Jody Geiger on this episode
Jody Geiger, co-founder of AI Sales Studio at GTM Shift and revenue leader with 20 years at companies like Apple, Galvanize, and Rogers, brings a systems-first perspective to building go-to-market organizations in the AI era. In this episode, Geiger challenges the assumption that buying AI tools solves business problems, arguing instead that too many teams chase speed before trust and automate busy work without understanding the system beneath it. The core insight is simple but often missed: AI can automate repetitive tasks and scale good processes, but it cannot automate judgment, empathy, or curiosity—the human qualities that actually win deals and drive revenue growth. Rather than starting with tools, Geiger outlines a discovery-driven framework: find friction in your workflows, audit at the click level to understand how work gets done, capture customer language and insights from every interaction, and build a business case before implementing. The episode walks through practical examples from Clue, where an eight-hour manual demo setup was reduced to under two minutes and 75 cents per token using workflow automation, and where a one-click personalized outbound email system eliminated hours of copying, pasting, and context switching. Throughout, Geiger emphasizes that successful AI implementation depends on lightweight systems that create space for thinking, strong change management across connected teams (enablement, RevOps, finance, people), and leadership that views this era as fundamentally new—one where no one has been a CRO or GTM leader before, and old playbooks no longer apply.
What we cover in this episode
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3:35
Building GTM Orgs from Scratch How past eras (PLG, RevOps) shaped current thinking, and why lightweight systems centered on clarity, trust, and rhythm beat tool-heavy approaches.
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8:05
Skills for High-Performing Revenue Teams Curiosity, process discipline, and the ability to make unscalable things (customer language, deep insights) repeatable and credible.
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9:29
Scaling the Unscalable Differentiator How to capture customer language and insights from every interaction without asking for more time; building systems that extract knowledge from existing moments.
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16:05
AI Sales Studio Origin and Model Co-founded with James Kekis to help teams navigate AI-driven change; teaches workshops on systems thinking and runs advisory engagements with go-to-market teams.
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18:28
Best Use Cases for AI Implementation Focus on repeatable, manual, high-effort tasks; AI makes good reps faster but humans coach, create, and improve systems using judgment and curiosity.
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22:21
Demo Automation First Win Eight-hour manual demo environment setup reduced to under two minutes and 75 cents per token using Clay, Zapier, and Slack workflow automation.
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26:37
Streamlining Outbound Email with AI Replaced manual research, drafting, and multi-tool workflow with one-click personalized emails in HubSpot using Clay, prompts, and Outreach integration.
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29:51
Teaching AI Implementation via Workshops Live cohort-based workshops mixing sellers, enablement, L&D, and leadership to embed systems mindset and hands-on workflow design skills.
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33:14
Behaviors of AI-Enabled Elite Sellers Same habits as elite sellers: own your system, repeat it obsessively, understand inputs and outputs, and experiment iteratively to optimize.
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36:00
Framework for Tying AI to Pipeline and Productivity Find friction, do discovery, audit workflows at click level, build a one-page business case with before/after metrics, and rally the team around it.
The lines worth sharing
AI can automate busy work, but it's not going to automate judgment. It's not going to automate empathy. It's not going to automate curiosity. And those things win deals.
Jody Geiger · 1:30
So many teams out there are starting with tools thinking a point solution AI tool will solve something that's broken. But it's not just a tool. It's the people, it's the process, it's understanding and designing a system.
Jody Geiger · 8:20
Context beats content. It's the ability to offer insights and interpretation for our customers. It's the ability to connect the dots that allows us to do unscalable work early so we can build something scalable later.
Jody Geiger · 11:45
No one's been a CRO in 2026 before. All the playbooks we've had leading up to this moment are not going to be the way things get done anymore.
James Kekis (via Jody) · 35:10
Common questions from this episode
How should go-to-market leaders start implementing AI without chasing speed before trust?
Start by finding friction in your system, do discovery like a salesperson would, audit workflows at the click level to understand baseline cost and impact, and build a one-page business case with before-and-after metrics before implementing any tool.
What are the best use cases for AI in go-to-market operations?
Focus on repeatable, manual, high-effort tasks that take time and resources but don't require human judgment or creativity. AI can make good reps faster, but humans must coach, create systems, and use judgment to improve them.
How do you capture customer insights and language without asking customers for more time?
Build systems that extract insights from interactions already happening: website clicks, webinar attendance, cold calls, discovery calls, emails, and onboarding data. Use AI to parse these sources and surface language for use across messaging and sales workflows.
What behaviors separate AI-enabled elite sellers from average performers?
Elite sellers own a repeatable system, understand their inputs and outputs deeply, experiment iteratively to optimize, and create space for their team to try new workflows and learn collectively from wins and mistakes.
Why is change management and team alignment critical to AI success?
AI tools only succeed when leadership is all-in, teams understand why change matters, enablement and RevOps are involved in design, and sellers feel ownership of the new system because they helped build it.
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Read the full transcript · 40 KB · Jody Geiger
JODY GEIGERI'm looking at systems that allow individual contributors or managers the space to think, right? Not just click and not have context. I want them to turn their brains on. And I think AI can automate busy work, but it really isn't going to automate. It can augment, but it's not going to automate judgment. Welcome to go-to-market science. There's an art and
SPEAKER_04there's a science to go-to-market. And in this podcast, we talk about the science by interviewing CROs, private equity investors, and other sales and marketing experts, as well as talking about what we learn every day in the trenches helping to build go-to-market engines.
SPEAKER_07Welcome back. My name is Rachel Buchert. I'm the marketing manager here at Union Square Consulting.
RACHAEL BUECKERTAnd with me today is Jodi Geiger, co-founder of AI Sales Studio at Go-to-Market Shift. Jodi is also a go-to-market advisor and revenue coach with about 20 years in sales leadership across Clue, Apple, Galvanize, and Rogers. Jodi, thank you so much for jumping on talking with me today. Yeah, excited to be here. Yeah. So today we're talking about building a culture of innovation with AI and practical applications of AI in go-to-market ops and everything surrounding that. So to start us off, Jodi, you've led sales teams through multiple evolutions, PLG, RevOps, and now AI. If you were building a go-to-market org from scratch today, what would you design differently? And how would your past career experiences influence that design?
JODY GEIGERYeah, it's interesting. When you, as you said that, I was like, yeah, PLG, RevOps, AI, they're definitely eras. I can like even think back to, you know, working in software when it was perpetual licensing or on-premise software that we were converting and migrating to cloud. So, you know, there's like the mobile era. I mean, there's been so many of these eras. I think the interesting piece right now, if we're, you know, even thinking about defining some of the ones you just talked about. So PLG, I think we all as an industry learned about, you know, product adoption with growth teams, you know, growth PMs, growth hackers, really being the kind of heroes of that era. There was a huge focus in the organizations at the time to have a, you know, seamless UX and the assumption that, you know, buyers can figure out how to buy and complex sales should be ignored. You know, buyers know how to buy. The product should just work. And then I think overlapping with that, we also saw the RevOps era where I would classify that as maybe like process alignment really with RevOps teams growing and taking, you know, higher and kind of larger and building larger and larger orgs and data and systems and tools really becoming a thing. And it was really, you know, focusing on the mechanics of the system. How does data and how do tools talk to each other? And in some ways we over-mechanized that, I think. And then with AI, the advent of a go-to-market engineer and this, you know, the things probably I love most about this era is the focus on this system and the ability for the system to have built-in learning loops. And so, and I think we're now just starting to figure out what are going to be some of the limitations with this system? What will be different versus the same from some of the other eras that we've lived through in go-to-market? But I think, you know, to your question of how would my past experiences influence the design today if I'm starting. And in many ways, I am starting today, you know, with co-founding AI Sales Studio. And I think that what I'm seeing right now, and maybe the same mistake that we've made in other eras, is I see so many teams chasing speed before trust. We have to move fast, but really these winning go-to-market orgs are moving fast because they're grounding themselves in understanding, yes, from data, but also from connection and from curiosity. I'm someone who's led always, I think, with like people before process as a mindset, but process makes people scalable, right? The best go-to-market organizations are not built on tools. I think they're built on clarity, they're built on trust, and they're built on rhythm. So that RevOps era taught us the power of systems, but it also taught us limits. You know, we can't sit and kind of dashboard our way to growth. So I think in this AI era, I'm looking at lightweight systems. I'm looking at systems that allow individual contributors or managers the space to think, right? Not just click and not have context. I want them to turn their brains on. And I think AI can automate busy work, but it really isn't going to automate, it can augment, but it's not going to automate judgment. It's not going to automate empathy. It's not going to automate curiosity. And really those things are the things that win deals and help revenue grow. And that's what I still think that we need to hire for and we need to cultivate.
RACHAEL BUECKERTAbsolutely. I couldn't agree more. And that's so validating too, because that's kind of the crux of what we try to do all the time here at Union Square Consulting. Just yesterday, I was doing a podcast with Eddie and we were talking about how people can actually succeed with Salesforce, for example, and build revenue from that. And it's not about the tool at all. We didn't talk about dashboards or workflows or anything like that. It was all about the process and like what your mindset is when you are building these systems and what you put into it to make sure that your salespeople are following the right sales processes and methodology and you have clear exit and entry stage criteria and stuff like that. Eddie had a quote, I'm probably not going to remember it correctly, but it's something along the lines of you're not going to succeed with tools. You're going to succeed with process. The tools don't matter. It's like the process and the people that really matters. And the tools are just that they're just tools.
JODY GEIGERYeah. I think so many teams out there are starting with tools thinking, okay, we just need to purchase this point solution AI tool and it'll solve something that's broken in my business. And I think what we forget is that it's not just a tool. You know, the technology is one aspect of it, but it's the people, it's the process, it's understanding and designing a system. And what that takes is, you know, we're talking about change and change management and change is hard for people. We have to start in that place where we understand both what's happening on the ground level. What are the people that are doing the jobs and understand every click required to do that job at a high level? Can we understand and audit that? And then can we somehow bridge that gap between the people that have decision authority and control to change the system? And then how do we work with those teams that are those connected tissue teams, like the enablement functions and L&D and people and finance and ops and rev ops and AI ops? And how do we bring all these teams together so that we're all part of designing and building in and testing into that new system? And I think that's what we get wrong is we think it's a tool, we slap a tool on it, it doesn't work, we say, you know, the output is generic or something is broken. But I think that's on us as leaders, we haven't spent the time to do the mapping, the auditing, and the planning for change and adoption and testing, let alone setting up the iterative process of experimentation and that learning loop. We're missing it.
RACHAEL BUECKERTAbsolutely. Absolutely. Leadership has to be all in on this stuff or it's just not going to work. You can't have leadership and the people with the actual change authority to just like push it off to somebody else and be like, here's the tool, you know, have at it. You don't bother me with this anymore. Like they have to be involved. So what other skills do you think will be so important in doing this and defining the next generation of high performing revenue teams, especially as we're working so much more with AI these days? You know, when I think about that, I think it's skills, but
JODY GEIGERit's also a mindset. I think in some ways, people have been, especially in startup culture, or in our tech, you know, world and bubbles, we can be a bit allergic to process. Sometimes we think it's the enemy of creativity or the slowdown of experimentation, which are both so poor to startup culture. But I don't really think that process and implementing process is the problem. I think it's when you bring in process and how you introduce it. So in my experience, you bring in process once something is working, once a flywheel is in place, and that's how you make creativity repeatable and dependable. So what are the things that we're looking to do now and the skills that are needed? We need to all be curious so that we can find the unscalable things that make our solution magical for our customers, right? So we need to work so hard to find out what those things are that we do, and only we do. And then we have to figure out a way to make those things scalable so they don't break the bank as we try to grow. But that's, I think, what cuts through today. It's not more information. Context, I think, beats content. And it's the ability to offer insights and interpretation for our customers. And it's that ability to connect the dots that is going to allow us to do that unscalable work early so that we can build something scalable
SPEAKER_19and credible later. That's interesting. So how does one scale the unscalable differentiator in their
RACHAEL BUECKERTbusiness? I mean, I think almost to your earliest question is, what would I do differently? Or where
JODY GEIGERdo I think, you know, if I can, in some of the businesses I've been in, if I wish I could rewind the clock, what moment would I rewind it to? Or, you know, when you first started a company, I think you have this very precious amount of time at the beginning to get yourself so immersed in what the customers are experiencing. We have to take the time to deeply understand our customers. We have to understand their situations so we can know why now and why us. I think only when we understand our customers' situation can we understand why they need our solution. And I think so often we rush at the early stage of building or we rush at the early stage of joining a company through that precious time where we get to ask those questions and get to, you know, really dig down deep and learn. Because once we understand our customers deeply, there's going to be other customers in the exact same situation who need us. And we'll be able to recognize those signs. So unscalable things can be like listening to the language that our buyers use, right? And anchoring our messaging in it. Customers tell us what they need. They tell us in their words all the time in every single conversation. So how do we design a system that's going to capture their words? And then simply in our messaging, we just use their words. Root our messaging in our customers' language. And it's not
SPEAKER_16just going to convert better. It's going to connect us to our customers better.
RACHAEL BUECKERTAbsolutely. And for me, like coming from a marketing and copywriting background, that was such a huge thing for me when I was just doing copywriting for businesses and their websites and stuff. Voice of customer data. Like I would go out of my way to interview my clients' customers and find out in their words on a call, like how would they describe the moment where they decide to reach out to my own clients and all these things. So yeah, that's a very underrated skill and benefit for the company to be able to listen to that and put it into every aspect of your business. Not just marketing, but product, sales, customer success, everything.
JODY GEIGERYeah, that's the connected tissue. I think that it is the world. AI allows us to be able to do some of the, what would have been manual hours of labor, right? We can shortcut that. And like, if we shortcut that well, now it's not just people doing the copywriting and, you know, working in voice of customer. It's now sellers can have that context. SDRs can have that context. Customer success can have that context. Our engineers can have that context. What that allows you to do, I think, is that, I mean, again, we can shortcut it with AI, but it's going to pay dividends even if it does take a bit more time at the beginning. Because what it allows you to start to do is work with your customers more deeply. Follow them in a case study fashion. Look at the, and understand deeply their world before working with you and in their world after working with you. You know, I think that we can all think about working in organizations where every seller, every solution consultant, every customer success person, every marketer is going, who are our good customers? Where do their good stories live? Do we have strong impact analysis, you know, reporting? It's like the hardest thing to find, but it's one of those things that if we, you know, relate it to investing, it's the thing that's the compound interest in your business, right? It's slow to start. It's hard to do. But once you have those few solid data points, your credibility starts to grow exponentially. And so I think where teams go wrong in this is that they're chasing the next sale or they're moving on to the next thing before they, you know, spend enough time in that first thing or with those first customers, proving the value, proving the impact, and then designing their system around that, you know, value outcome.
RACHAEL BUECKERTAnd so how do you suggest people do this in the early days or even like later on if they just haven't done this yet? Because I imagine it takes a lot of effort from the customer side as well to actually sit with you and talk about these things. So how do you like kind of convince them to share these stories with you and use their time to try to educate you on this? I think it's about capturing the moments that you are in front of customers. It's creating the
JODY GEIGERsystem where you are collecting these data points from every possible interaction, be that from website clicks to who's attending a webinar or an in-person event and taking great notes. It's every cold call. It's every discovery call. It's every email and the context back from that. It's customer onboarding data. So I don't think it's sitting there and asking customers to invest more time with us. I think it's us being able to extract the insights that they're already sharing in these already built moments where we're demonstrating value and learning, you know, and co-creating with them. We have to have systems that extract that so that we know how to use it. And again, I think when we're moving so quickly, one of the hardest things to do is to slow down and actually do postmortem, actually, you know, take time to reflect on what worked, actually to strategize on where to go next. Those things are hard, right? When you're on a cycle of every quarter, every year, time moves quickly. And it's, I think it's the teams that are able to have insights from data and then take immediate action from data that are moving faster in today's world.
RACHAEL BUECKERTOkay. So this process of, you know, getting good at this stuff in the beginning, does AI have a role to play in that or does that come later?
JODY GEIGERYeah, absolutely. It does. I think if we think about the old way of doing something and there's still need, need it. The old way is still needed. It can be true today. But I think in the olden days, you know, we are sitting there and trying to go through and parse through data manually. And that doesn't, you know, need to happen anymore. We're now able to say, even without, you know, complex AI tools and systems being built, you can connect data from multiple places and you should be extracting data from those places. And that's, I think, the first step to setting up a great go-to-market motion is figuring out where does the data live that's going to inform how we, you know, get better and learn as a team and learn as a system.
RACHAEL BUECKERTAbsolutely. Tell us a bit about AI Sales Studio. I don't know how it got started, why it got started. What do you guys do?
JODY GEIGERYeah. I mean, we're still at the beginning. We just, we were about two months into working together, James Kekis and I. James is the previous CRO at Testbox. And prior to that, I was a co-founder with Presales Collective and we were both in a similar position where we were working and leading, you know, revenue functions in startup and scale-up environments. And when we first connected, we realized that we were working on a lot of similar projects and we were seeing similar wins running into similar challenges within our own businesses, trying to figure out how do we grow quickly? How do we scale quickly? How do we leverage AI and build out new ways of operating within our teams? How do we manage the change? What does a good system look like? All of those things. So we started connecting on those types of, having those conversations regularly and sharing and learning. And then both of us came to a point where we had that itch that I think so many people do of what if we did this for ourselves and what if we could help other teams navigate the same change process and the same point in the market. And that's where, you know, AI Sales Studio was born from, is can we bring together, at least in my case, can I bring together the expertise I have around people? You know, I've obviously like led revenue teams, but I'm also a, you know, an ICF certified executive and teams coach. I'm trained in Enneagram. So I have this deep love of people and, you know, how, like, and brain science and how do we bring that together with expertise and experience in building revenue systems? And then now with the experience I've gained in the last, you know, almost two years of pioneering some of the first AI ops functions, can we bring all of that together? And can I help other teams figure out how to work smarter well with AI while still bringing forward what makes humans the best? Yeah. You can't lose the human element soon. The human element is going to be like the
RACHAEL BUECKERTbig differentiator in all these companies. I know. I keep thinking that the role of enablement and
JODY GEIGERthose mindset and kind of traditionally soft skills types of functions are going to become more and more relevant as we leverage AI more and more in our businesses. Absolutely. So what are the kinds of
RACHAEL BUECKERTthings that you think AI is like best suited for? If we want to keep the human element and we want to
RACHAEL BUECKERTlike maintain this level of personality in our businesses, what should we then be delegating to
JODY GEIGERAI? I think anything that is working and repeatable and that we can, that takes a lot of manual effort and time, I think we can use AI for, right? AI can make good reps faster, but I think we need humans still to coach and help develop humans to be wiser. Humans are generative. We're creative. AI works within the construct of what has already been done. And so I think that's where we need to maintain our difference and our uniqueness as humans within the process. So we can build smart AI systems that continuously learn, but we need to be able to use our best, again, judgment and curiosity and connection as humans to improve that system and give feedback to that system. I can give a couple examples, but at Clue anyway, is that we were, we used to take, it sounds like wild to say, but we used to take eight hours per prospect to create and set up a demo environment, meaning a customer books a demo. So either inbound or outbound books a demo, we are spending eight hours on the backend, customizing that demo space so that they see their competitors, the right competitive positioning information, because we want them to experience what it actually feels like to have good competitive enablement content in the tool. But when we realized the time and looked at that, we realized like one, two things. When we customize, our deals move faster, you know, we, we win more, but also it's so slow. And you know, the CAC on that is terrible.
Right?
SPEAKER_37Yeah. We're not winning all of those customers. So we started to hypothesize and this was kind of early on with AI kind of on the scene. And we started to wonder, you know, could we cut the manual effort
JODY GEIGERwhile keeping personalization intact? And so we ended up devising kind of three approaches as a bit of a test. We said, can our, you know, newly formed at the time AI ops function with, you know, it was like one person and an intern. Can we figure out a way to use different AI or workflow automation tools to create these environments and have it loaded with personalized content? Or can our enablement team review off the shelf demo automation tools and cost that out and see what the benefit would be? And then we also looked at, do we not customize or personalize at the individual company level anymore? Do we actually just build out some vertical demo spaces? And so we ran a test and we ran that test over a not long period of time. It was like maybe a month or so. And what we ended up doing is the AI ops team won the horse race. They ended up building a clay, you know, meets Zapier meets Slack workflow that auto-generated these demo spaces. It went from eight hours per demo space to under two minutes and like 75 cents per token. So you can imagine what we were doing before with someone very experienced people with like vast expertise in the space designing this content previously to now AI doing it. That's crazy. Yeah. Like that obviously lowered cap and like cost per opportunity with minimum tooling costs, but also our AEs gained, you know, instant access to personalized demo spaces when they need it. So now our deal velocity and also deal capacity improved. And I think that was the experiment that really got my mind, you know, moving and going, whoa, what is a, you know, systemic go-to-market engineering mindset and approach look like? And what is that going to mean to our business? And that was
SPEAKER_43really exciting. Yeah, absolutely. Was that kind of like the first, like real measurable win that you
RACHAEL BUECKERTsaw implementing AI? Yeah, that was, I'd say like the first big one that really made me go, oh my gosh,
JODY GEIGERlike just like the swing in time and cost. We had other ones. Like, I think if we go back circa 2020, what is your outbound personalized email process look like? We were at the time growing really fast and we were growing really fast, largely off of outbound prospecting activity. And we were known, I think, for our personalized attention to detail when outbounding prospects. It was very high touch and we had a high, you know, attention and eye for detail, but we also knew we needed to send more emails. We need to send, you know, better research emails to stand out in what was becoming a more complex and I think like overloaded space in people's inboxes. And we also knew we wanted a human in the loop. So we started looking at how great outbound emails were being generated. And we wanted to, again, see those unscalable things that were high quality, but also high impact. And we needed to understand the process. What did it look like for each rep to write an email? Well, they were doing it from scratch. They were manually researching each prospect. They were writing a point of view. They were crafting each message line by line. How long did that take? You know,
SPEAKER_38it's like 15 plus minutes per message. You know, it's slow. It's, you know, it's also inconsistent.
JODY GEIGERSo then what do we do? We said, okay, well, you know, now with AI, this is great. We can just use chatbots or, you know, like different LLMs to speed things up. So we crafted a number of prompts that could be easily reused. We'd save them into like spreadsheets and we'd copy those prompts from the sheets and paste them into chat GPT and add in buyer context and edit the generated emails and copy and paste it in and out of outreach. And I know like it felt more modern, but, and it was really just like maybe a more winding version of a manual process. Cause like every step lived in different tools. And there was still so much context switching between like copying, pasting, reformatting, adding context, and each task that looked small in isolation. But when you take that and you put that across every rep, every prospect, it's just hours of wasted effort, you know, with what you dream that AI can do for you. So anyway, we pushed to find a new way. And we basically started by looking at, at, you know, every box in that old workflow as a step in the process and ask questions like, what can we cut? What can we automate? What actually needs AI or is a good prospect for replacement with AI? And that led to a completely re-imagined flow that we were able to design from that detailed workflow audit. So now instead of toggling between tabs and tools, the automation is built, it now, you know, conducts and pulls research from clay, from prompts that live in there. It surfaces your insights right in HubSpot at the company and contact level and reps send personalized context-rich emails with just literally one click. Like they go into the contact, you know, at the company level, it's connected into outreach and it's like, all of the personalization and point of view research is there in the structure of the email is there. So no more copying prompts, no manual edits necessarily. And I think the rollout was cool because we had spent so, or like the teams have spent so much time one-on-one with people who were doing the work and getting feedback on, is this the right output? Is this the right output? What would we change? Where do we need to feel more human? Where do we need to add more context? Where do we need to bring more of the buyer's situational understanding in? Where do we need to improve our value prop? Where can we bring in customer language? And because the teams across Sparkle go to market motion and like customer success teams, everyone was involved. Now the team has buy-in to the process. And so the first day that this was rolled out, we had an SDR on the team, shout out Emma, went in, found the context she wanted to connect with, literally like hit the button, email went out and booked a demo that day off of it. And so, you know, that type of win, I think too, really supported people's excitement about adoption.
RACHAEL BUECKERTAbsolutely. Because adoption can be one of the hardest parts, just getting people on board with a big change. People don't like change. So is this like a, this is a proprietary tool? No. What tool is this? No, this is like a combination of outreach, HubSpot, Zapier, Play, like just building and
JODY GEIGERfiguring out again, what does good look like? What does research look like? What are the sources that we're going to? What's the structure of an email? What are the data sources we're going to, to collect that? What does our process look like? And what, how do our sellers actually send an email? Let's understand all of that. And then let's test and engineer that so that it can be just a one click emails ready, human in the loop to review the email.
RACHAEL BUECKERTSo I'm just trying to picture this. I haven't worked with all these different tech tools you mentioned. Where's the interface that you're using? Like, where does the one click go to? Is that like a one click in HubSpot? HubSpot. That's HubSpot? Okay. Awesome. I think, I mean, it couldn't change now because I left in July and like the team is constantly
JODY GEIGERiterating. But when I left, I think it was like a contact, at the contact level in HubSpot, you can do a one click and all of your point of view research email is ready to go that you then can send out that's connected through to your outreach. So kind of logs everything there.
RACHAEL BUECKERTThat's awesome. And is this the kind of stuff that you guys teach in AI Sales Studio? Like you show people how to actually create these workflows?
JODY GEIGERYeah. So we do two different things. We teach live workshops with people who sign up and we're just finishing our first cohort with this one workshop. And that workshop has people from enablement roles, solution consulting roles, sellers, L&D roles, sales leadership folks in the room. And I think everyone's trying to figure out what does that system look like? What is the systems mindset as we look, as we think about bringing AI into what was a standard go-to-market motion, right? Yeah. So we're teaching that you're getting hands-on, you're figuring out and getting access to some new tools, you're testing out some things, but we're really trying to embed that idea of where does my data live? What is the input and what's the output and what should be like the system? Can I understand actually this workflow? Can I break it down? And then where would I bring AI into that workflow and what do I need to understand? So yeah, so we're teaching that. And then also we work with go-to-market teams in like actually in companies and come in there and do everything from advisory, from a leadership perspective, to coaching through the change, to working on designing the systems and kind of doing the audits. And we work with a number of partners and tools as well that we can bring in and help get these pilots and experiments off the ground and help with the change management process. That's really interesting to me because like I've fiddled around with Clay and HubSpot and
RACHAEL BUECKERTthese different tools and stuff, but I just don't have the time in the day to like focus so hard on learning the ins and outs of all these tools. So I might even join one of these workshops someday, figure this stuff out for our own business. That sounds really cool.
JODY GEIGERYeah. Love to have you. I mean, it is, it's, it's no one, oh, I don't know one, but like for most people, I think we're so, it's like that far side. I don't know if you remember this far side cartoon. Oh yeah. It's like these cave people pushing the, you know, the square wheels wagon. And then this like person's like, I have a round wheel for you. It's like, oh, I'm too busy, you know, to put this round wheel on as I'm pushing this square wheel up the hill. And like, I think that's where we're all at right now is that, yeah, it's so hard to find the time to figure out how to work smarter and bring AI into our own workflows because we are again, racing and moving so fast, but at the expense of a better way of working. And I think that's where, at least what James and I have experienced and what we hope to be able to bring to other teams is how to get started, how to think about the process and what a step-by-step phased approach looks like to get some small wins and create that culture of experimentation and iteration within a team.
RACHAEL BUECKERTYeah. That's so funny because the more that I'm thinking about the, like the square wheel thing, the more it applies to like so many different things. Like even with our own company, that's, that's kind of like what we're trying to do for our own audience as well. But from the process side, instead of like the actual building side of these tech tools, everyone's like, I'm too busy. You know, I can't, I'm pushing this square wheel. Like I can't, I don't have time to change my processes.
SPEAKER_30And humans are so funny. I was just listening to Diary of a CEO and, but this episode, and if you
JODY GEIGERlistened to it, it was this one recently about what women in their forties. So, you know, right in my demographic, what we should be doing health-wise and longevity-wise. And one of the things that was brought up was this idea that, I can't remember who it was, but there was like a, an MRI done on people and they asked them to think about their current selves. And then they asked them to think about a celebrity who they don't know, and then asked them to think about their future selves. And the, in these MRIs, our brains lit up. This is, you know, like conclusive. Our brains, when we think about ourselves was a certain light up. When they think about a celebrity who they don't know and their future selves, that activity was the same. We literally can't conceptualize future me. And we think about future me as there's always going to be time. There's going to be this better version of me. I will suddenly like have figured it out in my future self. Right. And it's really hard for us to figure, to put ourselves there and make decisions today that put us in a better place for our future self. Right. That's why it's like instant gratification. And so when I think about AI, it's kind of like that and changing our workflows today, it's, I think I will have time in the future, or I'm going to wait until my company tells me how to do it. And I don't think that's the way to think about it. I think it's the people who are building in some of the trying and testing new things and playing with new workflows and figuring out ways to optimize their own workflows. I think those are the people that are going to be, if we take health and into it, those are the people that have built the habits around the weight training and the right supplements and the right sleep habits, et cetera. And I think it's just that it's setting ourselves up for who is the me in 10 years. And what does my work look like then because of what I've built today in terms of a system?
SPEAKER_17Absolutely. What would you say are some of the behaviors and habits that separates the AI enabled sellers from the people who just get distracted?
JODY GEIGERI actually don't think it's that different from you asking me, what's the difference between an elite seller and an average seller? I think it's the same question. And the reason I think it's the same question is that if you look at elite sellers, they know and have a system and they own that system works for them and they repeat it to the point where it's like boring almost to watch them because they do and say the same things again and again, but they know it's going to work, right? They figured it out and they packed it. And I think that's the same thing with AI. It's spending the time to figure out what does my work look like? Where does the data need to flow? What do I need access to? What are the right inputs? What is the output? Can I understand that deeply of like what good looks like as an output? And then can I figure out what the right system is to be able to repeat and optimize and experiment to make sure that this system is the best system to be able to optimize my own growth and output. And so, yeah, I think it's all a systems mindset and what that takes skill wise. I think it takes, well, I know it takes curiosity. It takes the ability to make some mistakes. It takes a culture of experimentation where you can show something that didn't quite work or isn't quite there yet. We have to play. And that first pancake is probably going to be a little burnt, but that's okay. We have to be able to get that one out of the way so we can continue to learn. And so one of the biggest things I try to share with people in teams is how are you making space for your teams to be experimenting with different tools, trying different workflows, changing the way they're working, and how are they sharing that with one another so that we tap into that collective creativity and collective knowledge and wisdom.
RACHAEL BUECKERTAbsolutely. I think a lot of companies are a little bit scared to experiment these days too, especially the earlier stage companies who feel like they don't have a ton of runway or revenue or time to fail. And so they're too scared of failing and they don't want to experiment and they're trying to do, you know, what's tried and true, but there's no one playbook that's tried and true for every company. So you kind of have to, like it's, you have to, there's no, there's no shortcut around experimenting.
JODY GEIGERNo. My co-founder James was famous at a pavilion conference in the spring, the CRO conference. He's got up on stage and said, no one's been a CRO in 2026 before.
SPEAKER_43I like that.
JODY GEIGERAll the playbooks that we've had leading up to this moment, not that they're obsolete, but they're not going to be, you know, the way things get done anymore. We have to shift and grow as leaders and we have to make space for our teams to shift and grow because we are in a new world. And we also, you know, it's our responsibility to chart a path for our teams to step into and create a future that doesn't already exist. Right. And have a big vision. And the only way I know how to do that is to get everyone rowing in the same direction. And that takes an alignment around a vision that takes agency for your teams and people to take their work into their own hands and try to move it forward. Right. And that's not in a typical, like hierarchical kind of command structure. Yeah. You know, we need to be more tactical and we need to have more flexibility in our systems.
RACHAEL BUECKERTSo what would your advice be for go-to-market leaders and CROs who are already experimenting with AI, but they want it tied to pipeline, red weights, red productivity, and really see
RACHAEL BUECKERTwhat is actually moving the needle, so to say?
JODY GEIGERYeah. I think it's the same thing as like what a good salesperson does in discovery. We have to figure out where the friction is in the system. What is it that's preventing us from or costing us time? What's costing us money? What's costing us confidence? We have to find that friction. Once we find that friction, we then need to figure out, is this the right problem to solve? Is this the thing that's going to move the needle? Is this the thing that's going to, you know, be the story that the board wants to hear and give them the confidence in us? So yeah, figuring out what is the point of friction, figuring out if that's the problem that you want to solve. And if it is, then get down to as ground level, click level as you can to understand what that workflow looks like today and get the baseline. What is it costing you? What is it, you know, preventing you from doing and build a little bit of like that one page business case? What's the narrative around it? And we have to have that before and after so that as we start to test it, we know what those metrics, you know, look like. Like back to my story of we had to go through and figure out it takes us eight hours to create a demo environment. What does good look like? And like, if we break down the cost of that, you know, persons, these people who are doing this, what's their salary? A lot more than 75 cents per space for sure. And so, yeah, I think that's where I would say to start is find the friction, do some good discovery, do some good auditing and figure out if that's the priority, that's the problem, that's the metric that you need to solve for. And if it is, your team's going to rally behind that
SPEAKER_01because they know that that's going to be the thing that's going to lead them towards your growth goal.
SPEAKER_17Absolutely. What a great answer. This has been an excellent conversation, Jodi. Thank you so much. Maybe one day we can get you guys back on again, get Eddie in on it too. Before we head out though,
RACHAEL BUECKERTwhere can people find you and AI Sales Studio? LinkedIn is probably the best place. I mean, our website, GoToMarketShift as well,
JODY GEIGERbut LinkedIn, both James Kekis and I put out a decent amount of content just around what we're seeing, what we're doing, trying to share best practices and stories. And you can find us from there into, you know, Substack and other places, but I'd say start with LinkedIn.
RACHAEL BUECKERTAwesome. Thank you so much. Have a great rest of your day.
SPEAKER_03Thanks for listening to the show. If this resonated and, or you'd like help with anything we talked about in the show, please reach out to us. You can find us at unionsquareconsulting.com and the info will be in our show notes.
