that are gonna be just the best in their function, right? They’re looking for CMOs that deeply understand the market, bring those insights back into the business so that the business can make strategic decisions that actually impact business outcomes and financials. So, when I say, hey, in the past we weren’t able to pulse the market, this is how we got in trouble as CMOs because we were functional leaders in our board decks, a lot of our stats and a lot of our dashboards were around MQLs and leads and things like that. Well, guess what? That’s like towards the back of the board deck, maybe even in the appendix, right? Because we got marketing tactics in there. But now with AI allowing us to pulse the market and really understand what the market is doing, CEOs actually want to say, Hey, CMO, I want the first three slides of the board deck to be what’s happening in the market. How should we respond and give us the trends and insights? That was super hard before AI because we would have to talk to salespeople, talk to a lot of customers and go talk to a bunch of analysts, but now AI is helping with all that, right? So that’s one thing. We have a seat at the table. The other thing is when I talked about crossing departments. Now we’re delivering seamless customer experience. It’s no longer, well, marketing said we’re gonna be awesome in customer experience. We have all of the collateral says that and there’s some proof points, but that’s not what we experienced as we got handed off to sales and CS. But now marketing with the help of AI can actually bridge those gaps and actually show the other organizations what customers are seeing, right? So now we have the ability to tie into the brand message and actually living it and not just being marketing, like lipstick on the pig, right? Like marketing now has the ability to bring people together and say, here’s the expectation, but here’s what they’re experiencing as a result of the handoffs between these departments. So there’s just lots of things like, and then the other one is the upsell, the cross sell, right? That was hard to do. And then now we are actually being able to improve retention. Like I think rather than MQLs, closed deals and renewals, or in addition to those, we need to think about customer-based outcomes like time to value and CSAT and net retention rate. Right. If we now align to that and the CMO is able to peg on those things, we have a much better shot of getting a real seat at the table and being more strategic and impacting the business outcomes. Brian Carroll (31:13): I love what you’re saying because what I’ve heard from CMOs is they feel like I’m being held accountable for things I don’t control. And as much as they spend time with the marketing team, they need to do it with the executive team. Liza Adams (31:24): Well, here’s the challenge. I think it is only part of the answer. Because it takes two to tango. Right? Like, we can expect the CMO to do these things, but if the environment doesn’t allow the CMO to do that, we don’t allow the CMO to bring people together, right? We don’t allow the CMO to go outside of their function to actually help bridge the gaps. Not necessarily land grab and do everything, but be a facilitator of bringing people together, it’s not gonna work. Right? So, there’s the mechanics, but there’s also the culture. And there are also CEOs that want to continue just putting marketing in a functional role. It’s fine, right? And I also know some CMOs that don’t want to be a GM. They love the craft of marketing and they just want to be the best of the best in their function. And I also respect that, right? So this is really about fit. You bring in a CEO that wants a functional leader, a marketer that wants to be a functional leader, that’s gonna gel. But you’ve got a CEO that wants a GM and a CMO that’s a functional leader, that’s never gonna connect, right? Like we need the two of them to align. Brian Carroll (32:43): Exactly. Brian Carroll (32:47): And I think that’s partly, CMOs need to be doing the due diligence to talk to the CEO executive team. What are your expectations of marketing? What are the things we’re gonna use to measure success in the interim as we’re setting things up, correct? Liza Adams (33:00): Yeah. And you know, if I was still doing the CMO thing and I was in transition and looking for a job, one of my questions would be, Hey, can I see a board deck? And I just wanna see where the marketing slides are. If they’re not there or in the appendix, we’re in trouble. Right. So that’s just like one of the litmus tests that I have. But I also do have a lot of empathy because it’s not easy to find the CEOs that think about marketing in that way, right? And depending on where we are in our career journey and our stability in our career and financially, sometimes we are more tolerant of the disconnects because we still have to put food on the table, roofs over children’s heads, right? So, I’m not here to say you must do this, you must do that, because we all are in different different situations and I’ve been there and I’m empathetic to wherever people are in this journey. Brian Carroll (34:03): Yeah, and I am as well, and I think you’ve shared so much. As I’m listening to you, we started out with this idea of not just automating the past, and that we need to be thinking about the future. And I was wondering if you could share a recent story or someone where you’ve seen a team actually reimagine the work. Liza Adams (34:25): So Megan is a perfect example of that, right? She reimagined the work and then she reimagined her role and now that company is reimagining the org chart. Which actually leads me to what many have asked me. They say, Hey Liza, what does the org chart of the future look like? I’m like, my gosh. Brian Carroll (34:49): Ha ha ha ha. Liza Adams (34:50): Question. You know, if I had the answer to that, you guys need to be paying me more money. Brian Carroll (34:57): Ha ha ha. Liza Adams (34:58): And I actually believe, based on pattern recognition, I actually believe that it’s backwards. Like if we start with what does the org of the future look like? Let’s reimagine the org of the future. I’m like, hmm, well, that feels strange to me because you know, I love watching, Brian, I love watching HGTV like Property Brothers or Joanna Gaines and you know how they love Brian Carroll (35:25): I love those shows, yeah. Liza Adams (35:26): those shows, okay, like where they remodel the home, they can come in and just like reimagine them, right? But I think if you’re a designer and you just come into a home and you’re like, this kitchen, it needs like a pet station where the dogs can eat and we need some disability rails and things like that. But we don’t design it for the family and we don’t understand how the family’s lifestyle is and we don’t know who’s gonna live there, then they may not have pets. They may not have anyone disabled. Or the other analogy is like, it’s like hiring a bunch of actors before you even know what the script is, right? So my challenge to go to market leaders is rather than thinking about what the org of the future looks like, and I bet you the orgs are going to be different by company and by function. All right, and I’ll explain why. Start with reimagining the work first, right? When we reimagine the work, then we figure out what the roles need to look like in that reimagined work. When we understand the new roles, then we can create the org chart. Versus creating the org chart and working backwards, right? It’s like work first and then go to the org chart. And the decisions along the way will vary because our goals are different, our existing expertise with the people who we have are different, the cultures are different, the budget is different, right? Some people have budget to build these tools on their own, and they’re going to replace the SaaS platforms that they have. Well, if that’s the case, the org’s gonna be different, the roles are going to be different, right? So there’s all of these considerations when we think about the reimagination of the work that have, in my opinion, trickled down to the roles and then ultimately the organization. Brian Carroll (37:29): Well Liza, I’ve loved our conversation. I wanted to say it’s been so great having you on. Thank you. Liza Adams (37:35): Thank you so much. This has been so fun and you’re asking all the right questions and thank you for giving me the opportunity to share. Brian Carroll (37:42): Well, we’re glad to have you again and thanks to everyone who’s listening to the B2B Round table. We’ll look forward to seeing you next time.

3. 

   18 Aug 2026

   AI Scaled Activity. It Didn’t Scale Relevance with Craig Rosenberg

   For years, B2B teams tried to make SDRs more efficient. More calls. More emails. More activity. Then AI arrived, and many teams tried to automate the same model. But what if the problem wasn’t needing a faster version of the old playbook? What if the real opportunity is to use AI to make people better at the things only humans can do? That’s the question behind my conversation with Craig Rosenberg. Craig has been gathering some of the best SDR and pipeline leaders in B2B through Scale Venture Partners’ Pipeline Council. What he’s seeing feels less like a completely new playbook and more like a return to fundamentals, with much better tools. AI can help us choose the right accounts, recognize signals, research buyers, practice conversations, and move faster. But the last mile still comes down to relevance, judgment, taste, trust, and human connection. About this episode Craig and I have known each other since the early days of B2B marketing and demand generation. I followed his Funnelholic blog back in 2008, and he reminded me during our conversation that my book, Lead Generation for the Complex Sale (https://www.amazon.com/dp/0071458972), was one of the first B2B GTM books he read. Several things Craig had recently been sharing from Scale’s Pipeline Council brought us back together. One of the big questions they’re working through is simple: What does a high-performing SDR motion look like now that AI can do so much of the work SDRs used to do? The answer isn’t fewer humans everywhere. In fact, Craig is seeing AI companies hiring SDRs and experienced enterprise sellers as they move beyond product-led growth and into harder-to-reach markets. Craig and I discuss: Why automating the old activity-based SDR model didn’t solve the pipeline problem How Glean uses AI to help SDRs get better at human conversations Why Craig believes the “last mile” of selling is still human What unmistakably human outreach looks like when buyers are surrounded by AI-generated messages Why AI companies are hiring SDRs and experienced enterprise sellers again How ICP and signals help teams focus on the accounts most likely to buy Why selling AI is becoming harder and business process may become the new software moat About Craig Rosenberg Craig Rosenberg is Chief Platform Officer at Scale Venture Partners, where he helps build and lead Scale’s go-to-market platform for software companies. Before joining Scale, Craig was Distinguished Vice President in Gartner’s sales practice. He joined Gartner through its acquisition of TOPO, the research and advisory firm he co-founded. Long before that, many B2B marketers and sales leaders knew Craig as the Funnelholic, where he built a following writing and speaking about demand generation, sales development, and B2B go-to-market strategy. He also co-hosts The Transaction podcast with Matt Amundson. Connect with Craig Craig Rosenberg on LinkedIn (https://www.linkedin.com/in/craigrosenberg/) Scale Venture Partners (https://www.scalevp.com/) The Transaction podcast (https://thetransactionpod.com/) Chapters 00:00 What Top SDR Leaders Are Figuring Out 04:41 How Glean Uses AI to Make SDRs Better on the Phone 09:09 The Last Mile Is Human 12:46 Why AI Companies Are Hiring SDRs Again 15:33 What Does “Unmistakably Human” Look Like? 22:06 Why Enterprise Prospecting Shouldn’t Always Scale 23:36 ICP, Signals and Choosing the Right Accounts 25:25 Why Selling AI Is Getting Harder A few things worth taking away The old SDR model treated people like “human robots.” Automating the same activity-heavy motion with AI didn’t solve the underlying problem of relevance. The better teams are using AI to prepare humans, not replace them. At Glean, AI supports account selection, research, signals, and practice while SDRs focus on getting better at live conversations. The last mile is still human. AI can provide information and suggestions, but judgment, taste, relevance, trust, and relationship building still require people. Being unmistakably human sometimes means admitting what you don’t know. AI can help you understand a buyer’s situation, but it shouldn’t create expertise or experience you don’t actually have. AI companies are hiring SDRs and experienced sellers as they move beyond product-led growth into enterprise markets. As Craig put it, “The minute you want to talk to people that aren’t coming to you, you need people.” ICP matters more when data is abundant. Craig shared an example where ICP opportunities converted at 37% compared with 17% outside the ICP. Signals then help determine when to reach out and what may matter. AI is also changing software competition. As products become easier to build and replace, Craig believes companies need to expand from TAM to “Total Available Problem” and become deeply embedded in customer workflows and business processes. A few lines that stuck with me “The reality is the most important thing now is trust building, humanity and relationship building.” “It’s that last mile, which is the human.” “The minute you want to talk to people that aren’t coming to you, you need people.” “Getting into AT&T doesn’t scale.” “There are accounts that are the absolute best fit for you right now. Why would we spend time on anything else?” “We’ve moved from TAM to TAP, which is Total Available Problem.” Listen and subscribe Subscribe to The B2B Roundtable (https://www.markempa.com/b2bpodcast/) wherever you listen to podcasts. Transcript Brian Carroll: Welcome to The B2B Roundtable. I’m Brian Carroll, and I’m excited to have our guest today, Craig Rosenberg. Craig is the Chief Platform Officer at Scale Venture Partners. What Craig’s doing is helping them build their go-to-market platform so that they can bring this expertise to help software companies drive growth. I’ve known Craig quite a while. We go way back in terms of what we were doing in the early days of B2B marketing and complex sales. I started following Craig’s blog, The Funnelholic, going all the way back to 2008. Craig first shared a Pipeline Council they’re doing with some of the top SDR leaders in enterprise and software sales. And then Craig did a post with Jason Vargas talking about the “taste layer” and bringing that to the SDR rep. What I’m excited about, Craig, for us to talk about is, you know, the more things change, the more they are the same. What’s coming up in the Pipeline Council that the rest of us aren’t talking about yet? Craig Rosenberg: Well, first I thought it would be important for the audience to know that, yes, you found me through The Funnelholic, but everyone found you through your book. Was it Lead Generation for the Complex Sale, I think was the name? Brian Carroll: Yeah, yeah, it was. Craig Rosenberg: And that was like the book. I mean, Brian, you were the OG out there with the book and talking about it. So I think that’s amazing to bring up. And even the fact that you brought me here because you saw these posts, for everyone who’s wondering if it’s important for you to share what you’re working on and thinking about on social, I mean, look, that’s how I met Brian in the first place. He had a book and was doing the speaking circuit. I had a blog. And then recently, he brought me back here after he read one of my posts on social. So there is a lesson in your intro in and of itself. Brian Carroll: That is true. And you also do a podcast, which is awesome. Craig Rosenberg: Thank you. Brian Carroll: So let’s go back to what’s coming up in the Pipeline Council that the rest of us aren’t talking about. Craig Rosenberg: I have two councils. I’ve got one where I brought together the folks that have figured it out. I’ll talk about that in a second. Then I’ve got my regular councils, which bring together people who are still trying to sort this out. Brian, from our conversation before, I’ll just go on the negative side. There was a moment where SDRs were basically human robots, right? They were basically conveyor belts of information. It was about how many emails could you get out, in some cases how many calls, and then the messaging was sort of one message. It was all about output. Or I think you said they were activity-based, right? They were machines. So we had that moment. We had to come out of that and sort of accept that the original iteration of AI here, and the way people thought AI would work, would be to somehow automate that motion, which was a highly generic, activity-based motion. We had this run of SDRs being these human robots and delivering activity. And frankly, let’s face it, they got meetings. Then everything changed and it got really hard. Then we said, “Well, we’re going to solve it by using AI to deliver what they were doing as robots,” and that didn’t work. Everything got really confusing. That’s why I put the Pipeline Council together at the Rosewood, so I could start learning more. I work with a woman named Christina McMillan, who I’ve worked with for years. She was at TOPO with me, but she was an SDR consultant for years. I said, “You know what? We don’t know anymore. We’ve got to go figure this out.” So we bring together the Pipeline Council, and it’s really interesting because we actually do know. The reality is the most important thing now is trust building, right? Humanity and relationship building. What we missed for, call it eight or ten years, was that, because we didn’t need it. Now, the truth is, from watching you, reading you, and listening to you for a long time, you would say, “Wait a minute. That’s what I was talking about back then.” But the truth is, I think we kind of lost sight of that. There were some really interesting things I learned from the Pipeline Council. I’ll give you an example. This guy Joey Lopez, he’s at Glean, and this guy amazed me. So I’m just going to give you this example of what he does. Most everything is AI and automated. Who they’re going to talk to, what types of companies, those things are served to them. Because, by the way, Brian, one of the things that was also happening during the SDR-as-robots phase was they were choosing their own accounts. They were going into ZoomInfo and just downloading names and sending emails. There was no thought process on who we should talk to. The AI will research the company, help them identify both educational information and signals. The AI actually sends emails for them. What he believes is: Can I focus on one thing? His choice is to focus on the phone, which is a highly converting channel for them. So they train and they practice this all the time. But ready for this? He’s a football, wrestling guy. Every day the SDRs come in and they huddle like a sports team. He’s like, “Look, you don’t just practice before the game. You get in the locker room and you go through the game plan.” But they actually practice. Let’s say that day they’re going to call CIOs. They all get trained on the CIO persona: what they care about, what their challenges are, day in the life. They get trained on the type of messaging that works under different scenarios. Then they go practice. Then they come back and huddle. Then they all spend the whole day calling CIOs, and that’s it. Then they optimize against it. It is just brilliant, right? Brian Carroll: It is brilliant. Craig Rosenberg: I’ve never heard anything like it. I told him, “Look, that is better than what me and Brian used to do.” In the practice, they’re using sales simulations where they can practice against the CIO persona, which is AI. Everyone asks me, and I’m like, look, I’m in a venture firm. We love AI. But it’s that last mile, which is the human, which is the thing that we’re learning. Brian Carroll: That’s right. Craig Rosenberg: He trains them on the human, and they go in and have these conversations. Then they listen to calls together, maybe like a halftime, and they optimize. That day, they just do really well with that type of person. I thought that blew my mind. It was incredible. The other things I saw were highly personalized direct mail. There are these groups where they’ll actually create custom gifts for someone based on what they care about. An example would be, if developers have a high predisposition for Legos, there are groups that do personalized Legos. Or they might know someone is way into archery, so they’d send them something around archery. It was these highly personalized gifts. And the conversion rates are the most important thing. We have to live by the numbers, even if it’s a great idea. Sometimes I have a great idea every week that doesn’t work. Brian Carroll: Sure. I mean, that’s part of life. Craig Rosenberg: Now that we’re our age, we can relate to this. But the conversion rates are really high. Everyone says, “Well, that’s a gimmick.” No, it’s not a gimmick. It’s personalized. If you send me a stress ball, that’s not going to work. Brian Carroll: Mm-hmm. Craig Rosenberg: But if you show me that you know me, then that’s going to be infinitely more effective. The other thing that was surprising to me was there was a guy in cybersecurity, which is one of the hardest markets to email, and he improved email reply rates to 6%. We haven’t seen 6% since 2021. What he did, again, was make the emails more relevant, more personalized. He tore everything down and rebuilt it in a way that was more highly relevant and highly personalized. So if I had to leave a theme, there are some really fun channels and tactics that I learned about, but at the end of the day, I think the key is that last mile. And I think that’s what leads you probably into the taste layer. Everyone wants to know what humans are going to do. Well, the humans are there to make sure that we’re building a relationship, that we’re being relevant, that this is something tasteful that we would send to someone. That’s what we saw. We went around the table, and that’s where we learned all those things. That Joey Lopez example, what do you think of that? That was incredible. Brian Carroll: I love that. Going back, Joey took it to another level. When I was running BDR teams, I created something I called “How to Talk to Me,” which was doing what Joey was doing. But with the role-play, we didn’t have AI to do role-play. It was our best educated guess on a persona. We did focus on just calling that persona because people would be reaching into multiple people within an organization. I just think getting that level of specialization matters. In sports, you need to get reps in, but they were practicing the reps before they talked to a live person. Then they were able to go deep, which I think is brilliant, because that’s how people get good: having that focus, having the understanding. It also helps younger, less experienced people who haven’t had the life experience, maybe calling an executive, to actually know how to talk to them. Craig Rosenberg: Yeah, for sure. By the way, one thing on the experience-versus-not thing. It’s a challenge because we do typically use less experienced SDRs in this process. But, on the other hand, it was interesting. We had a really successful leader. He’s not allowed me to talk about who he is ever. It’s a long story. He’s got a highly successful SDR team that’s scaling, let’s say, a hundred. Remember when everyone told us they were dead? Brian Carroll: Yeah. Craig Rosenberg: His issue with the experienced folks is that they couldn’t approach the buyer the way he wanted to, which was in a much more personalized way. If you think about it, if someone was highly successful during the SDR robot phase, are they really more experienced? I don’t know. Brian Carroll: Really, they aren’t. They’re experienced being repetitive and doing activity. But when it comes to actually connecting with people and being relevant, that’s something you need to train. It’s a skill. It’s something people need to develop, and it doesn’t just happen. Craig Rosenberg: Yeah, for sure. I was going through the numbers everyone was giving me. I’m like, “Who’s hiring?” Everyone raised their hand. It’s nuts because everyone told me SDRs were dead. Brian, I think we’ve seen this before, though. There was a moment where everyone tried to kill the SDRs. They keep trying to kill the enterprise sales reps, saying, “No, those old guys, they don’t know anything.” And now they’re getting hired at prices where, I mean, they’re unaffordable. But it’s the same thing. It’s your same theme. You need AI to help everything go faster for the human, but at the end of the day, that relationship is built with these people. We’re seeing that across the board. These AI companies came up through PLG. Some get to a billion without hiring go-to-market. But guess what? The minute you want to talk to people that aren’t coming to you, you need people. Brian Carroll: That’s right. You had shared something, I think this came from Adam Schoenfeld, about 39%, and maybe it’s higher, of AI companies hiring SDRs. Everyone thought these companies were building the technology that’s supposed to replace SDRs, supposed to replace salespeople, but they’re still hiring. So what do you make of this? Craig Rosenberg: First of all, you are right. It’s probably higher because that was six months ago when Adam did that. He looked at 150, I think a little more, top AI companies. Thirty-nine percent were hiring SDRs and SDR leaders. A year ago, I was talking to experienced SDR leaders who were crying because they weren’t going to hit their mortgage. Now they’re getting paid more than they ever did. Those top AI companies, frankly, look, I’m in venture, but you see their numbers. It’s extraordinary. They’re doing it by people catching fire from a brand perspective very early on, people coming to them, and typically a PLG motion. I’m all in favor of that. What we’re seeing now is that whole cohort is trying to get into enterprises, new markets, even mid-market that didn’t necessarily come to them. At a certain point, you have to do this. And they’re not just hiring SDRs. They’re hiring, like I said, experienced sales reps that were supposedly dinosaurs and out of the business. The second thing, though, is what we just talked about. I actually do believe there was a moment where SDR leaders were running the same playbook and they failed. Then they went to the next place and they failed. So in defense of the sort of fall of the SDR, the SDR leaders had not adjusted. Now they’ve adjusted, and now you’re seeing folks starting to share successful implementations. It was a return to humanity in many cases. But I will say AI is predominant in their systems and how they cue everything up. There’s the ability to provide information SDRs have never had before, the ability to give them both educational information and signals that tell them when to reach out to someone and how to be relevant. Those things are real. The fact is, what we need is that last mile to be people. That has been the breakthrough. Brian Carroll: You’ve said this a couple of times, bringing humanity back. What would you say “unmistakably human” looks like now, today? Craig Rosenberg: Man, that’s a really good question. Brian Carroll: I read probably a dozen things on LinkedIn where someone’s saying, “How not to sound like you wrote by AI.” And I’m like, why not try writing? Why not try actually writing yourself in your voice? Because there’s a backlash happening too, you know. Craig Rosenberg: Yeah. I know. You’re right. I think there have been two moments that turned people off to generic messaging. There were SDRs as robots just flaming the market with emails. Then there was, like we said, “Well, we could solve this with AI.” Even today, I got emails this morning that were clearly not written by a human. We’re surrounded by AI messaging all over the place. And so when we get a human, that’s something that’s really relatable. I’ll give you an example. You said try writing. I use AI every day. I originally tried to have AI write emails to folks, and then I said, “Okay, well, that doesn’t work.” Then someone said, “Well, it’s easier to be an editor.” And I used to say that. Then I tried editing it, and it was too hard. So I went the other way. I use AI, let’s say I’m prospecting, to tell me what kinds of things work. It can help me with the structure or the rubric of an email. What types of things work in the first sentence? Stuff we train on. It can look and say, “Hey, the best reps are doing this at the top.” That helps me a lot. I ask it for ideas in bullets. That’s my new thing. I get these great ideas, but then I write it. So I’m still faster, but more importantly, I’m better. AI does help me a lot, but I just couldn’t have it write it anymore. If it’s AI-patterned or templated, it just won’t work. I’ll give you an example of humanity. I was just talking to John Barrows, and he said, well, a young SDR gets this signal about a merger. He’s never seen a merger before, and he goes and writes about it. I’m like, “Dude, you can’t do that. I’m not going to answer.” So it’s like, you want to use AI? Well, tell me what happens in a merger. Tell me what things might be happening at this organization. Now I’m going to take it and write something more heartfelt. I might have even written, “You know what? I don’t know a ton about what happens in mergers. But I do know, just having experienced this, that this, that, and the other might be happening in your business. And that’s why I feel like we might have the ability to have a conversation about this use case.” Just being humble and approaching it that way might have worked. The other way is to do your own research and be okay with not being perfect. I thought that was a really good example from him because that would be an example where we’d use tech. We’d say, “It’ll identify if there’s a merger, then it’ll put together a message.” It’s like, yeah, but that person got 200 messages that all look the same. That shows zero understanding of that person and what they might be going through. So what’s your differentiator? How are you going to do it? I think when we talk about humanity, we have to be able to tell the buyer, “Look, it’s worth talking to me.” And that actually has to be done by you, the person. It’s one of the reasons I’m surprised people answer their phones, because I certainly don’t. But we’re seeing the data, and it does work. It works when you connect because ultimately that’s two humans connecting, having a conversation, and being able to talk it through, which says, “No, I’m not talking to a robot.” Brian Carroll: Yeah, and I think there is a lot to what you’re saying. My first job as an SDR, I was calling to set up appointments for sales training. My first day, I knew nothing about sales. I was frustrated in the week, and Julie, the manager, said, “Brian, just be people with people. Why not own the fact? You’re 22 years old. You don’t know anything about sales. And the irony is you’re setting up appointments for sales training.” The point being, the admission of who you are and what you don’t know can open up possibilities. I could talk about, “I’ve learned so much in the sales training already.” I think there’s this point that we still need to go back and learn what is unmistakably human and do more of that. I wanted to go back to when you did the meeting at the Rosewood. Was there anything that surprised you the most or was counterintuitive that you came away with? Craig Rosenberg: Counterintuitive? Well, I actually would say the most surprising thing was that I wasn’t surprised. I mean, that’s cheating, but I think everything ended in the same theme that we just discussed. I’m surprised people still answer their phones. They do. There’s tech to go do that. By the time we got to, let’s say there were 12 people in the room, when we got to number four, I was like, “I got it.” Then they kept going, and I’m like, “I still got it.” I’ll give you another one that was big. The SDR thing kind of blew up a year and a half ago. Now it’s back, and it’s like, what were the things that we forgot? Well, one, they want to get promoted. One of the people in the room was like, “One of my keys is that I have about 70% of my SDRs get promoted into sales.” I’m like, “Okay, that’s amazing.” And she’s like, “Now more talented people come. They stay longer because they know they’re going to move up.” I was like, my gosh, that’s an old theme that’s come back. Maybe the thing to say is that what’s old is new again. A lot of the fundamental things that we used to discuss with SDR team building, that I kind of forgot about, came back. Brian Carroll: AI has allowed us to scale activity. It hasn’t allowed us to scale relevancy unless you use it properly. Craig Rosenberg: Yeah. I actually do have a fun one for you. Brian Carroll: Okay. Craig Rosenberg: A fun one and one that we already knew, but is really important. The fun one did not come from the Pipeline Council. I like to just talk to people. These hot companies that are sort of breaking down doors, I just want to talk to whoever’s doing it. There’s a company in New York called Attention, and one of their highest-converting channels is the SDR taking a gift and walking in the doors of their target account. Brian Carroll: Wild. Craig Rosenberg: So I called him. He’s like, “Yeah, it’s the field SDR.” They also get a LinkedIn message saying, “Hey, the Attention guys just brought that.” It’s that motion because, guess what? We give donuts. It has our name on it. Or we could give whatever. But the fact that we made that personal effort, having the person who’s trying to reach out to someone show up at the admin’s desk and hand them that, that’s the ultimate in conversion. Now, you can’t scale that. But look, you and I, you’re the complex sale guy. I’m the enterprise guy. I keep telling people, guess what? Getting into AT&T doesn’t scale. You have to find your way in, then find your way across, and continue to do that. That was a surprising channel for me and really interesting. The other thing, though, that I did not mention before, that people are doing a lot better across the board, is ideal customer profile work. I knew this at TOPO, and people didn’t believe me because everything was about meetings. They didn’t care what. I kept saying, “Forget the term account-based marketing. Don’t worry about it. The most important thing is there are accounts that are the absolute best fit for you right now. Why would we spend time on anything else?” It was funny. When I’d go in and they’d say, “Can I look at the forecast?” I’d say, “Well, let’s run it against the ICP.” It was obvious. You’re getting a 37% conversion rate against the ICP and 17% against other accounts. That should tell you everything. What we see now, with data and the ability to do this, is that a lot of these successful teams are doing a way better job of choosing the accounts. The second part is, with signals and these things, you’re able to figure out when to reach out to them and what to say. Those two breakthroughs are huge. Brian Carroll: Yeah, and I think back, you brought up my book. By the way, it’s coming up on 20 years since that book came out. Craig Rosenberg: No way. I’m getting old, man. Brian Carroll: Yeah, I can’t believe it either. So 20 years ago, in 2006, there wasn’t an abundance of data. We now have an overabundance of data. It’s: What do we do with it? We can move from thinking ICP is how you build a list to, no, your ICP is how you know who’s relevant, and you focus on just those. You aren’t trying to build the biggest list possible. You’re trying to build the most relevant list. It makes perfect sense. Craig Rosenberg: Yeah, I know. Brian Carroll: What are you seeing right now, as you look across your portfolio, that a lot of us might miss? Craig Rosenberg: Well, I’d say to everyone, you’ve got to stop firing your CMO just because things are tough out there. The movement there has been extraordinary in terms of people getting shipped out. There is a point there, which is messaging matters. I think it’s really hard right now. It’s been a killer. CMOs who are pretty good are fighting with the organization, trying to find the best message and not getting there. Look, I work with startups, and it’s hard to run marketing at startups. It’s really hard. The good news is everyone wants to talk about AI. The bad news is everyone’s selling AI. AI is not the same as SaaS. Everyone says, “Well, yeah it is.” No, because SaaS you could load it and go. AI has to integrate with your data. That’s why you see this sort of forward-deployed engineer thing. To really understand it, you have to be able to get it in and get your data moving through the system. So it’s different. If you think about it, everyone’s pitching AI. Everyone knows they need to go to AI, but now everyone’s afraid of it. There’s also a whole naysayer element in the buying committee that makes it even harder. But more importantly, there are so many more products out there. You’re selling into your category, where there may be 35 other companies. Then you have horizontal AI companies like OpenAI and Anthropic coming at you from the other side. You’ve got other AI companies coming in and tangentially touching your message and your value proposition. That makes the ability to distinguish yourself really hard. Here’s the big thing. For AI companies, many of them come into the market as a wedge. They found a hole in the market and they filled that hole. In the SaaS era, if you found that wedge, you would be able to run with that wedge, go raise lots of money, and dominate by focusing on that wedge. Now you can’t, because it’s too easy to make software and it’s too inexpensive. We like to joke that four kids in Brooklyn will create your product in a month and be coming at you. If you sit on that wedge now, you’re actually asking to get flanked. That’s an incredible challenge. A company today has to go in via its wedge, and then the things that used to happen eight years after a company existed, you have to do now. We have an investor here who said we’ve moved from TAM, looking at the biggest market, to TAP, which is Total Available Problem. We have to expand the problem set as fast as we can. Brian Carroll: Wow. Craig Rosenberg: The other thing is moating. Moats are really hard because, like I said, it’s the same problem. Building software is easier than before. Then you’ve got the threat of the frontier labs. Anthropic can take you out in a night and not even know you existed. Your moat now is integrating yourself into business processes and workflows as fast as you can, because that makes you harder to pull out. It’s funny because everyone’s talking about CRM and whether there are new CRMs. Except the reason SAP and Salesforce don’t die is because they become the business process. Tearing them out means you’re tearing down your entire business process. Everyone thinks it’s the data. Data moves now. You can move data in less than a day. It’s actually the business process. There’s a lot to learn there for these companies. The faster you can become integrated into their business process and become the business process, the stickier you are and the bigger your moat can be. But if you don’t do that, then you’re easily replaceable. I talked to a RevOps leader I’ve respected and known for years. He said, “We look at our tech stack every month, and we’ll tear stuff out every three months.” I’m going, “Is that good?” He’s like, “Yeah, because guess what? I can always look at what’s better.” Ripping and replacing is actually not that hard unless they’re dug into my business. Those are things I think people may not know about that are really important to take in and think about. How you sell, how you message, what you do in the sales process, and what you do in the post-sales process are different. There are big challenges today. There are different approaches to how you think about things. If I had to give you anything that I’ve learned, that’s more of what I’ve learned from the investors looking at the market that I’ve found fascinating. Brian Carroll: Well, Craig, I just want to say thanks for the conversation today. It’s been so great catching up with you and hearing your perspective. The more I listen to you, the more I’m remembering how aligned we are in so many ways. So I just want to say thanks for joining us and being on the show today. Craig Rosenberg: Yeah, thanks for having me. It’s great to see you and talk to you again. I’m going to have to flip through your book again. That was one of the first B2B go-to-market books I ever read. So it’s really cool to catch up.

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