Business Model Innovation & 
Growth Strategies

Julia Nimchinski [ 00:57:32 ] We’ve got really good engagement in our Slack. Please everyone follow our esteemed panelists such a pleasure. Hopefully we’ll feature you again in February. We’re coming back quarterly. So, yeah, we are transitioning to our next panel, business model innovation and growth strategies. Welcome, Lara. Hi, everyone. I want to make sure that we’ve got all of our panelists here. I think we might be made it waiting for a few people. We’ve got Beth, Tommy… Yeah, just need a couple more minutes. Bringing them on. How’s everyone? Very awesome. How are you? I’m super excited for this one. Actually, the most tangible and practical out of all of the panels for GTM. So, yeah, let’s do a quick round of introductions. All right, everyone. So, I’m Lara Shackelford.

Lara Shackelford [ 00:58:33 ] I’m the moderator for this session, I’m SVP of Growth Marketing and Revenue Operations at iCapital. I’m Chairman and Founder also of a company Fideri AI that helps with AI strategy for AI field strategies for marketing customer experience. And I have background at Intel and Microsoft. I’m currently coming to you live from Oxford in sequence because we’ve got our black tie dinner tonight after this. And and I’m earning my Master’s in AI here. So, that’s me. And we also have I’ll hand over to you Tommy to introduce himself and then we can go down the line. All right. Good evening, everyone from Barcelona. I’m Tommy O’Brien, Chief Sales Officer at SEMrush. Really excited to be here. Okay, Beth. Hi everyone. Beth Bauer. Founder and CEO of Poseroy that comes from intentionally creating positive returns.

Beth Bauer [ 00:59:37 ] And I’ve been thinking about that with regard to data and AI for over 35 years. Some of my background is in big data as a product through companies like IQVIA and Merck known as MSD outside the US. Super excited to be talking with everyone today. Great. Welcome Beth. Russell, over to you. Hey team. I’m Russell Sherwin. I am on a sabbatical right now while I’m on sabbatical. I’m running B2B tracks, a consulting firm. I’m teaming with Force Management as a facilitator, and I like to think of myself as a pragmatist. With that said, I was writing neural network code about 30 years ago when I was not on sabbatical. I was Chief Revenue Officer for a fast company called FPX and Chief Marketing Officer for Watson Commerce at IBM. Excellent.

Lara Shackelford [ 01:00:26 ] Okay, Brandi, you’re next. Wonderful. So first off, I’m loving the sequence and I applaud them whether there’s a dinner happening or not. I was like a panelist in sequence. Yes. I’m here. Pleasure to connect with everyone. I’m Brandi Sanders currently CMO at Apramore Process Mining Company. Super excited to be a part of this panel and bringing a very non-traditional background: coming originally from creative multimedia and all of the softer creative arts, including theater, television, film, and media industry. And then eventually deeper data analytics things like data lakes, working with companies like Blackline, leading them to IPO, and then other wonderful organizations like Sony Music, Etsy, etc. So super excited to see some familiar faces and some new ones here today. Well, we’re thrilled to have you Brandi, and let’s let’s wrap it up here with Paul Kuhn, buddy.

Paul Kühne [ 01:01:24 ] Sorry, my background is a little screwed up, but my name is Paul Kuhn. I’m based in the US. And I’ve headed up marketing and sales for about 20 years. I’m heavy social impact, bent on educational technology, but also industrial and manufacturing CMO and marketing and sales leader mostly in B2B. Great. So we have a great group of panelists and we want to get right into the content because oh, there’s Julian and we wouldn’t be complete without you. I’ll let you introduce yourself. Sorry, I’m late. I’m always fashionably late. That’s the Frenchness that speaks. Hi, everybody. Julian. I very happy to be here. Marketing exec coming from the sales tech side of the house: Salesforce, Gong, and Clary. Excellent.

Lara Shackelford [ 01:02:12 ] So as you all know, we’re here to talk about what the future looks like in 2025 and talk about global AI and and how we look at innovation and growth for 2025 leveraging AI and we can’t do that without talking about the global landscape. Right? So I wanted to just take a quick minute to share some things that we’ve been thinking about here while I’ve been at Oxford working on my diploma in AI for the week. And one of the things we’ve been thinking about is, you know, what how does the global landscape change and where does it stand today? And how do we as organizations moving into 2025? We’re all hopefully we’re all wrapping up 2025 planning. I imagine a lot of you are in your, you know, planning on Q5 planning because that’s more common than it should be.

Lara Shackelford [ 01:02:58 ] But as you look to 2025, we have to think about a couple of things. One, the European Union right there. They, you know, the EU AI Act came into effect in August of 2024. It’s really going to start, you know, having its full application though in August of 2026. The EU is taking, of course, a highly regulated conservative approach and their aim, of course, is to have a very comprehensive and regulatory framework both for AI development and use. Which is important because you know, if anyone thinks well, they don’t operate in the EU or their company is not based there. It’s use within the EU. So lots to pay attention to there. And then we need to consider England separately, or I should say the UK, right?

Lara Shackelford [ 01:03:46 ] So post-Brexit the UK, you’re going to a lot of people be feeling enthusiastic because the UK has a chance to set their own standard and their own approach and be less regulated. If they choose to do so, that’s not a choice. They’ve made yet. They’re looking to potentially move faster and AI and development and implementation, but the stage is set to see where they’re going to go. And then of course, we have China right with that. China has been adopting a very insular, inward-focused approach to AI development. We have limited information about their specific strategies and regulations, but it’s worth noting that five of the top 20 universities and AI are in China. There’s a lot of great work happening there. We presume, and so we’ll see what unfolds there over time.

Lara Shackelford [ 01:04:36 ] And then, of course, in the US, whether whatever your politics are, we’re not getting into politics on this, but the recent shift following our elections means that we’re moving from a more cautious innovator in the US to becoming less regulated and we’ll see a faster-paced approach to AI in the US. We’re going to likely focus more on domestic AI development. Less on the global part cooperation and there will definitely be a you know, a focus on efficiency with Elon Musk being a leader in AI who also of course has just been appointed the co-leader for the Department of government government efficiency. So, with that lens as we look to 2025, we need to think need to think about our global approach right and how we’re going to take those business models into account and adjust for those.

Lara Shackelford [ 01:05:28 ] Especially as we apply AI to become more innovative, drive greater efficiency, and ultimately more growth. So, those shifts might influence a couple of things: the need for flexible business models that can adjust to the different regulations that will come into effect; opportunities to for companies to leverage different approaches regionally. And then there’s a potential for new partnerships that will come out of this across borders and ways we haven’t seen before as these dynamics are changing. So, I want to stop there and ask panelists based on you know what I just shared in your point of view, experience. What are my thoughts on the kind of the global view how I’m approaching thinking about our global organization for 2025? That’s over to me.

Lara Shackelford [ 01:06:18 ] So I always think of it as we’re so connected quite frankly now, that whether you’re US-based or not, you’re going to be impacted by what’s happening globally, whether we like it or not, and GDPR along with CCPA in California combined really end up impacting and driving all the things that we’re thinking about. But that’s a perfect tie into how I think about business model innovation, quite frankly. There are several different components: the external, the internal, your customers, and then how do you bring that all together? And I was actually thinking that the number one thing that I wanted to bring out to people today is something called a PESTEL analysis, which AI just lends itself so beautifully to. PESTEL is an acronym that stands for political, economic, social, technological, environmental, and legal.

Beth Bauer [ 01:07:07 ] And that base of legal at the end, I think, is a key component because what I have seen in order to actually do extraordinarily well and accelerate with AI, you need to be bringing legal and regulatory and be compliant by design. That means you need to be bringing legal and regulatory and be compliant by design. That means thinking through and bringing all of those people across that entire PESTEL on the journey with you so that when you are ready to innovate technologically, everybody else is ready to accept that innovation as well. So AI will allow us to be able to better understand our world rapidly across those continuums. And then we can take that and go back to our internal business capabilities and begin to see what are the processes that we can accelerate internally by bringing AI into the picture, beginning to understand what decision-making we have.

Beth Bauer [ 01:08:00 ] I, again, bring that back to the legal component because legal, for example, a report just came out from Reuters earlier this week that the legal teams are actually responding that they don’t want to be touched by AI. But quite frankly, if we don’t bring them along on this journey, we’re not getting anywhere because they’re the barrier that keeps us from moving forward. And I say that with the flip side of, we’re not going to be able to do that. We’re not going to be able to do that. We’re not going to be able to do that. We’re not going to be able to do that. We’re not going to be able to do that. Governance is key, which is why we want to bring them at the beginning because we want to be compliant by design.

Beth Bauer [ 01:08:30 ] We want them to be thinking through that with us. And that opens us up into the entire: how could we begin to create blue oceans to get at new customers? And then how could we begin to take the totality of these things back to our decision-making and allow AI to help us to actually identify the decisions that we’ve been making all along, whether we could articulate them or not, but now we can see them. Visibly and break down the silos across our organizations and partners so that we can actually transparently move forward and say, ‘This is what we’re coming forward to provide value to our customers, to provide value to our shareholders, and to provide value to our employees.’ I love what you said about compliant by design.

Lara Shackelford [ 01:09:15 ] That’s definitely how we think about it. And it’s the right approach as much as we can, right? So we’ll be ready. And then consider things as they come up. But Brandy, I was watching your faces as Beth was talking, and it looked like you were eager to jump in. And by the way, folks, everyone on this panel is excited to talk to you about this topic. So I’ll call people out to talk when needed, but also people will jump in, right? So we’ve got a lot of interest here. So expect that too from the next minutes that we’re together. This is where the X Theater Major stuff really comes in handy is because it’s easy. It’s intense signals, if you would. No. So first off, Beth, that is so eloquent and well put together.

Brandee Sanders [ 01:10:01 ] And compliance, which people often view as a burden, is actually now turning into a necessity. And I could literally go into everything from automated alerts, violation, detailed root analysis causes, linkage with process models. There’s so much technical stuff there, but it’s so messy with the human element. Because quite often, I think chat GPT, gen AI, AI, honestly, over the last three to five years, and possibly even further back, has created this buzz, this kind of like hyper energy that’s traveled through organizations because everybody rolls over to the next tech bro who’s like, ‘this is the tool.’ And we all wake up and go buy the thing, and we install it. And then legal, of course, at the bottom of the pyramid trying to protect us all, turns around and goes, ‘who’s in charge of that?’ Who keeps it in the guardrails?

Brandee Sanders [ 01:10:54 ] And you have sales looking at marketing, and marketing looking at sales, and sales looking at IT, and IT is like, ‘I quit.’ And the lawyer burns out and leaves. And so it’s this lovely idea, this concept. But the actual execution process and operations of it are quite often messy. The data is bad. Things are built on something like a Jenga from 1985 on some server. No one has any ideas in the middle of Iowa. There’s all of these intricacies that I think we kick right over with the concept. But the execution, particularly from the compliance side, Ben, which I’ll, of course, be obsessed with because Appamore is process mining, and we just launched Compliance Center.

Brandee Sanders [ 01:11:30 ] But there’s this idea that what looks good on paper is always so much harder to execute within organizations, especially if they’re in hyper growth mode, they’re on the startup side. And conversely, legacy organizations that are glacially slow to change. So there’s a human element here, not to push that button bingo on AI human hybrid, but I’m going to do it. There’s a emotional element as well, which is like, who owns this? Because no one’s going to want to touch it. Look at Dora, GDPR, look at the fact that there’s now litigative measures to put people behind bars if they violate certain things of compliance at an executive level. And it’s a bit of a hot potato. So for me personally, when I hear the concept, I’m like, that sounds so sexy and wonderful, and it’s great.

Brandee Sanders [ 01:12:14 ] And then how do you do it? Starting on page one, who’s in charge of this bad boy? Who’s creating the guardrails? Are we progressively going to push it? Like the recent administration, or are we more conservative because we don’t want our CTO behind bars? So it’s this lovely balancing act that I think everybody will do differently. And we’re at that beginning of that maturity arc. So I’m super curious to see how this plays out. But I agree, compliance is key. And this is like no longer an if-then-that bullion that is optional. It now, at the scale at which we are adapting in AI, automation, workflow, everything, we’re going to need this to be automated. And you’d have to have those systems in place before you’re entering your PII, your customer data, all of that valuable information, which I think more than ever is at risk for vulnerability.

Brandee Sanders [ 01:13:01 ] Hey, Brandy, I’m going to give you two points for putting the word bullying in there. I thought that was awesome that you worked that in. I want to throw a question out to the three of you or anyone else who’s been talking about compliance. And I’ll be honest, I have not dug into the compliance regulations here. And personally, I’m a little worried that we can’t put Pandora back in the box here. That said, if China and the U.S. Are going to be able to do this, I’m going to have to ask you a question. If the U. S. is wild, wild west with AI and the EU is getting heavily regulated, is that putting the EU nations at a competitive disadvantage?

Russell Scherwin [ 01:13:33 ] How are nations thinking about the impact of regulations around what the global landscape will look like in 20 years? Oh, I have thoughts. And I’ll say them really quickly and get the hell out of the way, but it’s a spider web. This global market is inexorably tied, right? Even though we want it to be its own thing that you’ve got a strong parent who’s like, I’m sticking to the rules. You’ve got your kid out in the playground playing with the other person at that meeting, or you’ve got this engineer over here in Estonia, or you’ve got this person over here in India, and you know how difficult it is to control them at both the individual level and the process level. So I think that when one part of the spider web pulls, the other part will pull back.

Lara Shackelford [ 01:14:18 ] I think that individually as units, they’ll try to control these things. But to your point, the toothpaste is literally out of the tube. And so it’s going to be pew, pew, you know, a little bit of the wild west there with things being pulled in lateral directions across the markets. Other thoughts? I mean, Larry, you’re taking a PhD or a class in AI. It sounds like you’re deep in deep in the woods here. What’s the what’s the thought around compliance? Is it right or wrong? And how does it plug into global power? Yeah, I think it’s, it’s, I just go back to what Beth was saying about compliance by design. You know, we, we talk a lot about ethics and AI,

Tommie O’Brien [ 01:14:58 ] and it’s not not the same, but ethics and compliance just go hand in hand, you have to design for compliance at the outset as best you can, you design for ethics and think through what potential scenarios could be as best you can, and you have to allow space for the unknown, because there’s so much unknown here. And that’s not a very direct answer. But that’s, that’s, that’s the highest level of how we’re thinking about it. I do want to make sure, Russell, that we give Tommy a chance to Tommy, you’re sitting in Spain, right for this call, unless you’re, you’re traveling. And so I feel like you should give us a view from the right from the field. Yeah. Hello, everyone from Spain. There’s a lot to uncover there.

Tommie O’Brien [ 01:15:42 ] I think the most interesting part from a revenue standpoint is over the last few years, there’s been this big drive towards consolidation that drives compliance, but it drives the ability to effectively leverage your data. And now that seems to have gone completely out the window. We’re going to buy this AI tool for content, this AI tool for search for IT compliance. And I’m really interested to see what happens with CTOs in the next 12 to 18 months, because it all seems well and good. But when you try and integrate it, and you try and leverage that data, I got a chance over the last two days to join some of the sessions. And, you know, one of the most common themes was, you can achieve remarkable, remarkable things, but it is the data that you put into it.

Tommie O’Brien [ 01:16:26 ] It’s your ability to ingest it, leverage it, execute it. And some of the things that we’re most focused in on, on a sales side right now is just diversification of our revenue streams. You know, we’ve seen, you know, over the last few years, it’s diversification has become absolutely essential for, for any business at all. And things like strategic partnerships are great; things like product development, but they’re incredibly risky. And take time and effort. Whereas we’ve started to see some really nice uplift from leveraging AI for new markets and new verticals. So prior to AI, you would have done what an acronym that I’ve worked with is MACARA, which is market availability, real-time analytics, and customer accessibility. So you’re doing everything from trying to understand GDP, population, search maturity, online maturity.

Tommie O’Brien [ 01:17:21 ] You’re then trying to leverage your own real-time analytics. So you’re trying to understand, well, what are customers doing with us today? What are the spending? How are they leveraging our technology? What’s their attach rates? How long have they been with us? And then that customer accessibility, trying to fundamentally understand if you’re an online business, what’s the payment success rate look like? Like that’s very different in LATAM and APAC versus US. What’s the language component? What’s the currency component? And you go and work with a consultancy that costs you an arm and a leg, or you’d work with your REVOC. And you go and work with a consultancy that costs you an arm and a leg, or you’d work with your REVOC. And it could take several weeks to do.

Tommie O’Brien [ 01:17:56 ] If you’ve got your data in the right area, that could take you hours. And now all of a sudden you’re getting to build a really strong pilot to understand what new markets you need to go into to diversify or just continue to accelerate growth and vice versa with new verticals as well. So I think the power is absolutely essential. I think the consolidation play is going to come back very quickly when people realize how challenging it is to actually leverage these technologies, but done right, we’ve been able to move into new markets so much quicker than I’ve ever seen before. And it’s definitely had a huge impact on our revenue. Related to all of this, having worked in global companies all of my life, quite frankly, and in the space of IT and data, at the end of the day, there are a series of best practices, the best practices of concepts that need to be utilized, literally in every country.

Beth Bauer [ 01:18:57 ] But how they play out from an execution standpoint needs to be able to be flexible. So federated and flexible ensures that we have the ability to reach customers in the way that they can and want to be reached in various countries. That means we have to be able to understand the differences in the regulatory, as well as the similarities in the regulatory, playing to that base, but being able to take opportunities as they play out. Just an interesting concept about the whole China thing as well. I mean, China has more data technically than anywhere, right? They’re capturing data about every move that people make. And in some cases, there’s thought that that is attempted to be happening all over the globe through certain applications. TikTok comes to mind outside of the United States.

Beth Bauer [ 01:19:50 ] But also recognizing that within China, they actually have put caps on that, right? So that there’s limited usage of TikTok by young people in China as a requirement by law. It’s not that they’re not recognizing that there are differences in how we want to play out looking at somebody else versus looking at ourselves. And that’s going to be a big part of the whole thing. It’s going to be up to how all of us behave in the future and how both as the businesses as well as the consumers, what we will request. And so I think that the long-term survivors in this space will actually begin to build personal relationships with who they’re looking to create better business with, long-term, so that actually there’s an anchor in trust because the trust component is really going to be a major issue for the future.

Beth Bauer [ 01:20:47 ] Great. I want to move over to, we’re getting some great questions from the audience as we speak. And so I want to move over to one of those questions and I’ll hand it over to either Paul or Julian, whoever wants to take this one, which is what does an AI first business model look like in practice? I’m happy to take it. And Paul, you can chime in any time. Well, first off, everybody’s saying ‘AI first.’ So I don’t even know what that means anymore, right? If you’re not ‘AI first,’ you’re nowhere. So it’s the most annoying piece of B2B tech messaging ever. I hate ‘AI first.’ Side note, but I think ‘AI first’ and putting ‘AI’ in the center of your business model and execution means going from functional departments using ‘AI’ in silos to ‘AI’ across the workflows and across the functions.

Julien Sauvage [ 01:21:45 ] I think that’s what it, at least to me, that’s what it means. Because when you think about it, like 90% of the use cases we hear about for ‘AI’ are productivity-based, right? That’s like automation stuff. So SDRs can now write emails faster. Content marketers can produce content faster. Reps can don’t have to manually enter their sales data anymore. Like everything’s automated, but it still is like, it lives in pockets, right? It’s all very, very siloed. So I think an AI first business model and company tries to break the silos and really bring all the revenue critical functions together and infuse that AI into the workflows. Like that’s what it means. And I think there’s, back to what we were talking about earlier, there’s a governance aspect to that as well.

Julien Sauvage [ 01:22:40 ] If AI is well-defined in existing cross-functional workflows, then everybody’s going to be able to leverage it and benefit from it. And it’s not going to be just in pockets. So that would be my high-level answer to the question. I’m not even sure I got the question right, but AI in the cross-functional workflows to break the silos. So I don’t disagree, obviously. I have the same frustration you do, Julian, about AI and ML. They’d slap it on everything. And it’s a reason to either jack up the price or to launch something new that was previously just sad. And so I struggle with it because I think it’s just the evolution of smarter automation or more intelligent automation that, despite the success of these platforms, two things, big companies struggle with still adopting sales 2.

Paul Kühne [ 01:23:30 ] 0 principles, let alone whatever AI is going to do, because they’re big enough to be inefficient, or they’re so small, they don’t have the resources. And I think that that AI is not a silver bullet. It can help us work smarter. It can be that sidekick or turbocharge that you said, Julian, right? And I think that even with the proliferation of marketing automation and smarter automation, it’s still very siloed. It’s not that single pane of glass across the business, even if it is in a utopia across marketing and sales, like you said, Julian. And so I think that that attempt to have, not that it’s a local language model, but the attempt to have sort of everybody speaking the same language at the company, and to kind of layer on efficiencies based on that is awesome.

Paul Kühne [ 01:24:09 ] Now, what’s hard is that I think a lot of people, like marketing automation was sold to us 20 years ago, a lot of people think if they buy the system, or 17 of them, that’s going to happen tomorrow. And that’s not how it works. It doesn’t mean you shouldn’t get started. But you know, the use cases we see out there of, you know, oh, we’re actually using our conversational intelligence and to customize or personalize content and follow up at scale, which seems so basic and unsexy isn’t happening at most places, right? People with marketing automation might have, especially in B2B versus B2C, abandoned dynamic content, or it’s hard to maintain ages ago, right? And so I think that there’s still an efficiency there, but the starting small across the business and figuring out what it means for go-to-market in terms of brand and demand and keeping the lights on.

Tommie O’Brien [ 01:24:52 ] And then how does that bleed into ops and finance and CS and product is important. And that’s how do we leverage tools that are based on ChatGPT and cloud, or they might be bespoke AI for your industry. And all of that still so at the front of the bell curve, that it’s exciting, but you could just dabble in it and still not be disciplined enough to see anything through. And I worry about that even with sort of, you know, the marketing automation stuff we have, it’s sort of like Industry 4. 0 and 5. 0. And in manufacturing, it’s like we’re moving on to something we’ve the quorum has not mastered what came before. And so I think you want to keep your finger on the pulse there.

Tommie O’Brien [ 01:25:27 ] But in marketing and sales, if you can work smarter, and AI enables that, that’s that that will help you meet your revenue goals, which are what the short-term goal is, right. And I think that people are dizzy about AI and excited to read up on it and excited to play with it. But just employing small wins, whether it’s, you know, campaigns, or, you know, like, you know, like, you know, like, you know, like, you know, like, pain analysis, or product market fit on the back end, or whether it’s content and not press go and publish 19 crappy blogs, but sort of how do we make this blog a podcast? How do we clip something more easily? All of that’s out there today.

Lara Shackelford [ 01:25:58 ] But that’s not the be all end all, I think it’s moving toward what Julian’s vision was, that would be more ideal. I’m going to take a bit of a contrarian tone to what we call AI first. And that is, that sounds like a bunch of rubbish, unless you’re mistrial, unless you’re open AI, unless you’re writer, unless you’re a writer, unless you’re a writer, unless you’re a writer, unless you’re a writer, unless your business is selling AI, it’s rubbish. I’ll give you a story back in the 90s. I was consultant out of America was my client, and we put in their website, which was wonderful. And this was at the point in time when everyone was smoking web crack, which is the web was going to solve and change everything.

Russell Scherwin [ 01:26:31 ] And we were out for a drink and the CMO, Jim walks up to me and says, ‘We did a great job with the website. Now let’s go sell cars online.’ I’m like, ‘Awesome. Let’s have a meeting tomorrow.’ My point of view, Jim was Jim, you’re an outsider in America, you don’t make cars, don’t sell cars. Or at least, the consumers, you import cars and distribute cars. Just like any other business, your purpose is driving revenue by serving a mission and minimizing your costs, minimizing your risk. At the end of the day, businesses exist to serve a purpose. AI is a tool that in some cases is going to help us out in some cases isn’t. And just like the internet, just like databases, just like the wheel, we just got to figure out how it’s going to help us serve our purpose.

Paul Kühne [ 01:27:12 ] So perhaps my point of view there is, as I’m thinking about it, it’s AI. AI second or AI third, because again, just like anything else, it’s a tool that’s going to help us serve our mission. If we’re putting AI first, then perhaps we’re the tool. Yeah, we’re speaking to the car, but where’s the car going, right? Yeah. AI enabled is a term that we use a lot because it is about, there are a lot of people who for a bit thought that they, let me get an AI strategy. And I’m sure we’ve all seen organizations where, oh, let me, I’ve, I’ve, someone’s got an AI strategy and they’re like, oh, let me get an AI strategy. And so it’s been appointed in our company to lead AI.

Paul Kühne [ 01:27:48 ] And, and then that person is running around looking for use cases, right? And what you know, AI strategies should come from we have a business purpose. We’re doing our best to align our culture to it. People get it, they’re bought in, our strategy now aligns to it. And then by the way, AI can enable and support that strategy. So that’s, that’s where it comes in versus AI first for AI sake. That will get any company in trouble. One of the things that came up at the best mention, yesterday when we were talking, was this idea that that digital transformation, which AI is part of, is a journey and not a destination. And like, it’s, I can cut Beth off there, but I thought that’s an important point because it is, you can’t just jump from, you know, backwards processes to suddenly buying three pieces of software or bolting it onto your legacy software solution for what you sell and hope that it’s the AI first.

Brandee Sanders [ 01:28:39 ] I do think that that’s a little misleading. I think it’s enabled in various degrees of enablement, like you said. And I’m going to add to that. I have seen organizations say that they want to be first, it was Data First, now it’s AI First. At the end of the day, it’s Business First. But I’m going to add to that: strategy does not only come through business. There does need to be an AI strategy. There does need to be a Data strategy. All of those things need to be tied to the Business strategy, right? But you can’t come, you can’t come at this and say it’s AI last either. Because if you don’t think about and strategize about how you’re going to take your data and your AI over time aligned and evolving with your business, you’ve missed the mark.

Brandee Sanders [ 01:29:25 ] But I think any technology, sorry, go on Paul. I was just going to say what’s essential to that strategy. Marketing also often is challenged as a service organization, right? Or corporate strategy similarly, when you like have to have your hands in everything and people that are in charge of in manufacturing, it’s digital transformation or advanced manufacturing industry 4. 0. And now it’s kind of like AI, digital transformation. If you don’t build that consensus across the leadership team to do more of what you were saying, Beth, or you were saying, Julian, we skipped that step sometimes, that internal education about what the hell is AI, or what does pragmatic, AI look like in stages or what do we need because of our vertical and our product?

Brandee Sanders [ 01:30:03 ] Maybe it’s not sort of the TikTok data up to wazoo as helping or maybe it’s not sort of everything agentic. And so that it’s dizzying as a product. But it’s also sort of a place to question, right? So I think that’s an opposed to like what core parts of it could enhance our main go-to-market strategy or open new markets, to your point, Beth. But yeah, I just, I think that the internal education is almost taken for granted. And then this poor person that either grew through the ranks or comes in sideways and is charged with AI or digital transformation is not empowered to succeed. And there’s all the scary stats from Wef and Gartner and friends about how many digital transformation initiatives die. So, but, and then they think that they’re going to do that alone, right?

Lara Shackelford [ 01:30:40 ] That’s the person who’s going to make this happen, not the web across the entire-So we’re pulling their magic AI buttons behind the scenes. Right. It feels like that stanza from the Bo Burnham song, a little bit of everything, all of the time, because that’s what it feels like when you’re on the receiving end of that, and there’s no discipline. It turns into chaos. And then we all go, what, what happened? I thought we spent six figures to get this exec from XYZ with the accolades to come in and make magic. But there’s that human element again, like one person cannot control all of that chaos, the discipline. The compliance, the standards have to be set before you go out there. You got to know what plants you want in the garden before you’re putting seeds in the ground.

Beth Bauer [ 01:31:18 ] And I think quite often to Paul and Beth’s point, it’s always retrospective. And sometimes the others, if you haven’t educated yourself right, especially at a scale-up or a startup, the CEO was wooed by some SDR or saw something somewhere, right, about how these SDR robots are going to have it rain from the skies. And so then you have to like figure out, are you doing this? Do you agree? Does it make sense? And so there’s like a lot of potential but you can’t, what’s going to make room for that, even if we’ll ultimately make efficiencies, right? New technology takes a hot minute. And I know someone was asking about what types of different people you might hire. And I think just like any rev ops on steroids or sort of coordination on steroids, it’s people that are willing to think differently.

Lara Shackelford [ 01:32:00 ] It might be digital natives or people that understand how to layer technology onto business processes. It’s not so that they’re willing to, you know, look at the auto cuts from a web, edit super slightly, throw on something from Canva and call it a day. That’s more efficient. Can a 70-year-old or a 22-year-old do that? Absolutely. But, you know, can, is someone that’s new to sales more likely to use conversational intelligence versus someone that’s been doing it for 50 years? Maybe. Maybe they’re great at note-taking. Maybe they’re great at putting notes in Salesforce. Maybe they weren’t. But I think it’s the mindset that’s important no matter your age.

Brandee Sanders [ 01:32:39 ] Let’s flip over to talk about partnerships in the ecosystem because we’re in such a connected world, right? We have been for quite some time, but it becomes even more connected in this AI-enabled world that we’re in. So this question, Russell, was for you, but for all the panelists where you have a point of view, when you think about your experiences at IBM Watson, your current advisory role, how do you think strategic partnerships within AI-driven ecosystems, let’s not say AI-driven, sorry, AI ecosystems that are potentially AI-enabled, how do you think those partnerships will enable innovation and growth in 20-25? And what factors do you consider when you select and manage partnerships? It’s a fascinating question, AI and partnership. And here’s why I find it fascinating. And I’ll give you a point of view.

Brandee Sanders [ 01:33:34 ] And I think AI will grant, grant, it’s going to change you. It’s wonderful. At the same time, when I look at AI and sales, and AI and partnerships, at the end of the day, people don’t buy a darn thing, at least in complex sales, because you had a great message or even because you were a little bit better in the competition. At the end of the day, partnerships work because I trust that when s**t hits the fan, you’re going to take care of me. And I’ve built up trust over the course of a sales cycle. And so when I think about AI and partnerships, I think AI can lubricate the path and make some of the busy work easier or fall to the background.

Russell Scherwin [ 01:34:16 ] But I think too much AI and partnerships is a scary place. Because AI, when AI starts doing the thinking, the human element leaves and it’s the human element that drives the trust that underlies good working partnerships. So my instinct is too much AI is not a good, and I’ve seen that too. On the buy side, when people try to sell to me, and I see, when I see AI taking the place of a rep, it’s an immediate turnoff. And frankly, when I motivate sellers, like I don’t mind a seller or a partnership rep using AI to help think through a message or to role-play, okay, talk to me, I’m working with an industrial manufacturer that needs a partner with, what might the value driver, what might be some value driver hypotheses be that I can attach a message to?

Tommie O’Brien [ 01:35:06 ] That’s great. When all of a sudden, AI is just automating stuff, all of a sudden the trust arose. And that’s the fabric of a partnership anyways. Right. So sorry to be the contrarian once again there. Oh, we like contrarians in this panel. Who else? No, I was just going to say that I think, on the light side of AI, more intelligent automation about which channel partners are most active or which are at risk, the same types of the same types of Intel, we would apply to you directly. And so I think that, you know, obviously, sometimes channel partners have a lot to sell and staying on top of their radar, realizing who your low-hanging fruit are, whether they’re small, medium or enterprise is important.

Brandee Sanders [ 01:35:52 ] And so some Intel behind the scenes could help, but it’s not some silver bullet. And that’s different than the wider picture, obviously, that you painted. I wanted to add to that, that there is so much accelerated change and so many new tools and so many ways that AI can help us, that AI will help us find partners, yes, but then our partners will help us find AI because we’re not going to be able to adopt everything. And so our trusted networks and circles will rely on them because we can’t all know everything. We’ll rely on those humans to guide us to what they think is going to work best for us. And so some of those partnerships are going to be very, very important.

Brandee Sanders [ 01:36:38 ] We’re going to get stronger and stronger where those are guiding us towards specific tools that will help us to have a better future. I like the emphasis on AI and human. I heard it in other discussions over the last couple of days, but for sure, it’s not AI, you know, the fear of AI replacing our jobs, right? It’s AI helping us to be more efficient, more productive, more innovative, so that we can do more of the things that we can, where we can add the most value. And so I think that’s something that’s going to be very, very important. One other thing I wanted to add to that, it was an important distinction that I just heard this week, which I think really needs to be reiterated.

Beth Bauer [ 01:37:18 ] It’s not just a human in the loop, right? It’s not just some now robotic human who’s going to do some checking. It’s humans and AI in this together all the way. Exactly. I would just agree. I know some when we were at Cisco, some of the research we did, we jokingly didn’t call the report this, but like, robots are going to take your job, but they’re going to give you a new one. And I would say for the purpose of this calls robots, AI, digital transformation, it’s all sort of interchangeable because what can be automated will be, but then the human skills or the soft skills or the 21st century skills or whatever we want to call the entrepreneurial skills, the what you get in is what you get the better, you know, as you start to master these AI models, whether they’re language based or other based, that sort of interface, making it part of your regular operations, like you said, Beth, is so important and will evolve greatly as the tech evolves.

Tommie O’Brien [ 01:38:07 ] And as the data is being used, the data is being used, the data is being used, the data is being used, at its disposal, if it’s data based evolves, but that is exciting. People aren’t going away. It’s just a different way of interacting with data and tech. And I, and I, I totally will throw out there that I often think of humans as the guardian of quality and AI, because we’re overseeing the rules. We’re validating, we’re refining AI, like the processes that are involved with that from both like a technical and ethical perspective, hopefully ethical standard, like setting the standards, reviewing the outputs, detecting and addressing bias, which is a massive issue or errors, because we’re creating the rules and the mechanisms that enforce these certain things.

Lara Shackelford [ 01:38:44 ] And there’s continuous improvement, of course, through feedback loops, but it’s, it’s inexorably, they’re tied together for now. And the going back and forth on that, I see it both ways, because while we ultimately make the decision-making on that, we make mistakes. And so there are little spots, where maybe a rule we wanted didn’t get applied, and AI can go find that. AI can actually also identify if we’ve said that there needs to be a certain decision process, and then that decision process was not applied in every case, it will find those cases. It won’t necessarily go and implement, I hope, but it would bring them to our attention and make us more aware of where we have holes and blind spots. I want to shift gears a little bit, and bring us back to, we’re talking about AI and maybe the future. I want to look at really 20-25 planning. And I’d like to ask the panelists to weigh in on, as you’re looking at 20-25, how are you incorporating AI into your plans? How is it either helping you to build your plans, or going to be a key, a factor in what you’re building for next year?

Lara Shackelford [ 01:40:04 ] Okay, I’ll go. I was like, ‘Come on, someone take the hot mic!’ Uh, I definitely feel like, first off, retrospectively, looking back, amalgamating massive amounts of data on performance, on marketing, and I’ll just view this from like, a sales and marketing and B2B tech perspective in sass space is huge because you can go back, amalgamate massive amounts of data beyond just the dashboard, and hopefully, you’re using it also for a little bit of predictive and forecasting in 25. But you can understand what worked, what didn’t, you know where those where those posts were that you anticipated based off of the model or the data that you had from last year, and then what that’s foreseeably going to look like with data-driven forecasting and like even scenario planning now some scenarios as our market has proven to us, and I have the white hair to prove it time and time again we’ll get little surprises there with scenario planning in our markets and the world in general.

Lara Shackelford [ 01:41:03 ] But I think from the perspective that I look at it, it’s operational efficiency, resource allocation being able to determine that if then that there’s bullying again right being able to do that if than that and then making sure that there’s some level of personalization to that market strategy so we understand customer personalization we’re laser focused on icp we understand what worked what didn’t you remove it you optimize it you set those kind of goal posts up and you know hey if i’m 85 percent of the world i’m going to be able to do that way through the quarter and my forecast is telling me i’m only 25 percent of the way to goal what levers can we pull and you you integrate ai across that as a solver as someone mentioned lubricant earlier to make those decisions easier and then also remove the someone Coming in, I think we should do X.

Lara Shackelford [ 01:41:50 ] And then being able to say, ‘I know we want to do a $5,000 dollar you know Rick and Morty steak dinner in Iowa, but there’s like zero customers, there’s zero prospects.’ I’m Oric, I’m Rick, and Morty steak dinner in Iowa, but there’s zero prospects. I’m resourceful and put those things together so both across both budgets go to market, sales, ed marketing. I think it’s um it’s a pretty core piece for both retrospectively understanding what worked, what didn’t, getting everyone to agree on the handshake and then using that for forecasting and scenario modeling in terms of prep for 2025. I go back to um again late 90s, I feel like an old man here, um.

Julien Sauvage [ 01:42:28 ] A gardener made a ton of money by selling classes to non-IT people, executives around what the internet is and how it might impact what you do every day. And I think it’s very similar for AI. I think if you’re a business leader, yeah, you need to incorporate AI into your plans, but I think you need to take personal accountability to understand it at a non-superficial level and start thinking through where it can help you serve your purpose better. Me personally, I’m looking into the O1 model. I’m looking at things like Replit and Cursor and working with AI. I’m looking into a lot of, I’m advising a lot of these companies, frankly, so I could learn because as much as I wish we could, Brandy said, put the toothpaste back in the bottle, it’s here.

Russell Scherwin [ 01:43:13 ] It’s real. And whether the EU wants to stick their head in the sand and over-regulate and let the Chinese and Americans get ahead of them or not, it’s there. It’s real. We all have our purposes and our missions. And it’s up to us to figure out how this tool can help us. And the pursuit of these outcomes. So that’s a long-winded way of saying, take it seriously and get in under the surface so you can figure out how it can help you in serving your purpose and mission. I’ll add to that. One of the important things, I love what you were saying just a minute ago, Brandy, about personalization, right? And so much what AI can help us do is also to be relevant with our audience.

Russell Scherwin [ 01:43:55 ] And that’s one of the key things I see for 2025 is more of that relevance. In addition to or on top of personalization. I would just add that aside from, even if it’s just in Canva, playing with it on the content side of things, I think the product marketing or forecasting implications that Brandy spoke of are really important here. Because at a startup or scale-up, the idea of FP &A is hysterical. And so, to expand your capabilities in finance and marketing and go-to-market with crowd-sourced, data from somewhere, or looking at your own data with hands-on you don’t have as a kind of co-pilot is a huge opportunity so that you can be honest with yourself or realize, assuming it’s not hallucinating, realize opportunities that you might not uncover yourself, right?

Russell Scherwin [ 01:44:43 ] And so that is really important because I’ve seen so many places that where finance and investor forecasts are a silo from marketing and sales, right? Which is hysterical since you’re supposed to meet them at the end of the day, right? So this can really help with that. And I think that’s one of the things that’s really important is that sort of parsing and collecting of information. And so, and what type of person would do that? It’s almost like there’s a lot of talk about Google being such an important skill, Googling, right? Searching, being such an important skill on resumes or for kids these days, being able to understand prompts and curation and working with AI tools, both basic and bespoke is sort of an evolution of that.

Tommie O’Brien [ 01:45:23 ] That is, you know, a huge area of opportunity. And if you know how to harness that so that you have this army of thousands that isn’t perfect, but it’s pretty darn important, then that’s a huge area of opportunity. And I think that’s a huge area of opportunity for planning or for output on the other side. And I think related to that is creating a more broad awareness of how data and AI need to be contextualized to actually provide you the right answer. So we often look to data and AI to just, you know, oh, I’m going to ask this big thing and it’s just going to give me the big answer. But that personalization is really down in the weeds and being able to parse out where are you able to apply an insight and where do you need a different insight and beginning to understand what it means to capture data from these various spaces when you can generalize and when you can’t.

Tommie O’Brien [ 01:46:17 ] And that’s going to require, back to the partnerships conversation, that people are going to have to talk about what it means when they see certain data and not make assumptions and be able to have the language to train them. Translate across these various silos and ultimately to their customers. And when I say language, I don’t mean language like English versus French. Codification. Technical versus marketing. Codification. Yeah. Yeah. So critical. Yeah. I love that you picked French, by the way. Thank you, Beth. That’s a good call. I think one of the things I like to say is that AI forces us to think about our tasks. You know? It’s like, it’s that huge, like automation booster. But then if you don’t really know what the sequence of tasks that a given person is taking to get to an outcome, you can never optimize it, right?

Tommie O’Brien [ 01:47:11 ] In other terms, you cannot define the destination. Well, you know where you are today, but if you don’t know the road to get to a destination, you can’t optimize that route. And so I think one of the beauties of AI to me, despite my bashing the marketing of it, is it forces all of us, leaders, practitioners, everybody, to think about, okay, what’s the sequence? Where do I spend time today? Where do I click? What do I look at? Who do I talk to? And then it should put us in that, like, in that mindset of there’s no tolerance for what I call the dead click. The dead click is if you clicked on something already once, you are not allowed to click on it again. Because that means that you’re repeating a process.

Beth Bauer [ 01:47:58 ] You’re repeating a pattern, and that could be automated. So every time you think about the click path or the sequence of event or something that you’re doing, and it’s a repetition of something you did in the past, that’s a potential for automation and AI. So I think AI, despite all the hype, is a great way for us to think about the ways we work. And processes, which is so critical because, again, it’s very easy to talk conceptual, and there’s, like, the reality of what people assume it takes to get X done. And then there’s reality of it, because even if you look at, like, things like AI often gets interplayed with process mining, all of that is tied together because it allows for smarter resource allocation and continuous levels of improvement.

Beth Bauer [ 01:48:43 ] So you have strategies that are actually grounded in operational reality, not the assumption that the exec thinks it takes 10 steps when it really takes 55 and a fax machine, and it’s coming back over and someone’s pager goes off in an office. Like, in addition to that, when you interplay process mining across that AI branch and you’re looking at operational reality, there’s this compliance management element that’s tied into everything we’re talking about for that, which identifies the regulatory risks and all those little ping pong steps that you’re mentioning, Julian, and it can integrate that AI for that actual like data-driven monitoring for proactive mitigation and eliminating inefficiencies. So, like, the process mining side of that is also really fascinating.

Beth Bauer [ 01:49:27 ] I would just like to-I’m gonna go back to-But I think idiot proofing that for your executive team or your peers is really important, right? So there’s, and they still might think it’s bullshit, but like showing the process and showing what could be automated, showing the risks is important. I know I had to do that both for practitioners and for leaders and marketing automation, and still it was Greek, right? But you have to be like, here’s today and here’s tomorrow, guys. Here’s what it happens. Like, this is what’s going to happen. And it’s not, we’re not even getting to revenue impact yet, but obviously that is the goal over time. And, but that is part of that education that everybody said, but I think that it is, I think Julian and Brandy, you hit it.

Paul Kühne [ 01:50:01 ] It’s, it’s, if you don’t have a good process, if the process, if the bad process is what you’re putting in, if the crap is what you’re putting in, crap is what you’re going to get out. You don’t want to scale that. So I wanted to add one thing onto that. What I have found is most organizations hate two words, process and governance. And if we can flip both of them on their heads, process is really your organizational habit. And everybody loves the Atomic Habits book, right? So if we can think about that as what are the habits of your organization and how can you change those habits? And then from a governance standpoint, flipping governance on its head to something that is more, what are, what are the capabilities that we want to have?

Paul Kühne [ 01:50:45 ] And what are the guardrails that we need in place to be able to enable that? I really see the flip side of governance as enablement. And how can you begin to focus on breaking down those barriers that actually lead you to that full-on enablement, but without governance in place, you’re going to end up with bigger fences than you thought. I like that you said enablement because I keep wanting to go back to AI literacy. You brought me back there. So thank you. The AI literacy, we, I think a lot of us, especially if you’ve tuned into this show, you’re probably already engaged with AI, right? But there’s so much. And so there’s still so much. There’s still so much for people to learn and learn across organizations.

Paul Kühne [ 01:51:26 ] And we can’t assume that, you know, people who are more enthusiastic or maybe more kind of change-oriented are the norm, right? And there’s still a high level of AI literacy training that needs to be done to bring the rest of our organizations along. So, that’s one thing that I look to in 2025 is how do we make sure that our organizations are truly literate, have the ability to take advantage of AI. And, you know, look at their processes with help from, you know, someone who really understands AI, but also always question where, you know, if there’s a place where they can be more efficient because AI can help them, even something like Clay. Oh, I don’t have, I have a couple of hundred thousand email or sorry, contacts where I don’t have email addresses for them.

Brandee Sanders [ 01:52:11 ] Right. Clay can help me solve that problem in a matter of hours, but if someone’s not necessarily as literate, they, they wouldn’t know. Um, so that’s a really important piece. That I wanted to stress. All right. We’ve got a few minutes here. Go ahead, Beth. Were you going to jump in with something? I have to add one little thing on a soapbox about calling anything literacy. I’d like to use fluency. And the reason why is literacy is like a binary. You’re either literate or illiterate. And it makes a lot of people feel like they’re not part of the cool kids. If we can switch to fluency, because we are all at various levels of fluency with regard to AI, um, it, it opens up the world and actually points out that, um, we’re, there are very few people who are actually completely illiterate at this point with regard to AI, but, uh, we want them to up their game, no matter where they are.

Brandee Sanders [ 01:53:08 ] I like that. I’ll, I’ll, I’ll adopt fluency. I’m in. So, we have just a couple of minutes here and I want to, again, focus on our theme of 2025 innovation and growth. I want to go through each of the panelists and ask you, just give us your, you know, pretty rapid fire. What are the, what’s the trend one trend that you really want to make sure people have their eye on for 2025? Since we were just speaking, why don’t we start with you, and then we’ll move down the line? I really think that, uh, uh, one of the key things that we’re going to finally realize is how much data we have. Data is really feedback, is knowledge, is everything we know. And it’s a question of what did we prioritize to digitize?

Russell Scherwin [ 01:53:55 ] And if we recognize within organizations, we’ve got a lot of data that we haven’t digitized yet, and we can actually monetize that both for ourselves and potentially for others, which opens up even more revenue streams, both internally and externally. I think that’s going to be the key is, is recognizing that prioritizing what knowledge we have to digitize and turn into data is going to be really powerful. Paul, over to you. Sure. I mean, obviously we’re seeing a lot of AI used for content, but I think that on the go-to-market side, um, and we were touching on it before with planning, I think that from either a campaign analysis or go-to-market fit perspective, um, it, it gives you capabilities at a startup or scale up that you probably don’t have, cause you’re trying to dial for dollars, but do it in a smartly intelligent way.

Lara Shackelford [ 01:54:45 ] Right. And so, whether you’re trying to look at messaging or trying to look at ICPs and you’re putting data in there or getting data that is out there to analyze it, or you want more analysis than you can do alone on how certain channels are working, using it behind the scenes in marketing and servicing and marketing sales, I think is really important. And you can do that with the, the, the larger agents out there, um, before you even look at bespoke solutions, cause you could be like doing demos all day long. So I think getting into that and realizing the power for arming you with information, um, it’s behind the scenes, but I think it’s more powerful because it is. It helps focus people. Excellent. Russell, your turn.

Russell Scherwin [ 01:55:27 ] I think the trend is acceleration. Here’s what I mean. Um, Paul, you’ve been speaking about digital disruption a couple of times. Digital disruption used to mean I have an idea. Let me go hire some people to build something, which is going to take a long time. Now I have an idea. I asked my robot to, to do it and it does it really fast, like in 10 minutes. And then I hone it a little bit. And 24 hours later, I have a disruptive application. So that’s going to be moving so fast that it’s going to give us as a species whiplash. And so I think buckle up and dig in, learn. You can either put your head in the sand or you can learn and get on the wave. So acceleration.

Russell Scherwin [ 01:56:11 ] Acceleration. Brandy. Oh, oh, it’s so funny because what Russell said reminds me of that. Ian Malcolm from Jurassic Park, just because we can, doesn’t mean we should. So be careful because the life finds a way, if you know what I’m saying. And I’m sure AI will as well. Anyway, I would say top target, honestly, if you think about the top line for 25, I’d go right back to the idea of processes because AI is a lovely sticker to slap on anything, but data in data out, garbage in garbage out. So like process mining process intelligence, uh, really should be a part of enhanced strategic planning. So you harness that data-driven insight. You come back in; it reveals the true state of operations, whether it’s 10 steps or 25 steps in a fax.

Lara Shackelford [ 01:56:58 ] Uh, and it helps you to really properly allocate those limited resources and markets like these and make sure that you have operational efficiencies and that you have automation and innovation tied together. On the proper target. So you’re not no longer just spraying and praying-by the way, this doesn’t just apply to marketing and sales. It’s universal. It’s engineering resources. It’s IT resources. It’s human resources. It’s people opt because that combination of that process, mining process, intelligence, and AI really ensures that if you’re looking at 25 from a planning point of view, decision-making is grounded in actual process performance. And it supports honestly, a more precise, agile business strategy. So you’re able to react to anything that the market might swing our way, which given the past few years could be anything.

Brandee Sanders [ 01:57:47 ] Julia, do you want to add? Do you want to bring us home? Yeah, for sure. I know we’re at time. I don’t know what the trend will be. I feel like the trends we’re talking about now, we could have talked about them last year. So I’ll give you, uh, what my hope of the trend should be. I hope 2025 will be the year of pragmatic AI, like practical ways of measuring the actual outcomes of AI. We can talk about AI all day. If we don’t identify the applications of it, if we don’t measure the before and after. That thing’s going to go through the trough of disillusionment, I forgot the name, the Gartner thing. Uh, and it’s, it’s going to go off the hype cycle.

Julien Sauvage [ 01:58:28 ] So, um, I guess my wishful thinking trend is, uh, pragmatic and, uh, and, uh, and measurable AI. Excellent. Thank you so much to our panelists. So as we wrap up, focus on AI fluency versus AI literacy, um, bringing that into your organization for 2025 more. Acceleration, focusing on process mining, and I have one too, but we’re over time. So I’m going to say thank you everyone and follow up with me. If you want to know what my trend is that I’m most excited about for 2025. Thanks everyone. Thank you so much, Lara. Thank you everyone. Next up, we’ll explore the nexus of AI and venture capital. Welcome our community favorite, one and only Anne Hollander, advisor at Strategic Edge. Will lead us in a deep dive on fundraising and M&NA.