B2B GTM in the AI Era: If AI Makes Marketing Easy, Why Is Growth Still Hard?
Questions we will cover:
1.How has AI changed the way you approach marketing? We’ll open by exploring how AI is reshaping day-to-day marketing work, from content and targeting to measurement and personalisation, to understand how each of you or your teams are experiencing this shift in practice.
2. Historically, how do you balance demand creation and demand capture (top and bottom of the funnel activities)? How are AI and personalisation at scale influencing this balance? This will look at how you manage the tension between long-term brand and short-term pipeline, and whether AI-driven targeting is changing where marketers invest their focus.
3.If AI can now do most of what marketers once did to reach, engage, and convert customers, what’s the role of a brand in this new world? Do we still need to care about branding, or should we rethink our entire go-to-market approach from the ground up? Here we’ll explore how brand identity and emotional connection evolve when technology handles much of the execution, and whether creativity, story, and empathy still matter as differentiators.
4.What new skills and mindsets will marketers need to stay relevant by 2030? To close, we’ll look ahead at how the role of marketers is changing, from strategic leadership to creative experimentation, and what capabilities will define success in the next decade.
Guests
• Allie Collins, Chief Marketing Officer at Betterworks
•Lauren Luen, Founder and CEO at The Nervous System LLC
•Nicole Mills, Sr. Director of Demand Generation at Algolia
Transcript
Joaquin (00:00)
welcome to another episode of B2B Marketing Futures. Today we are discussing B2B GTM in the AI era and exploring how AI is changing the way organizations define their markets, reach buyers, create demand, and execute their go-to-market strategies. AI is giving teams the ability to analyze audiences, develop content, personalize campaigns, and test new ideas faster than ever.
but it's also creating new challenges. GTM teams are being asked to do more. Competition for attention is increasing really fast. And ability to test new tools can make it harder, not easier to stay focused. In this episode, we'll explore whether AI is helping organizations make better strategic decisions or simply increasing volume of activity. But before we begin, I'd love for our guests
to introduce themselves and share a bit about their backgrounds and current focus.
Lauren Luen (00:55)
Sure, thank you for having me back. Really appreciate it. I'm Lauren Lewin, founder of The Nervous System, which is a strategy and operations consultancy that helps growth stage companies build the go-to-market infrastructure and AI enabled operating models that turn strategy into measurable outcomes. So happy to be here again.
Joaquin (01:14)
Thank you so much, Doreen, Ali, welcome.
Allie Collins (she/her) (01:15)
Hi, so excited to be here. I'm Allie Collins. I'm the chief marketing officer at BetterWorks. We're a performance management and talent intelligence company that's all about taking goals, strategy, and aligning it to business outcomes. So I'm excited to talk about my role in marketing and how that relates to better performance across the business. So excited to be here.
Joaquin (01:38)
Thank you so much, Ali and Nicole, welcome.
Nicole MIlls (01:41)
Hi, thanks for having me. I'm Nicole Mills. I am Senior Director of Demand Generation and Customer Marketing for Algolia. And we are an AI search company that basically functions as the intelligence layer in search and discovery for AI search and also agentic and generative experiences on websites and apps.
Joaquin (02:00)
Awesome, thank you so much for those great introductions. Let's begin with the broader picture, because AI is now influencing almost every part of the go-to-market strategy from the ICP definition, market research, targeting, content, personalization, and sales execution. Where are you seeing AI have the greatest impact today?
And is it primarily changing how organizations execute their existing strategy or is it beginning to change that strategy itself?
Lauren Luen (02:33)
in my experience, what I've seen is that
AI is really forcing go-to-market teams to get disciplined. Get disciplined about the data foundation before anything else. I know that most people, most companies, the knee-jerk reaction is, let's jump straight to the model. But if your data is fragmented, as I'm sure Ali and Nicole, you've experienced, the model just amplifies the mess. When I was at EDB, we spent months solving for data that was both duplicative and incomplete at the same time. It resulted in us unifying first and third party data
signals just to get to a great baseline before we built anything else. The AI results came after that because it had a good foundation to work from and those results were like 35 % average AR growth per account and 55 % more opportunities per account. for me it's the companies are WInning with AI in go-to-market. They're the ones not with the most sophisticated models. It's the ones that have done all of that data homework first so that you have something good to build on.
Nicole MIlls (03:31)
Yeah, I definitely would agree. It's still that junk in, junk out adage. If your inputs aren't clean, it's the quality of your data, the structure of your data. if you're starting out with a mess, there's nothing that AI is going to do to improve the quality of your input. of course, I work for an AI native company and we do have things like data transformation, things like that.
But again, it's the base input of what you have accumulated at your company and what you are introducing to the model that's going to inform the output that you're able to get. And I do think that we're in an interesting position. Like I said, Algolia is an AI native company. So we are, in our products, offering our customers ways to access AI to improve.
brand loyalty and retention and grow margin and so forth. But also we are a part of this whole AI transformation too. We're experiencing that ourselves internally. And so I see a really pervasive effect of AI across all of our work streams from how people are ideating and iterating a new product introduction on the go-to-market side, how we are approaching our workflows and how can we
get to market faster. How can we ingest more of the data signals that we're getting, and so that we can adjust our campaigns and our strategies more quickly, be more agile, be more responsive. But there is absolutely early, I don't want to say grumblings, but early feedback from the teams. I had one person who is overpaid media for my team, and she says,
Sometimes I feel like have to be a bootleg developer these days. And so there's so many different aspects of my job now that just didn't exist 10 years ago. There's a lot that I can do with these new tools to accelerate work and to experiment. But at the same time, all of that experimentation is time consuming. And it's a huge context switch for marketers too. So I think that...
As much as it's enabling us, it's also challenging us because we all still only get 24 hours in a day. None of us are spending 24 hours on work. And so it's a challenge of not being distracted by the possibilities, but really being very strategic about what can these tools actually help me do better at and where do I need to focus them? Not everything needs a laser. Some things just need a pair of scissors.
It's really trying to figure out how do you fit the tool to the task. And then it's a lot of learning on the job because we are all figuring out how this fits into our existing setups.
Allie Collins (she/her) (06:18)
Yeah,
I would agree with those perspectives. I think for me, it's like the fundamentals of go to market have not changed, Like the things that you need to do, Understanding your ICP, tailoring messaging, all of those things are more true than ever. I think what AI has done is increased our capacity to be able to
synthesize data and understand the inputs to those things, Like we're taking in more data and able to understand it much faster than we could before. We're able to then translate that data into content faster than ever before. We can create tons of campaigns. We can personalize that scale. We can do so many things that we couldn't do before, but I don't think that it's really replacing the strategy and the creative element
as marketers, have to see these as assistance and tools to help us do our job. No different than any other technology than we've had before. It's just more powerful. But for me, the strategy still very much sits with my team, how we operate these tools and get the most out of them. But like you guys said, the increase in capacity is true of all of us. So, our competitors have that same,
advantage of being able to increase capacity, pressure to move faster from above, I'm feeling, more than ever, We're all just expected to do more. keeping up with that pressure, it's like, the floor has, increased, but so has the ceiling at the same time, And we're all dealing with that, inflation type effect of everybody's expecting more, we're doing more. But
the strategy component still takes time and thought and a human element to it. So I would say not on the strategy side, other than being an assistant to the strategic element.
Lauren Luen (08:03)
I'm thinking about what you said, Nicole, what you said, it brings us two points together that without a clear objective, AI encourages teams to do so much more, but we're doing more of what? It's amplifying the health of Skelter per se. you see companies with 15 AI initiatives, but they're 20 % done. But if you scope it tightly I think Nicole, said something about what can I focus on?
If you have a tight scope, then that AI really does force the focus. at EDB, we picked one motion, one motion initially, it's accounts that need to land and expand. Simple. We've been doing it, Ali, you said, generations of time. That's part of go-to-market accounts that land and expand. went deep before we touched anything else. So we helped our sellers go from fishing in an ocean to fishing in a pond and giving them the right bait. Now we have all the intelligence.
of AI. So it's really that fine balance of keep it focused, keep it narrow, go deep, do well. I feel if we keep it broad, we're just not going to progress beyond that pet project phase.
Allie Collins (she/her) (09:01)
thousand percent like I've always said that strategy is often less about what you're going to do and more about what you're not going to do.
Lauren Luen (09:09)
Yes.
Allie Collins (she/her) (09:10)
Being strategic about that, I would say that's like my number one job right now is curating and helping my team prioritize against the goals that we have, So setting an objective, working towards that and being really disciplined, like you said, Lauren, about how we're going to map to that. The AI is giving us the tools to
achieve those goals faster, which is great. but if we're not laser focused on that intent that we started with, the scope creep can get crazy and the quality of the outputs can really diminish fast, right? Like I have people from other departments, people on my own team, putting things in front of me constantly that I'm going, yeah, definitely AI did this, And so really training the team on how to use the tools in a way that,
uses AI as an assistant and not as the fast pass to creating slop, right? Like that's such a danger. You're seeing it everywhere right now. Every LinkedIn post looks exactly the same to me. it's honestly sickening to me at this point. like getting creative about how we use the tools without turning it into just a formula. Like we're all feeding the AI the same, information and outputs like
It's such a challenge, right? Especially under the pressure of, the C-suite telling us like we should be able to move faster. We should be able to reduce head count. It's like, yeah, sure, we can do that. But we also have to maintain taste and we have to maintain, you know, a standard of quality that I feel like overall is just slipping in a big way right now.
Nicole MIlls (10:40)
Yeah, I think brand stewardship becomes even more important in this particular era. And I think that we really have to encourage people to really interrogate the output of the LLMs and the different tools that they're using. I do sometimes see what I think is an uncritical use of AI tools, particularly when
I get something emailed to me and it's 17 pages. And I look at it and I go, how much time am I going to spend to distill what exactly is needed of me, asked of me, what do I need to respond? How much of this is just really something that I can act on? And then I feel like I'm helping people to go back to basics to a certain extent.
how could you have used this as something that was contextual or good background information, but it is not the way that you want to steer or have the conversation. We still need human beings to apply their practices, their experience, their creativity, their knowledge of our customers, of their colleagues and our companies and our brands. All of that has to be,
add it to process by a human being. So it's like, think of these as tools and starting points, but you can't just abdicate your responsibilities, as a professional to the output of a tool. It doesn't work like that. Not well.
Allie Collins (she/her) (12:06)
Yeah, and getting more specific into like where I think it is working, Is when we get really smart about training the AI tools, creating GPTs, creating skills that are really highly trained on your business's point of view is where I'm seeing.
actual good outputs come out. Like you guys were talking about data and how the input or the output is only as strong as the input that you can trust. Where I do think that we are starting to see major improvements within my team is getting really smart about training our tools on exactly who our ICP is, exactly how our persona thinks, exactly what conversations with those people sound like, and exactly where our point of view sits.
relative to how our competition and what their point of view is, So if we can train the AI to really deeply understand those things, then we can arm our team with tools where they can, like you said, create things and interrogate those things against what we've trained it on. That's where I actually am seeing some quality outputs, but it really requires that discipline ahead of time.
of your messaging team to really get smart about how they build those point of views, create them and train rigorously so that the outputs are what you can actually trust.
Joaquin (13:28)
The basics remain the same. think that's the thing that all of you have mentioned. You still need to find your ICP. You need to do targeting correctly, messaging, measuring. All the basics are still the same. And then picking probably one channel at a time and start improving and working on that channel until it works. And using your AI...
for that purpose, but not the other way around. Many times we focus on making the AI work, but without the end in mind, And you mentioned some interesting things about brand and the importance of having your brand. And I think that leads us into that tension that is very inherent in B2B marketing, which is the...
the balance between demand creation and demand capture, right? You definitely need to invest in your brand to get results, but search behavior is changing, right? Organic traffic is becoming less predictable, generated engines are increasingly answering questions directly, and paid media is becoming more competitive.
And at the same time, AI is making it easier for every company to produce more content and more personalized messaging. So there's a lot of noise. So how is AI changing that balance between creating new demand and capturing demand that already exists in your case?
Nicole MIlls (14:54)
So as somebody who works on the full life cycles, the new business side with DemandGen, and then I have our expansion side with customer marketing, we are absolutely seeing changes in search behavior and our audience's behavior. So it's not just us. think it's marketers across verticals are seeing.
a lot less traffic coming to our site because if you encounter a generative overview on Google, that may satisfy the information that you were looking for with your query and you don't necessarily feel like you have to click through to additional websites to dig further. Then also, more and more our audiences are spending a lot of time within
perplexity looking for sources or they're having extensive chats with Claude. They work through questions and problems. And there right now is a lot of faith, I think, in the results that are coming out of those types of agentic experiences and conversations. think that there will be
come a point, I suspect, where people are going to go back to double clicking. They're going to want to, like I said, interrogate the output. They're going to want to say, OK, well, let's take a look. You're citing a video and three other sources here in this generative overview. I want to actually take a look at this video. I'm going actually take a look at the document that is available for download here.
because we're going to want to verify to what extent was the summary accurate or was there something else deeper that I needed to understand that didn't surface in the summary. A summary inherently is going to be a condensed version of something much more meaningful. And so I think right now we're seeing people, they're prioritizing their time.
and they're trusting the output. But I think over time, I think that we will see a little bit of a return to that double-click behavior. But I think for right now, on the demand-gen side, we're seeing the need to take advantage of some of the opportunities. Like Google has its AI Max program that helps you from a paid perspective also surface your information in the same breath.
that a generative overview would be available. OpenAI has programs where there are different spots where you can pop up in addition to just the information that's coming up and an agenda conversation with their tools. I think that we're going to see more opportunities from different platforms as they're interested in monetizing.
those conversations, those agentic conversations. But we are definitely seeing a change in user behavior and we're seeing a change in how people are seeking to get information. And so that's requiring us, to be... I think it's not about dumping a ton of content into the marketplace. I think it's about...
being very, very clear on your brand, your products, who you serve, why, what the value is of your company, I think is right now more important to get very tight on your reasons to believe as opposed to trying to flood the market so that you can pop up everywhere. Relevance is really important. And so I think it takes us back to the early days of SEO.
where, yeah, there were a lot of really dirty practices, loading keywords onto websites and hiding them and things like that. And we got to the point where there were best practices for SEO.
Joaquin (18:56)
Mm.
Nicole MIlls (18:58)
We're in that same sort of early days in terms of AEO and GEO also. And so I think that this does get back to
we do have a foundation for, what are ethical, relevant and valuable ways to engage your audience? You have to be thinking really hard about, how does your brand show up credibly in the marketplace? And I just
Joaquin (19:21)
100%.
Nicole MIlls (19:23)
have to believe that that's going to work in our stead. So as these tools get better at cleaning context and making
returns and conversations relevant and they're trying to connect the right information to the right person, based on the queries that they're receiving. the way that you chose to show the market and the more, I think refined your vision for company, your products, as I said, the better, I think that it's a time to go in and clean up your messaging.
It's a time to clean up your presence in marketing. And so if there is any sort of confusion about who you are, what you do, and why you do it, now is the time to really get clear on that.
Joaquin (20:07)
Hmm.
Allie Collins (she/her) (20:07)
Going back to your question
about brand, saw a stat this morning from winter that said that 92 % of buyers purchase from only from the brands that showed up on their day one shortlist, So.
on the brand side, you have to be in the minds of the buyer on the day that they start thinking that they are going to buy, So that requires brand investment that I think is often really difficult for CFOs and CEOs. they want to see the immediate performance marketing that I got the click and it turned into.
revenue, that's not how buyers are buying anymore.
one way that we're investing in that is on the AEO, GEO side, we're no longer, we believe that buyers are no longer searching, performance management software, Find Me Performance Management Software. They're searching in the LLM saying things like,
I'm a hospital with 5,000 employees. I'm looking for a performance management software that can solve problem one, XYZ. These are the things that I'm looking for specifically. So we're now writing content that isn't just, here's why we think we're the best performance management software. It's way more detailed than that into here's exactly why we think we're the best performance management software in these specific cases. Because I believe that's where.
searches have it headed, it's just going to get more and more specific, right? So we've eliminated paid search because we just don't think that buyers are, or we're seeing that buyers aren't buying that way anymore. And all that we were getting from paid search recently was just branded search, right? Which we can capture with our own brand, With our own organic listings. So we're really focused on those GEO searches that get really specific and creating content around that.
Lauren Luen (21:55)
I agree with that on creating the mind share and answering that question and creating that space for your brand before it even exists in the user's mind. think that really is that demand creation is the most interesting opportunity that marketing and brand has with AI. I found that when I was at Expedia, we used machine learning driven personalization to reach customers before they were actively shopping. So you're shifting the whole business model from being reactive to being proactive.
active
and you're not just creating, you're not just capturing the existing demand, but just trying to shape consideration. You're starting to create your own demand for people to say, I didn't even consider that before. it's more difficult. It's a much bigger challenge. It's far longer payback period. But if you can create that space, I think you're just expanding your TAM and the opportunities really are boundless then.
Allie Collins (she/her) (22:47)
Yeah, I feel really empathetic to, the startups that are just getting started. And CFOs are probably wanting to see that performance marketing like, I'm capturing the demand at the bottom of the funnel. When if you don't have a brand established right now, I really empathic to like, how do you do that and do it fast enough to get results for
a startup right now. It's like, that's where it all boils down to, you gotta have a really great product. Again, going back to fundamentals, the product has to, in a lot of ways, be something that sells itself by, creating advocacy, creating, people, rapid fans out there talking about you. Because that's the other thing that's feeding the, the AEO, GEO is
user generated content on Reddit, on G2, on all the places where people are out there talking about your product. And that goes back to like, it's really going to be challenging if you don't have a product that users love, right? And that's a huge brand moment everywhere.
Nicole MIlls (23:45)
Yeah, I will definitely say on the customer marketing side, the advocacy of our existing customers is priceless. You just can't get a better brand ambassador than a happy customer. And I think that what we really try to do as much as possible, we want to get their experiences and their words out in their work.
We are amplifying their own experiences and their advocacy. I really love in-person events where I can get customers and prospects together so that they can have their own organic conversations, not necessarily steered by us. If you have confidence in your relationship with the customer, you can have confidence in the interaction that they're going to be able to have with a prospect. I think that that is another aspect of it.
with brand health, you're not in control of Reddit threads where people get together and talk about your customer experience and your pricing and your product and uptime or downtime. Did this actually work for my use case? People want to hear from other human beings about what their experience is like with you.
I have seen really small brands really blow up based on influencer and customer advocacy, and social media, and forums, and things like that. So there still is the opportunity for word of mouth to really drive your brand. But again, it's the quality of the experience that they're having with you. You have to have a solid product, and your service has to be top notch.
And then I think also, we're in an era where that kind of thing can spread so quickly these days. We're not in an environment where you have time to smooth over a glitch in your relationships. You have one unhappy customer, right?
And then millions of people can know within the hour because of an exchange on TikTok or something like that. And so I think as much as it also gives us an opportunity, it's another way to really explode the brand across geos and across conversations, that criticism will also be just as immediate. So again, you're not going to get away from your brand responsibilities.
you're not gonna get away from having to have really good product market fit.
Allie Collins (she/her) (26:19)
Yeah, if anything, it's more important than ever, right? It's more important that marketing keeps a pulse on what product is doing, how customers are reacting to the product, what your pulse surveys look like. And the great news is that AI gets us closer to being able to synthesize that data than ever before, Like my rev ops team created an amazing report for us this week that really dove deep
on the closed loss side, why did we lose? Why are we winning? And really brought that forward in a way that we could use that to adjust our messaging. And we wanted to do a campaign to go back to opportunities that we had lost within the last couple of years. We were able to really tailor and personalize messages to those lost opportunities based on that data. AI was able to synthesize that, tell us, here's why we think we lost this. Here's what our point of view.
is saying today, here's new features that we've released since we lost this deal, and here's what we should do to go back to them with a fresh message. And we still are using the A.E. the human account executive, to go take that information, use it and craft the right message for the person and customize outreach, but they're really given the best source material that has all been brought together and served up on a silver platter to them.
bringing together the data, the insights and the right message crafted by marketing. That's where it goes back to those AI based GPTs and skills that I was talking about where we've trained it on our messaging. We've trained it on our persona. We can now merge those two things, the data and the insights with the message to craft and personalize in a way that we could never before. So those are areas that we really are seeing lift from AI.
Nicole MIlls (28:05)
Yeah, we are definitely seeing lift from AI in terms of the insights that it's able to give us about our ICP. And, it has also surfaced some unexpected new potential, areas, new, places where, we could find an audience, we have traditionally been a very e-commerce centric business, but.
we started to do some look back analysis on close one deals also. And we started to look at customers who initially we would have just thought, oh, well, these are bloopers. They had a niche use case for us. We were already in their considerations that maybe weren't quite clear how we got there. And we started to look and say, OK,
Are certain partners more likely to send these our way? Are these really disparate use cases across the Bluebirds? Or is there an underlying use case? For instance, is there a support use case that's common across these companies? They don't look alike on the surface because maybe they're different sizes, they have different site traffic, they're in different industries.
What AI is helping us do is to pull that common thread across what looks like disparate groups of customers. And then that is helping us figure out where we could target to get, how do we get more of them in? How do we make that a scalable, repeatable process? And so I think that that's one of the great things that we're seeing out of this AI-driven data analysis.
Joaquin (29:45)
100%. Well, we've covered a lot today from AI's impact on the ICP definition, the go-to-market execution, the risk of losing focus, the changing relationship between demand creation and demand capture, and the factors that will continue to create brand awareness and differentiate organizations. Before we wrap up, I'd love to ask you one final question. What is one...
principle GTM leaders should keep in mind as they introduce AI into their strategy and operations.
Allie Collins (she/her) (30:19)
think if I was to sum it up in one sentence, I would say that the real differentiator right now is judgment. And if you're a marketing leader right now, there is so much capacity to create so much. The thing that is going to separate you is knowing when to use it, knowing what good looks like and what you're trying to achieve and knowing how to prioritize that. And all that comes down to still is just judgment, Judgment, taste, and the ability to
Joaquin (30:47)
taste.
Allie Collins (she/her) (30:48)
really stay focused on what matters and what's going to move the needle.
Joaquin (30:51)
Yeah, taste 100%.
Lauren Luen (30:54)
say additionally and it also only comes from the human side
of the equation is thinking about the entire revenue flywheel. traditionally we've operated, many companies operated, it's marketing, then it's sales. And we each have our piece of the pie and we focus on that piece of the pie. But thinking about that entire revenue flywheel of how marketing feeds sales, how sales data feeds the model, how the model shapes the next campaign. And designing for that entire loop and not just your piece of it is really, really critical. Nicole, I'm going to echo you.
words I believe early on you said that you had a paid media person on your team who said that feel like a developer. That's what marketers need to be doing in the next few years is thinking like a system architect getting all of the different functions to agree on the same set of accounts whatever it may be working from that single source of truth so that we can inject AI everybody the full revenue life flywheel operate from the same page so to speak.
I think for me that's the big one in addition to the judgment. We'll never get rid of the judgment. AI will never be able to replace that.
Nicole MIlls (32:00)
I think that it helps to think of this as an innovation practice within your company. And so that it is not just how individuals or disparate or separate teams, I feel like disparate is my word of the day today. But I think don't think of this sort of AI adoption as a scattered.
thing that happens across your organization. It's really important to share strategy. It's really important to have a way that your teams can iterate and then learn from each other what you're trying, what you're experimenting with, what worked, what didn't, what they may be hearing outside of your organization, but what does not work within your organization.
because you all need to be learning from each other's trial and error. And you also need to be trying to figure out how can you efficiently make your organization faster, stronger, better, smarter. You want to be better informed by the data. You want to be making strategic application of these tools and processes. So there needs to be a practice of communication.
across teams. So I would just say, think of this as a cross-functional growth and innovation process for your company, as opposed to just kind of scattershot efforts, because that is going to help you basically maximize and really accelerate as an organization.
Joaquin (33:35)
Yeah, and an AI I believe is an amplifier of the good practices and the bad practices. So yeah, whatever you do well, you probably the AI will capture that and AO and everything will capture that but also will capture the bad practices. So yeah, we need to I think the technology alone doesn't create an effective GTM strategy organizations still need
clear priorities, reliable data, aligned teams, strong customer understanding and the judgment, the taste, where to focus and decide things. Thank you again for joining us today. It was a great conversation and for all the ones listening, please.
Stay tuned for upcoming episodes and give us a review if you like this episode. Until next time, thank you so much.
