Don't Get Left Behind: Your AI Growth Playbook

I know if you say that this is crazy, I will take it, because I joined HubSpot January 2020, a little bit of didn't know what was going to happen, but a lot has happened. And I would say that beyond the COVID years and dealing with all of that 2022, specifically November 2022, when ChatGPT came, there was a big shift. And you and I have seen this. It's a platform shift. It feels overwhelming. It feels like things are changing every single day. I do have a couple of slides I want to share, just to kind of walk us through where we are. This is what happens during a platform shift, and that's what we're going through in the industry. Every 15 to 20 years, we go through a platform shift. And when we go through a platform shift, a new technology emerges. People start building many times over, building. And then there is a question of who controls that technology, and then there's a question of who wins and who loses in that new technology wave. It's as simple as that. We've now seen it through PC, we've seen it through Internet, we've seen this through mobile, we've seen this through social, and the same pattern follows, right? So if you take Internet, when Internet emerged, was completely new as a technology, and you saw a level of overbuilding and building, which is kind of happening right now, right? Back then it was routers wans lans. And I know you remember this, there was a point in the early 2000s where 97% of the fiber that had been built was not used. It was called black fiber. That was a level of overbuilding that happened. And then the new technology emerged. Google became one of the gatekeepers of search. And new business models like Doordash, like Uber couldn't have emerged without the combination of Internet and mobile. And new winners and losers emerged. I think the same thing is happening with generative AI. Obviously, it's a new moment and there's a lot of building and I would say overbuilding that is happening in terms of the data center capacity. And that is going to lead us to a place where there will be new winners and there will be some, some losers who are not moving quick enough. I think that that's the same pattern, Steve. But my observation is two things. One is that it's happening much faster than any of the previous cycles. What we saw happen over eight years, 10 years, is now happening over three to five year period. And everybody's got a megaphone and everybody is on a podcast, everybody is on X, Everybody is on LinkedIn, everybody's got an opinion. And so it feels even more chaotic to navigate through what we've seen as a platform shift. Yeah, absolutely. And it's there for us all to see and use too. Yep. And once you immerse yourself in it, you can see the, in a sense, the scaling up of the way you're going to interact with these new tools, let alone how your organization is going to respond. Absolutely, absolutely. Yep.

So just talking about people in the room and how they're responding, how do you see the response so far by Australian customers? And should they be thinking, well, how should they be thinking about their investment in AI and the outcomes they should want for it? I first of all love the way you frame it, which is what should they be doing for the outcomes? Because it is about technology driving outcomes, not technology for the sake of technology. But let me ask you this. I can see most of the room. How many of you use AI every single day? Okay. How many of your organizations have seen significant growth and outcomes because of AI? Okay, okay. So about like, you know, half, I would say everybody is using AI, whether it is an LLM or some kind of tools, and there's a slightly lesser number or percent that has seen organizational transformation because of AI. That is the state of adoption and that is the state of transformation right now globally. Right. And you asked specifically about Australian customers, but I think globally, what we are seeing is that everybody is using AI. Everybody is, you know, got at least a couple of LLMs, a combination of some tools in their daily usage. But we're all trying to go from what I call individual AI productivity to institutional AI productivity. That means individual AI productivity is like you getting up in the morning and you're writing an email and now you have a better thought partner, maybe some LLM that actually understands you, your style and can give you a better email. And then there is institutional AI productivity which actually requires a lot more context because the change between individual and institutional is you need to get the growth context of the whole organization. Your best campaign manager, how do they pick the best campaign? Your best sales rep, how do they think about the best deal to work or how to save a deal that is not moving forward or your best support person and what should they care about? That requires growth context. And so I think that's the stage that we are in. I will say that specifically calling out some Australian customers, I know some of many of them are in the room, but there is good adoption and movement towards this. You know, Hungry Hungry is one of the customers. I hope you're there in the room. Very interesting in how they have completely reimagined marketing with Loop, which is the playbook that we have been talking about for a while as well as, you know, customer agent. They're resolving tickets using that Cannibuild is another Australian customer. Again leveraging AI in almost every aspect of their grow to market and going beyond the experimentation stage to scaling with it. And my own favorite is Wilderness New Zealand based company, Beautiful country. And they are actually in the hospitality as well as helping folks kind of figure out how to spend time in New Zealand. And they are also adopting AI in almost every part of the go to market. And I think that we're in that process of translating real productivity gains into go to market. And it's a fascinating time to be here.

It's interesting when you talk about those organizations. I would pretty well guess without knowing many of them that they're well led. And what I mean by that is the job we all have as leaders to get the institutional benefits of AI is a leadership challenge. It's about cross functionality. It's about being explicit from the top down as to what it means to be successful and what actions are expected across the organization. So I think that's the challenge because it is much easier to adopt individually than collectively. Actually we should going on to something else that I think is really important here is just Some of the best use cases that you see that are driving results and how should organizations that are beginning the journey, how should they sort of tackle it?

The answer is, what are your company's goals? What are your team's goals? Because while AI is a new platform shift, and of course it is something that everybody wants to have a roadmap, it has to start with your company, your goals, what you actually want to reimagine, and not the other way around. So I think almost every customer or prospect conversation that we have, we start with, what are you trying to drive? Where have you seen the biggest challenges in terms of how you want to grow? Let's then identify the use cases of what that looks like. So it really has to start with you identifying the biggest challenges in the way it's new ways to solve old problems. That's what AI is all about. But having said that, we are now three and a half years into AI and there are a set of very specific use cases that can help you unlock growth. And now I wanted to share and I'm going to flip to what we see as AI Customer journey. Again, you wouldn't just start with the entire journey, you would actually pick one or two areas and that makes the most sense to your business and what you want to solve. And let's start with aeo. I would also plug Asia Frost, who is speaking today. I would really plug her whole session because she started experimenting with AEO two and a half years ago for HubSpot. And what we found is that there is a completely new way in which you need to show up in, in the answers that LLMs are providing. Right. We've made it a science to show up in Google searches and blue links. And how to show up in blue links actually came up. But Then now almost 60% of Google searches do not end in a click, which means you have to find diversified channels. And AEO and showing up in LLM is one, and that's a place that we really encourage people to think about. And Asia will talk a lot about that. We're also finding, talking about old problems that we've had. It's pretty difficult to understand who your ideal customer profile is and how to reach them at scale. And so a lot of our customers who are trying to kind of expand their growth, they start with the data agent and prospecting agent. And in super simple terms, data agent will enrich all the companies that you have within your CRM and the contacts that you have within your CRM and it will get the latest information so that you have an ideal customer profile matched TAM so that you can expand there. And then what we are finding is prospecting. Steve, I don't know when you started in sales. I started in sales. The difficulty was the first time I got I had like 500 accounts and it was pretty hard to cover 500 accounts. You're going to go and look at like 10 case and 10 queues and actually find information about every single account. Now you can do it with AI. That's the thing that AI has made super easy. And so we find that prospecting agent, you can actually identify the right intent signals and then from there you are able to send personalized email based on your specific company and your specific problem that you're trying to solve. And that means better open rates. And so I think like in the sales arena we are beginning to see that. And then again talking about old problems with new solutions in sales, the hardest thing was trying to take notes during a call, entering that information into a CRM and then doing a follow up. You just didn't have enough hours in the day to be able to do that. Now what you can do is just have a bot listen to your conversation and tell you what the action items are, even give you an email to send. And that makes it much, much better for reps to focus their time and energy. And so I think those are really the top use cases that we're beginning to see from a sales perspective. And then the last thing I'll finish off with is customer agent which is support. In fact, I think one of the first use cases which found product market fit is the customer agent where you can resolve questions using your knowledge base, your history of how you've responded to your customers. And we now have over 10,000 customers at 70% resolution rate, resolving tickets and therefore scaling using AI. So some of the handful of use cases, but my guidance to any one of our customers and prospects is basically start with your problems and what you are trying to solve, where you have challenges and then pick an area and then go deep in that area. And once you scale that and once you get confidence in that, then you can pick other use cases. This is awesome. And this is also in a sense about raising the bar on the quality of your sales and go to market effort. Yes. And I mean we can all see that from our day to day experience how the sales experience we have are not as good as they could be and the connection there to growth is just undeniable. So that's wonderful, good stuff in terms of going to market org structures. How do you see them changing and what does that mean for the people that leaders should be looking to bring on board?

Yeah, I think it's a completely different aspect and glad we were talking about that. So what is interesting, Steve, is that when Internet era came, what happened is that all of your buyers were searching for information. And therefore what happened is that marketing and sales started to blur because every single buyer of yours, they searched for information, they already got information and by the time they actually came to a salesperson, they had read enough about you on the Internet. And what that meant was that the line between marketing and sales started to blur. Marketeers needed to get much more personal and personalized in terms of the information that they were sharing. And salespeople needed to almost act like marketeers because the lines were blurring. And that happened in the Internet age. I think what is happening right now and what is very interesting is that sales and customer success, the lines are blurring within the go to market organization. That's because with AI you want to be able to get the value and immediately expand the value of AI. And it's almost matter of minutes that you really need to see the value of an AI use case or an AI agent. And that needs to expand. Which means the handoff between your sales team and your customer success team. It first of all cannot even be a handoff. It just needs to be this continuous process of helping customers get value. And so I think the more fundamental change that's happening with the AI era is CS and sales. The handoffs are really blurring within the go to market organization. One of the things that HubSpot that we did coming into this year is we kind of moved sales and CS into the same org and we want that team to move faster, be able to present ideas during the sales cycle to customers, and then make sure that the value is delivered really quickly during cs. And so I, I think that over the next two to three years we're going to see that handoff change. But going to maybe the question which is what does that mean for leaders and how should they be thinking about hiring? It's a pretty transformative time. And what we are finding is that as these lines are blurring, it's much more about having people that are curious that are leaning forward into change versus fearing the change itself. And there are also builders that are experimenting with the technology and learning with the technology. And you and I were talking about this in terms of how leading through a time like this is much more about navigating change. And so I think what we think about is curiosity, experimentation, a learning mindset, being a learn it all. Those are the kinds of things that we need to hire for.

Absolutely, absolutely. You're talking about hire for culture and a mindset for change. Yes. Which curiosity goes right to the heart of it. The other thing, I think for all of us, it's a big thing at the center of this is our ability to want to demonstrate learning at the highest level, I think, which is seeking feedback from those around you. And also being open to what you don't want to hear is a really important element of that, particularly as you're going through these significant organizational changes or trying to deal with things that nobody knows the answer to. So mistakes are going to be made. How are you and how are others going to react, given that mistakes actually are the journey? Make no mistake about that. That is the journey. So how we react and respond and how we treat each other within customer success in sales, it's really going to come to the fore over the next few years. And it's something. Everything we're talking about is something we've been looking forward to for many, many years. How do you get customer success and sales to work better together? And it's something now that is real and a real opportunity for us, given what AI is providing.

Absolutely. And I like what you said, mistakes are the journey. And one of the things that we've encouraged our teams to do from a mindset perspective is really the experimentation mindset. And start with a hypothesis, prove yourself right or wrong within that hypothesis. It doesn't mean you're wrong. It means the hypothesis was right or the hypothesis was wrong. And encouraging that and being almost celebrating when you prove something wrong as much as you put prove something right is the kinds of mindset that we need. And that's a big shift as we navigate through this platform.

Shift sure is. We might talk a bit more about that later. Yeah, I want to move to something which is happening out there, which is people like me starting to code using Vibe coding, and this change is happening where we think the end of the engineer is near and all this crazy stuff that people are talking about. But do you think that this shift or the fact that AI makes it easier to write software, build products, what do you think it means for this whole question of build versus buy that organizations are going to have, and where do you think a platform still wins today? I love this question. I mean, everybody is Vibe coding on the weekend, right? Everybody is wipe coding. And so the whole conversation that's happening within the industry is, you know, coding has gotten easier, so where are you going to apply that? And you've been in the application phase for a very long time. And you know, at HubSpot, we've lived in this for 20 years. We have 3,000 engineers who live and breathe in, you know, agentic coding. And we've not vibe coded one core application because one part of it is writing code, but the rest of it is maintaining that code. It is integrating it with 20 to 50 other applications that we have. It is making sure that you're standing with the best practices of today. If something is changing in aeo, you want to have that reflect within your solution, the Agentix solution. I think there's a lot of difference between your ability to code versus your ability to have a scalable system. And so I do think that the build versus buy debate, the core of your organization's growth and maybe a couple other areas, you're not going to vibe code your payroll system, you're not going to vibe code your supply chain within the core ERP systems. And those areas you're going to continue to buy. And, and then on top of that, you probably will drive agentic automation. And that's what we are beginning to see. And one of the key things that from a HubSpot's perspective we are seeing is that also AI output is very different from AI outcomes that you can drive. And in order for you to drive output, think of an output as a blog post that you can write or an email that you can write. Now, does that output actually drive growth? Now in order to do that, you actually need your history of emails that you have sent to your customers, which competitive value proposition wins and which ones do not, how to represent your brand. That is the context. And when you give more of that context, then the output translates into growth outcome. If you have a very clear prospecting email that knows your company, knows your brand voice, knows how to represent you in addition to how you compete and win against your competitor, and you can send an email, that email gets a much better open rate and therefore can help you win more deals versus an email that you get generically. And so there's a lot of difference between just a generic email versus the ones that can actually drive outcomes. That's how we think about it. There is a place for Vibe coding, but it is much more of taking the context that you have within your organization and growing on top of it. And then there's a place for overall set of applications and you'll all be

faced with lots of people coming to you saying, look, we can do this, we can do that. And I always say there's a. A great way to follow up an idea, which is to say, so what now what? Which is, okay, so you can code this. So now what does that lead us? And I had that experience myself with something I just knocked up, and I looked at it and I go, well, this is great that I've done this, but where do I go from here? So I think that's a really important point. There's a lot more to the context and how it really plays into these ideas will play into the most important for your organization. And talking about organization, let's talk about HubSpot. You are and have been leading through a massive internal change. I think you told me that there's nothing that hasn't changed, given what is going on. So what are you changing and what are some of the, let's say, the most significant lessons you've learned in leading that change?

The answer to that question is like, what is it that we have not changed in the last three and a half years? And I do mean it, because we Talked about the November 2022 moment where ChatGPT came in. We had a plan for 2023, and we had just set that plan in motion as we came into January 2023. And we said, well, it doesn't work anymore because there's a big platform shift. And the question that we asked ourselves as a leadership team was, do we think that this change is incremental or do we think that it is a step change? And the answer, even then, even when the capabilities were not as well developed as it is today, it was very clear that it is a platform shift. And therefore the first thing that we started with was actually changing how we build our products. And that was a huge change. And I'll kind of like, you know, maybe if this is helpful, walk through. How we build has transformed. And the first stage for us in terms of building the product was Copilots. And we know back in 2023 it was copilot and assisted coding. And we started with using GitHub Copilot, and we were leveraging copilots for a little while. And what we found that the reliability of our product was not impacted with assistive coding. And so it gave us the confidence from an organizational perspective, and it gave us the data that we could continue leveraging that. And then what happened in 2024 is that Agentic coding just became incredibly good. And we saw A step change in the capabilities of the models. And so for us, the second stage was really leveraging cursor, leveraging CLAUDE code for agent encoding. And we found fairly big improvements in terms of engineering velocity, in terms of engineering productivity in every one of the metrics that we were tracking. It was like pretty big step change in terms of how we were building. And then what happened was that all of this off the shelf coding agents, they were not optimized for the HubSpot developer environment, which means the very specific libraries, the very specific ways in which we build and what our developers need to access was not available. And therefore we built an entire infrastructure for a containerized environment that we could optimize specifically for the HubSpot developer. And that was the phase three. And when we did that, it is now where all of our agents speak the same language, they access the same data, they access the same tools, and they are able to get to the same growth context that we've built. And that has really enable like 100% of our developers are building using our technology on top of the agent decoding. And that has meant that our pace of innovation has been really, really accelerating over the past couple of years. In addition to that, we've changed how we grow, right. And I talked about Asia and she's fantastic. Our marketing organization is fantastic. And we, one of the things that we started in terms of our own growth is actually a set of agents and assistants that we built internally, right? And the first set are demand agent. So the demand agent actually for us, it builds up our ICP and it expands the enriched contacts that we can actually access. Then we started with an inbound agent. And so if someone comes to our website today, 82% of the questions on our website are handled by this inbound agent. We've given it our pricing information, campaign information, how to qualify, how to provide competitive information to our prospects and customers. And so a lot of that has transformed. And aeo, which we talked about a little bit before, so the top of the funnel and how we think about marketing has now become completely agent first. And then when you go into the sales cycle, prospecting agent obviously allows for a much more personalized outreach. And we started using that a couple of years ago. And that meant our BDR productivity, our rep productivity has improved pretty significantly. And then, you know, what we also found is that our reps, they like having an assistant, they like to have a conversation to be like, tell me what the risk of this deal is, tell me what I need to be looking at in terms of closing it this quarter versus next quarter, what is the stage the deal is where I should be giving much better examples and support for the deals. And so we now have those types of assistance in the sales process. And we found that the combination of both the prospecting agent and the assistants in the sales process is, is improving our win rates and productivity. So on that we've seen a lot of change. And then in terms of our support, 60% of our support tickets are handled by customer agent. And what we have found is that we could probably bump it up more, but we don't want to sacrifice the customer satisfaction. And so we've really balanced what that looks like. So, again, case in point, almost every, every single aspect of how we build our product and how we continue to grow has changed with AI. And that is also because of how our teams have really embraced and experimented with AI internally.

And if you said, what's the one thing in terms of your experience of going through all this that you'd want to share with everybody? It's really about having a. In an explorer mindset. You said this earlier. Mistakes are the journey. And I think that resonates deeply with me. One of the things that we've been talking about overall within the company is that in the previous decade, it was almost like a map. You had point A, point B. There were known playbooks, there were known plays that you could take to grow through that journey. But right now it is experimenting, it's learning, it's. It's making mistakes, it's pivoting very quickly and being very agile as an organization and as a leadership, to go through that. And that has been the biggest part of the journey. And that's also the more fulfilling part. It's a bit freeing to say nobody knows the answers and therefore you can only learn by doing it and by experimenting. And the faster you learn as an organization, the more you're going to get the results. And so that has been part of the journey. Yeah. And look, I really believe that individually and collectively, our capacity and capability to change is by far the most important thing you need to be thinking about and developing in your organization. And it requires all those attributes that Yamini just mentioned. So it's a big leadership journey that we are all on. Yamni, thank you so much for being here and sharing your experiences with us. It's fascinating. It's exciting to see where your organisation is going. Please join me. Thank you. Thanking Steve. Thank you so much.