AI Sales — 2026 Predictions Redefining the Sales Organization

Julia Nimchinski:
Thank you so much again, and we are transitioning to yet another exceptional roundtable, a CEO roundtable, focused on sales tech predictions for 2026. Our host is Nicholas Dikuchakovsky, Industry Analyst at PacCube. Nicholas, stoked to have you here. Just one question, and the stage is yours. What’s your top GTMEI prediction for 2026?
Nicolas De Kouchkovsky:
Oh, man. I thought by moderating the panel, I could dodge the question. Oh, I… I have to skip this one, I’m sorry about that. no analysts have been able to predict gen AI. It lets them by hand to a kind of humbleness on making predictions. So, the way I look at it is more through Kind of trends and guiding predictions that give me lenses, rather than making a prediction that will be proven wrong in two quarters from now.
Julia Nimchinski:
Love it. We hurried the scientific approach, and now, the spicy one. Welcome to the show, Amanda Kello.
Amanda Kahlow:
Hi! Nice to see you!
Julia Nimchinski:
What’s your top GTA prediction? You gotta save the show.
Amanda Kahlow:
Yeah, I’ll share my prediction. My prediction is that we have a new for marketing and GTM, we have a new, like… I know we’ve been talking about new funnels for so long, but it’s no longer about experimental, and it’s no longer about measuring pipeline, but we’re really measuring revenue, and we’re thinking about our customer lifecycle holistically, as opposed to in silos because of human limitations. So, pipeline is not the main driver of marketing, would be my big prediction.
Julia Nimchinski:
Awesome. Nicholas, back to you.
Nicolas De Kouchkovsky:
Thank you very much. So, again, Nicholas Dukushkowski, I’m an industry analyst covering both the sales and customer experience technologies, and like I said early on, dodging the question about prediction, I’m both thrilled and humbled to discuss the challenging topic of making, predictions. What we’re gonna try to do through this panel is look at how AI is already defining how you design your motions, your sales motion. How it’s changing, we’ll look in particular about the pipeline from creation to, to closing, and hopefully you’ll get some kind of a… you’ll get some tangible guidance. So, like I said, I said humble because I think that making prediction is mission impossible. The pace of innovation is completely insane. And something that was true one or two quarters ago. May no longer be, true anymore, and for sure, agents, are changing a lot of things, and the art of, the possible keeps on being rewritten, almost in real time. And I said frail because, today I have with me, five CEOs, five, industry. Experts and 5 innovators that are really at the forefront. of what, AI can do, and hopefully together will, will help make sense and look in our crystal ball in the future. But, before we dig in, can you guys do a quick roundtable and introduce yourself and your companies?
Amanda Kahlow:
I’ll go first. Hi, Amanda Kalo. I am the CEO and founder of OneMind. I was the founder and former CEO of Sixth Sense. My one line to the market as I started Sixth Sense to find buyers, and one line to close them. We are building go-to-market superhumans. It’s a face voice and really double-click, it’s the brain that can take action and agency, across the full life cycle of the customer. Everything from creating top-of-funnel pipeline, all the way through to onboarding in your self-serve motion, also enterprise motion, so support customers all the way across. cross-sell, upsell, give a live demo, etc. So we are building humans, in the form of AI for go-to-market.
Nicolas De Kouchkovsky:
Ready? Next. It…
Rachit Kataria | Centralize:
I’ll jump in really quick. I’m Ratchet, co-founder, CEO of Centralize, did Y Combinator. We actually raised from Salesforce and jokingly say that the R in your CRM needs some help. There is no relationship layer. How do we help you operationalize multi-threading? Where is the place to wake up for highly complex enterprise strat deals where frankly, no map, no deal. Everyone pretends to be strategic in QBRs and makes one once and never again. How do we help you visualize exactly who you’re talking to, what they care about, who you missed? How do you fill in the white space to go from stage one to close, and actually have a strategic approach to sales using agents to get you to the last mile?
Stav Levi-Neumark | Alta:
for…
Braydan Young:
I can go. I’m Braden Young. I’m the co-founder of Sendoso in the past. I left there about a year ago, and just started a new company called Slash Experts, where we think that the very first step in the sales process is better to connect with the customer, rather than connect to sales. So, we use AI to help pair you with a customer who’s like you, to figure out and help answer your questions, and then you can move forward and hopefully close that deal.
Stav Levi-Neumark | Alta:
I’ll go next. So, I’m Stav, I’m co-founder and CEO of Alta. Alta is an AI go-to-market operating system, focusing on top of the funnel activities. In my previous role, I, led the growth organization in BigBrainMonday.com. So I work a lot with the go-to-market teams and understand what… what we can do in order to help them grow, and In Alta, we’re doing a lot of data-driven approach, helping connect the agents, with this first-party data, and we’re kind of in the AI transformation space, so we’re not for builders. We are for go-to-market teams, accelerating go-to-market teams, work with the revenue leaders. And they help them during this transformation, especially for mid-market, teams.
Daniel Vassilev | Relevance:
And hi everyone, I’m Daniel, co-founder and co-CEO of Relevance. We help organizations, and in particular go-to-market teams, build an AI workforce. We power some of the best companies in the world, like Canva, Lightspeed, Autodesk, and others, to help them take what makes their top performers really special, and amplify that, and accelerate that. So that in the future, in the same way that AI is currently revolutionizing software engineering, we can see that same sort of impact and accelerate our go-to-market teams.
Nicolas De Kouchkovsky:
Awesome. Thank you. So, I’d like to start by, looking back in the mirror, what we’ve learned. in 2025, so can you each give a sense of what your most advanced customer is actually doing, how they’re using AI, and more importantly, how it’s moving the needle for them?
Amanda Kahlow:
I can start at the top again, so I was giving somebody else a chance to go first. Sure. So, yeah, we’re working with customers, HubSpot, LinkedIn, New Relic, Nutanix, Boston Dynamics, a lot of big enterprise companies. I can give… I’ll give two quick case studies. One, HubSpot, we’ve got, five superhumans deployed live across HubSpot. It does everything from qualify, post, form fill, to, like, give the pitch, give the full demo, bring them through, and close business. So they saw a 25% increase in their revenue and their PLG business. So, not pipeline, but actually measuring to revenue. So I had another recent customer, Xperity, so they sell, ER software, and they saw 5X increase in their revenue from their previous chatbot. So they had a chatbot qualified prior, they turned us on, and they were able to increase their revenue across every one of their stages of the funnel. It almost doubled. And then one other name, I won’t say the name of the company because I’m not allowed to, but they were able to close, shorten their deal cycles by 22 days. and double their ACV. So, you know, as I started off, my prediction is all about measuring to revenue, not just to top the funnel, and I think that is the unlock that we’re seeing with our superhumans, that they’re not just better than chatbots, but they’re better than the humans.
Nicolas De Kouchkovsky:
Yeah, it’s incredible how, from an inbound perspective, it’s finally happening. Last year, I would have said that AI for inbound is over is overdue, and it’s finally happening. It’s amazing, also, that it has redefined… you don’t just engage on the self front, you bring also all the assistance, all the questions, so… Pretty phenomenal. I’m sure we… we’re going to continue to discuss it. Who’s next?
Braydan Young:
I can go. I mean, I think one of the biggest things for us is we just brought on our first handful of enterprise customers, and What we’re learning is that a lot of the challenges and issues are not just at one company, but it’s across the board. And so, learning from… from certain goals and tools that you use to help solve problems, like, you can share those, and typically, if you’re across SaaS or across finance, it’s usually the same challenges. Like, everybody has the same problems with data, same problems with using their customers to help close more deals, and if you can take those and apply it to different techs and to know what works, and then to help other companies. Like, that’s where we’ve seen it kind of really work well for us. I think what’s worked well this year, too, is putting an OKR or plan in place, and sticking with it for 6 months to a year. I think it’s a big one. There’s so many new tools and tech out there, we’re one of them, that I think it takes time for stuff to prove if it’s successful, and so to stick with it for a while and see if you’re hitting your OKRs and then pivot, I think doing too many pivots is, Probably the biggest challenge for 2025 we’ve seen.
Nicolas De Kouchkovsky:
Yeah, I’m hearing consistently this issue, if you want to have success, you need to put wood behind it, you need to put people to make things work. And the last thing you want to go is, after all the shiny objects and Just think that technology needs to be deployed, like, in the old ways, and get results.
Braydan Young:
there’s a lot of CEOs out there, right, that are like, hey, add AI to that. Tell it to every team is.
Nicolas De Kouchkovsky:
Yeah.
Braydan Young:
It’s a challenge.
Nicolas De Kouchkovsky:
And they still got the same pressure from their board, so… what’s next?
Rachit Kataria | Centralize:
I can jump in. Amanda, I like what you said about the… it’s not just pipe gen, like, there’s a whole funnel that’s involved here. I think a lot of AI has been about, like, oh, AI SDRs are the future, and there’s all these new ways you can leverage it to do that. maybe this is a little spicy, but I think that’s the easy part. Like, getting the first meeting, great. You still have 10 months of work ahead of you. Like. That is not sales, it’s just get the first call. It is navigating EBs, and champions, and DMs, and coaches, and above, on and below the line. There’s a very large process ahead of you. And I think the teams have been able to lean into the actual deal acceleration velocity close rate part of that flow. When Books are shrinking, and it’s harder to get that pipe, is really where a lot of the alpha is. We have a pretty strong take on this, which is just that, till date, somehow, despite having every tool under the sun, you still have deals that slip and stall, because you were too low and too single-threaded. Because it’s just hard. There’s, like, so many people to figure out, like, are you in the right rooms? Who are you talking to? And so a lot of the teams that we work with, we’re also very fortunate to work with, like, the intercoms and high spots, Brexes, Core Weaves of the world, really, really, I would say, discerning go-to-market teams, and privileged to work with them. Those are the ones that are actually leaning into being more human, if anything, right now, and getting the last mile of relationship building and everything else taken care of, where you’re actually just focused on the people and what they care about and those priorities. And if you can map those out well, I think that’s where you see the wins. when you don’t, things fall apart very quickly. And doing that at scale, I think, is the hard part. So, it’s been really cool to see when folks can really focus on that core part of their motion. It’s almost like people crave more relationships now, when there’s more AI, in some ways, is kind of the sentiment I get. And so it’s interesting to see how you kind of, like, err towards everything that gets you to that point where your job is building relationships is what you lean into, and a lot of the rest can get taken care of.
Stav Levi-Neumark | Alta:
So, so far, I agree with it, and I can take it for a few, use cases that is exactly like taking this, core, work and help them, like, do it a bit better, so… Things like around events, so, schedule meeting before events, and, making the, the, making sure that event is, like, a lot of salespeople going to events to, to, to, to do lead generation activities, so making sure that their calendar is already booked before, that they squeeze the lemon after, the, the, the book, the booked meeting that they had, is, like, following up. As they should. So this is, like, events is, is, is one use case that we see a lot of success in. Another is, like, like, we call it MQL, no meeting, so many times, like, inbounds and activities that are coming to the website, leaving contact sales, and not immediately booked a demo, so the time is really critical, and many times, like, in the… if it won’t… if they won’t book a meeting and we won’t nurture them really fast. With the right material, with the right success story, so we will lose the intent. So, like, again, squeezing the lemon and, like, taking, leads that is already qualified and making them, book meeting. As well as reviving and, like, resurrecting, old leads that was with intent and was lost, or, like, deals that was lost due to product wasn’t, not in the right place, or features that was missing, or, like, the timeline wasn’t the right timeline, and bring it back, so I think it’s a lot about finding the right processes that can, improve, and find how AI can help you improve it.
Daniel Vassilev | Relevance:
And maybe just to dovetail for what everything was said here, the… there’s kind of, like, a plethora of use cases that I think sales walls can leverage today with AI, and the number one thing I think we’ve learned in 2025 is that it works. AI, like, you know, it clearly works. The companies that are leveraging it correctly and well are succeeding and winning. Bigger than they have in the past. But I think there’s, like, two other lessons that tend to kind of go a little bit understated, and I think those are actually the two critical ones for people who are trying to succeed with AI. And the number one thing is. when you are deploying AI, if you’re treating it like a technology problem, you’re going to fail. It is half a technology problem and half a people problem. You need to have the right mindset shift and the right organizational structure to leverage AI, just as much as you need the right technology. So if you spend half your time evaluating things on API latency, or et cetera, et cetera, or it’s completely siloed to the IT and engineering org to help you build AI, you’re probably not going to be able to win. And the reason for that is very simple. Who hires your top marketing performers? Who hires your top sales performers? It’s the sales teams themselves, it’s the marketing teams themselves. who actually trains those people? Again, it’s those teams. And so what you really want to do is make sure you have the right organizational structure internally, and have the right people training the AI. And the second thing you want to make sure you’re doing is you’re actually training the AI to do things that only you do. Because if we all end up buying AI that does the same thing for everyone, there’s very little delta there. Where’s the leverage that we’re going to be able to use? You want to have you’re going to need to train the AI to do things the way you do them. And the way I like to, like, tell prospects to think about this is. train it to do what your top performer does, right? Like, think about how you can help your AI do more of what your top performers do. So then when your top performer is freed up from 30% to 60% of that… of the tasks, which today, realistically, AI should be doing for them. Where can they spend their time now, and keep moving up the ladder? But I think without those two things, you’re gonna end up with many unsuccessful AI projects, because at the end of the day, if no one’s accountable for your team of agents, in the same way that you have people accountable for your team of humans. You’re gonna have the exact same problem of having a team with no direction, no vision, no strategy, no clarity, and no accountability.

Nicolas De Kouchkovsky:
Yeah, you provide a wonderful, transition to, another question about the, the human and AI Division of labor has been a sensitive topic. It was a stream of thoughts where AI replaces, through automation and, better means humans. There’s a different angle, looking at AI and human coming together. So, through your interactions with customers, have you seen any evolution on these topics, and how do you see the human AI into working as we move into the next year?
Daniel Vassilev | Relevance:
And… and I’ll just jump into that one, because I think this is the one that I care the… one of the things I care the most about when I’m thinking about how does AI benefit teams. And, The reality is we’re all waiting for, kind of, like, the miracle use case for AI. I think that’s kind of, like, been a steady, like, pattern for the last couple of years. And the places where we’ve seen AI really take off and have, fundamentally changed behavior every single day is for software engineers. The products for AI coding have clearly had a permanent shift in behavior for people doing that job. And I actually think when we as go-to-market orgs, like, are thinking about how can we deploy AI, what could it look like for us, I think there’s a lot of lessons we can take from that. And the interesting… the most interesting insight that I… I’ve seen from, kind of, the AI coding impact is that people are now not… it’s not like they’re not coding any… it’s not like they’re not involved in the coding process anymore. They’re just not involved as much in the, like, writing line-by-line of code. They’re much more focused on delegating tasks. And so, what we’ve been really focused at Relevance is thinking about how do we integrate our teams, or the teams for our customers using us, to be able to delegate work that they shouldn’t be doing themselves. And in the future, how can we get to an end state where they’re basically just orchestrating and managing their own team? To help them achieve their outcomes, versus them spending, going through a list, clicking on buttons, scrolling down, clicking next page, everything else like that. How can we eliminate that? Help them focus instead on, hey, I need to achieve this outcome, help me get there. And I think that’s realistically, when we think about, kind of, a human plus AI relationship, that’s, I think, the kind of best in class. It’s about delegating work to AI. Now, I’d be disingenuous not to say that there will be some displacement. There is 100% gonna be roles today that exist that are majority of, like, of doing that kind of grunt-level work. Those are probably going to meaningfully shift, and we’re already seeing that. However, I do think that it creates a lot of opportunity on the other side of the table, kind of what Richie and Amanda were talking about, especially down the funnel. So the best sellers, the best people who go to market can really start focusing further and further down the funnel. And really kind of leverage, their kind of relationship building and other skills to dominate and win more deals, instead of spending a lot of time at the top of the funnel and letting those things slip.
Amanda Kahlow:
Yeah, I’ll jump in after what you said. So, I actually have somewhat of a spicy take that it’s neither. So, of course, yes, jobs are going to be replaced. Of course, we want to augment human tasks and capabilities, and that’s just the obvious answer, but I actually think there’s… AI has the ability to do something that humans can’t. So, to elevate the human experience where humans can’t do things. So, when I… when I’m talking to customers. In, for example, when you have a commercial SMB PLG motion, where there is no business model to put a human, but your buyers need a conversation. They need an empathetic conversation, need somebody to hear their needs, and to solution with them. And what we give them today is a website that you have to go click around and try to figure out, or read white papers, or download product documents to get to where you want to go, because you’re paying $500 a month, and there is no opportunity for a human to to, to intervene. And so… or even if you’re thinking about, like, when I think about our superhuman experiences. what she does, if we… if the bar is human, we’ve failed, because humans have massive limitations. We have time limitations, we have recall limitations. If you think about what humans are doing, even in a sale, if I’m on a call with somebody, the best seller is on the call and can have that deck ready to go, have all the case studies ready to go, but they don’t know where the conversation’s going. And so, for a company like, for example, like Databricks, who sells, like. horizontally, vertically, to every company, every industry, every vertical that has data, how do they pull in the right case study at the right time based on what they heard in that moment when they have 10,000 case studies, right? So. being able to do things a human can’t do, and grab that information, and then say, here, boom, it’s right here. And be able to move the conversation forward, and apply all the best-selling methodologies. Why do we teach our humans, like, Sandler or Challenger or MedPick? Because we can only teach them one, because their brains are like dumb trucks. We can only put so much in their brain before they have to, like, take something else out. But in the world of AI, you can do things infinitely. So… I challenge that best uses of AI is not to replace the human, it’s to supersede the human capacity limitations. That was a long answer to, yes, we’re gonna replace, but we can do better. And at the end of the day, it’s more revenue, and it’s a delighted buyer experience.
Braydan Young:
I like that. I agree with that. I think my hot take on this one is I think… I mean, being from a company in the past that did gifting, we’re very good in tech at over-correcting. I think we’re going to get rid of more sellers than we should, and I think we’re… I think next year at this time, it’ll be a correction back to hiring more, because I think the AI works very well in SMB, mid-market. If I go to a site, and it’s like, hey, take a demo, and then two days, I get someone sending me a message, and I have to book a time on a calendar, I’m like, that takes time, and I hate it. Like, I want the answers now. I already know that I want this, I’ve done my research. And so, I don’t think you can apply a lot of the AIs yet to enterprise deals. Like, if I’m spending more than $300,000 on a piece of software, I want a human to talk to. And so, I think it takes time to get to that point, and I think we’re gonna apply it to all sales, all go to market next year in the world of tech, and there’s gonna be a lot of layoffs, and we’re gonna be like, oh, shit. And so then I think we’re gonna pull back a little bit, is my… is my hot take on… on how tech is gonna take a look at it, but that’s my… that’s my, that’s my hot take for the… for the day.
Rachit Kataria | Centralize:
I’m weird.
Stav Levi-Neumark | Alta:
a little bit with it, I have to say, a little bit of Friday. This is what I wanted. I think that also, like, we can see it in, like, reports in the… I don’t know, everyone here probably read MIT reports and McKinsey reports, like, about the success and the implementation of AI. I don’t think that companies are on their way to huge layoffs tomorrow and replace all of our go-to-market team, and I think that if we look at companies, like, if we look at McKinsey reports, so companies that succeeded Versus companies that didn’t succeed, like, the top performers company did 3 times better in AI implementation than the low performer. So the differences between them is how they think about AI transformation, and human-in-the-loop design was, like, much higher in the hierarchy of how to do it in a correct way. And it means that it’s not tomorrow going to replace everyone. I find, like, with all the prediction, like. the Javon’s Paradox, I don’t know if you know it, but with the light bulbs, that when light bulbs became super efficient, so everyone thought that electricity, power places will go… will decrease, and in the end, it’s… it’s only, like, made it. much higher, like, the electricity consumption became much higher in the world, so I think it’s, like, it’s a bit of a paradox when thinking about, like, AI and, like, how is it going to help go-to-market teams, and I don’t think that tomorrow, every go-to-market team will be replaced by AI, and I think that if we… we will improve their performance, so it can… even doing vice versa, like, we will need more go-to-market teams, because they will be more efficient, and they can bring more value to the business and sell more. So, I’m.
Amanda Kahlow:
But what if the AI is smarter than the human? So I think the reason we go to humans is because we trust it more than we trust AI. If it’s smarter, and you actually have more trustworthy answers, and they’re instant, and imagine the world like we’re about to release a live demo, where she can actually click around and give a live demo. You don’t have to wait. So in an enterprise deal, you can get that live demo in real time. Right? So, those are the places where…
Rachit Kataria | Centralize:
I think that’d be bad.
Stav Levi-Neumark | Alta:
Isn’t…
Braydan Young:
funnel, absolutely.
Rachit Kataria | Centralize:
Yeah, I think we’re talking about, like, we’re all builders here in GoToMarket. The funnel is very long. Like, there’s angles that are about deflection, which I think is about… no one has the time, feasibly, and, like, staff of humans to go answer those questions, nor, even if they did, would have all the answers, and I think that’s the… like, solve the inbound problems, solve all that front of the house. I think, Daniel, I like the word he used, which was orchestration on the bottom half, which is, like. When you get to the point where a human is involved, then what you’re optimizing for is them orchestrating the info that’s already at their fingertips, versus them doing information gathering and finding the things to give as an answer. Now you put it in their hands where the human’s building the relationship, but has what they need to do the right things to build that relationship. I think that’s all it is. It’s like, you just find different use cases where you’re doing things that literally were unscalable until superhumans, like you say, Amanda, can do them, and no one else, frankly, should be doing them, but then those people should be working on the last mile that’s taking everything that’s fed to them at their fingertips, and that’s the delegation orchestration piece, and then they’re going and acting on it. That, I think, is going to end up being what the funnel ends up looking like, and whether you need more or less humans is going to be a… I think, a consequence of, like, how much you focus on top of funnel versus bottom, and where you need the bodies, if you will. But I do think, to point on Enterprise. no one is gonna buy a 100K plus deal without talking to a real person that they feel good about, because I think a lot of it is about relationships to that degree. Like, you have people that you’re gonna need to support to talk to to feel good about the implementation and deliverability long-term. Maybe that’s a hot take on just…
Braydan Young:
Yeah, I think it is.
Rachit Kataria | Centralize:
Where things are going.
Amanda Kahlow:
We have closed the.
Nicolas De Kouchkovsky:
Why don’t we build on that?
Amanda Kahlow:
And our customers have closed 100k plus deals with no humans. So, I’m just saying, not every customer in every way, but it has been done. So we have just…
Rachit Kataria | Centralize:
I would agree with that. I think as long as the ROI story of, like, look, I need 5 people that could never do this, and I would pay them $100K versus having superhumans, like, you can… that trade-off, I can… I can see how you wouldn’t need to talk to a human. I think anything that starts getting into more of a… truly, like, implementation engaged, have to talk through the use cases, where this changes the core of your stack. Like, people will start getting involved pretty quickly. So I feel like it depends on the product, is maybe, like, the simple answer here. Why don’t we… Why don’t…
Nicolas De Kouchkovsky:
We build on this to look at the new art of the possible and focus on the last leg. What is new that we can do with AI that we couldn’t before? And let’s focus on the pipeline. You can focus on the top, on the bottom, whatever. What, and maybe focus on what gets you the most excited about the new things we can do with AI that we couldn’t do before.
Stav Levi-Neumark | Alta:
Oh, maybe I’ll start with, like, sales enablement, materials and the ability to create really good sales enablement materials that are really fit to, like. The specific customer, so it can be, like, a customer story that is, exactly to the… to what the customer needs, and based on similar customers, or a specific e-book or thought leadership content. That can be really tailored. So I think, like, LLM, like, it’s the biggest revolution when we talk about AI, and of course, and the ability to create content and good content and quality content that is very specific to the need, and also learn from content. So learn from conversation, learn from calls. Learn from, like, CRM unstructured data. that this is a thing that we couldn’t do before, and we can do now, so it’s, this is really exciting, like, this really helps to top of funnel activities. And this was a really huge pain before, so I think this is really exciting.
Braydan Young:
I’ll, I’ll build on that. We, I mean, I’ll use our own tool, and what we saw was… there’s a lot of customers going through their journey of, like, hey, they purchased this thing, they’re onboarding, they’re integrating, they’re figuring it out, and there’s customers that are trying to sell, that are starting that journey, so connecting those two folks, saying, hey, here’s… what’d you run into that was a challenge? Or, like, not hearing it directly just from the tool, the company you just bought, but from people that are going through the process, is what we’re trying to inject in the pipeline. Just because I think it’s one of those, when you hear from a third party, it’s… it feels a little more valid. So that’s the… that’s what we’re excited about. I think. I mean, not to be on my own soapbox there, but, like, that’s one of the big things that we’re seeing work well, is learnings through other companies that are in different spots of their own journey.
Amanda Kahlow:
I do, I love… I love what you’re doing, 100%. I think it’s a really cool thesis. I would say my… my take is to… I always… as much as I’m out there to drive revenue and drive growth. I’m really… we exist to create a better buying experience. And so, if I think about the buying experience, it’s not just top of funnel, right? It’s after they purchase, it’s post-purchase, it’s the support, it’s the onboarding, it’s the cross-sell, it’s the upsell, and we take them through what we do to our buyers and our customers is atrocious if you actually think about it. You start on a website, you start on, like, an LLM, or you start on Google, you end up on a website, then you fill out a form, then you talk to an SDR, then you get an AE, then you get a sales engineer, and then you get a customer success manager. and then an AM, and like, holy shit, like, what do we put them through? And it’s because humans have limitations. So what if we could have one unified experience? They never have to start over again? They always, when you’re talking to somebody, whether it be a human or a superhuman, they truly understand the needs of the buyer, what they’re solving for, their pain points, so it can be the best solution support resource across the life cycle of the customer, and so that’s what I get super excited about, about the future. The future is not to make what we’re doing today better, it’s actually to create a whole fundamental paradigm shift, and what that looks like for our buyers, and as a result, revenue will fall out of the bottom.
Rachit Kataria | Centralize:
Yeah, I like that a lot. I want to echo what you said, Amanda, with that. You mentioned, like, 10 different orgs, or people in those orgs, like SEs, AEs, CSMs, SDRs, everyone’s collaborating together. I think part of the complexity that AI can actually solve for that’s exciting these days is the idea of team selling. Like. a place where everyone can come to and have the same picture, or, like, global understanding of what needs to happen in an org. I don’t know if this is a hot take, but I think most people listening that do any kind of mid-market enterprise strat sales have to get 10, 15, 30, 100 people involved in an org, mostly, these days. I think most companies that are selling have that kind of consequence. I’m sure selling Sixth Sense and Sendoso is very similar. Actually, Braden Sendoso’s a customer, so I know that’s very true. There’s, like, a lot of people involved in the buying process, and as a result. you kind of have to, like, find a way to orchestrate, which is, I go back to Daniel, what you keep saying, like, it comes down to, can AI get you to the point where I’m so excited about is literally visualize what was never possible before, which was that single org chart you would draw once, pretend to be strategic, and forget about. And then come back to every QBR, and… oh shit, we slipped, because the forecast was off, because we went to a champion that went on holiday and never got back to us. -Oh. We’re not in this deal. We have happy years the entire cycle. And so that idea of being able to like you said, centralize a single picture or visualize that story, I think that’s… that just wasn’t possible before, and I think that’s pretty exciting now, because I still think it all comes down to humans, that all, like, stand very firm and plant that flag. It’s all about people at some point in the cycle, eventually, because it’s not like Brex is buying, it’s not like any of us is buying, it’s… the person. Who are you solving for, and what they care about?
Amanda Kahlow:
Until agents are the ones who are the buyers, right? So what happens when we get to agents?
Rachit Kataria | Centralize:
There is a world where agents are just talking to each other.
Amanda Kahlow:
Either on both sides, and I think, actually, that’s the real future that we have to be thinking about. We’re not talking about today. It’s agent to agent.
Daniel Vassilev | Relevance:
Yeah, and actually to add to… yeah, to add to what I’m noticing, like, I think the… the kind of the discussion here is, like, it’s a sliding window of the future. It’s like, some things are possible today, and other things are going to be possible next year, and very different things are going to be possible in two years from now. And so I think, again, it’s disingenuous to not, like, be real and identify that more tasks are going to be like, subsided by, superseded by AI agents. And I think that is, like, that is true, we’re seeing that today, and just the question, I think, that exists right now is, where does that exist? And so what is possible today, and what’s going to be possible next year? And the things that I’ve seen personally be possible is, I think there’s this whole band of work that currently people cannot staff humans to do, and so it’s going undone, going back to what Amanda said. And what if you could train an agent to mimic your top performer and go after that pool of revenue as well? Now you just added a significant amount of extra pipeline to your business. Like, one of our customers was actually just mentioned, one of the big logos mentioned a little bit earlier today. 40% of the outbound is now completely handled by agents. 50% of inbound processing time has now been eliminated. And this is at a massive scale. This is an org with thousands of folks when they go to market, massive sales development teams, and that has just happened. A light switch has been clicked, and that has just occurred. And the thing that, the… most people don’t realize is this is happening in many organizations, but it’s happening in the top organizations. And so, actually, the art of the possible today is taking work that currently isn’t being handled and training agents that are top performers. The art of the possible today is giving your reps access to tools they never had access to before. Like, being able to be prepared for every single meeting with, like, a visualizer that, Richard mentioned to help them map an account. or collateral that they’ve got available to them at the right time. Like, one of the most exciting use cases I’ve recently seen AEs be adopting with us is, we’ve got on our homepage a video, you can see the whole journey. how you can use an agent to handle everything in your CRM, all the way through preparing content for you based on your conversations, and then building a full deck with an interactive ROI pricing calculator, especially if you have complex SKUs. And so, as an AE, me having to do all that work previously would have taken a tremendous amount of time. And there’s a lot of leverage to be able to tackle that use case today. But I think, you know, ultimately, I think as we think about what happens the year after that and the year after that, it’ll keep changing. We’re going to keep pushing the boundaries, and I think the best go-to-market leaders are gonna have one eye on, like, what are we doing right now with AI, and another eye on what… where is AI going to be in a year from now, and how are we preparing for that future as well. Because the things we’re talking about are gonna happen, they’re gonna come. The question is when and where, and that is going to be a sliding scale that is… You know, gonna massively transition and change in the next couple of years.

Nicolas De Kouchkovsky:
So, speaking about breakthrough, do you expect What would be the single biggest AI breakthrough we should expect? In the… I’d say next year, in the coming quarters. Or is it an unfair question? Because it’s so hard to predict? So let me spin through a different angle the question. One topic I keep on hearing, not just in tech, but in other industries, that is completely underserved with sales technologies. Is, how do we improve rep productivity? And it ties to this issue of measuring impact of AI, so rep productivity has become something tangible. For, many boards and, and many, Executives, with the focus on saying, let’s put… let’s give back. more… more time for selling, or those type of considerations. So, What is the, how big this is a focus of your customers, and how do you see this evolving? In the… in the coming years.
Braydan Young:
With rep productivity, in terms of, like.
Nicolas De Kouchkovsky:
Yes.
Braydan Young:
I think that, like, and to Daniel’s point, we have to keep in mind also that a lot of the companies and logos that we’re mentioning are tech companies, and so when you do go away from tech, like, yeah, not saying that they’re not adapting and adding new tech, but… none of us… I mean, maybe if anyone’s sold, like, Exxon or Chevron, hell yeah. But, like, companies that take a very long time to get to, and who have not… who are still just figuring out the CRM world. So, like, I think it takes a while for us to… to add, like, our techs and our tools in those spaces, but in terms of productivity, the ones that are in tech, the ones that are looking at us, the ones that are doing the best are the ones that are finding tech that helps them just do the tasks that are back office tasks, like, simple things, like call recordings and updating, you know, your sales force, and, like, things like that, I think is… I mean, those are all table stakes at this point, and you should have those. you should have a way to write emails quicker. I think all those tools are just out there at your fingertips, and if your reps aren’t using those currently, then I think you need to start fast, because I think that those are very much Need to be adopted now.
Amanda Kahlow:
I think about productivity for reps about… I think of everything in real time, right? So, you know, we have our superhumans, so they can be there to answer questions in real time, and to help the field, we have superhumans that join calls. So. I thought about bringing a superhuman onto this… onto this webinar here, but I didn’t get permission, so I didn’t… I didn’t drop her in. But the thought, you know, so that she could be hanging out answering questions, and the idea is that you know, how many times do you want is a rep on a call, and either says, I’ll get back to you, or hallucinates to move forward, move the deal forward? And they do so, you know, nefariously, to get the deal done. They may not make a huge lie, but they’re like, yeah, yeah, we do that, like, trying to do it, and say, like…
Braydan Young:
I bet.
Amanda Kahlow:
Right, right, or, like, skirt around the answer, because they don’t actually know the real answer, or they can’t get to that level of depth that is needed in the moment, because they don’t know where the conversation’s gonna go. But imagine having that SE resource on every single call. That SE resource is there to answer the hard technical questions, the SE resource is there to give the live demo and share, like, the very specific use case And do the things that a sales engineer would do, and I think that helps productivity, because then there’s no follow-ups anymore. And then, like you were saying, like, some of the obvious things of writing the follow-up email and giving real-time coaching, hang up the call and say, hey, you know what, you talked too much. You didn’t ask the questions, you didn’t ask if they were the buyer, you didn’t ask if they were the decision maker, and can give that feedback in the moment, versus, okay, now I need to go back and go log into another tool and see how I did, and I don’t even remember what happened on that conversation, because I’ve had 7 others since then. Right? So, those, like, real-time… the productivity is, like, getting real-time answers to your customers and real-time feedback to your field that can help them in the moment. Or slacking to them. The superhuman is on the call and is slacking to them, hey, you should say this.
Stav Levi-Neumark | Alta:
Like, or do you want me to jump in and say this?
Amanda Kahlow:
Or the rep says to the superhuman, hey, what did I miss? And you train the superhuman to ask the questions that you want it to answer, right? Like, you want it to ask that you’re afraid to as a rep, like, do you have budget or something, right? Like, ask those hard questions that our reps don’t always ask in the moment, because they don’t want… they’ve got happy ears, and they don’t want to ask the question that they need.
Rachit Kataria | Centralize:
Yeah. I have two, I think, extensions of that that I think about. I’m actually gonna go, like, back to what you said, Daniel, about coding and why it kind of caught fire in the coding space with, you know, Cognition and Devon and Cursor and all that. We’re all builders here, I’m an engineer by trade, I was at Meta for a few years before this, and somehow ended up in go-to-market. And I remember, like. it’s all about info gathering. I would just Google Stack Overflow every day, trying to find what was, like, the closest thing to pattern match to solve the problem. Just type things out 24-7, lose hours trying to build something. And then we built the core of our platform, me and my co-founder, on my couch for, like, a week or two with Cursor. It’s crazy, like, how fast you can move, because it took all of that info gathering and searching, and just giving it to you, and now you’re orchestrating what you want it to do. And I think with go-to-market, it’s kind of similar, if you think about the AE, even CSM-AM workflow, it’s… when Gong says 70% of time is not spent doing revenue generating activity or selling, what is that time? It’s… Finding the right people and doing contact information searching. It’s like, what have we said ever? Picking everyone’s brain from every inbox and gong call and email till date on what’s happened so far in this deal. Are we above the line, or on, or below, and are the right people involved? What do I say to them next? Like, all this BS that you have to just… get to even have a simple strategic outcome, which is, I’ll send this to this person at this time. And if you can take all of that away. I think to your question, Nicola, like, my take on the breakthrough is almost… every deal has a map, whether it’s invisible or you know it, and what AI can eventually do is become the GPS on that map, almost like Waze for your deal, because it has all the context on where you should go next from every prior closed loss one. And they’ll give you that insight. And you’re just taking left turns and right turns, and you know where to go, what stops to go along the way. I think that’s gonna get really interesting, and we’re not too far away from it, I think, if you have the data, but I think that’s the difference if I have to compare what I saw from Coding shift to what AI’s gonna do for sales, and what’s used to be info gathering, to just take a left here, take a right here, stop at this gas station on the way.
Stav Levi-Neumark | Alta:
So, I’ll continue that, and I think that it… to the previous question of the breakthrough that AI will do and the reproductivity, I think that in 2026, there will not be a CRO or go-to-market leader that will not break down the go-to-market processes and the buyer experience and the process, like, I think that what Amanda said, that, like, SDR, AE, like, if the experience is, is so, break because of, human, can, cannot do the full flow, so I think that there will not be a CRO or a revenue leader that will not think how we will improve this entire process with AI and with agents, and, like, agent orchestrate, this flow. So I think 2026 is the year of, like, revolution, and the way that go-to-market Teams thinks…
Nicolas De Kouchkovsky:
Okay, so it’s more… not just using AI to stitch and automate steps, but take a step back and rethink The plays, the journeys.
Stav Levi-Neumark | Alta:
And that way I can fit into it, like, and it helps.
Nicolas De Kouchkovsky:
Okay. So how do you drive those conversations with customers? Because it’s… Not easy.
Stav Levi-Neumark | Alta:
I would say that it is quite easy, because the intent is there, and they really, like, the intent is there, and they’re coming really, ready for transformation, and this is also part of the qualification criteria for us. Like, when we talk to a customer, we want to understand first if they have the right intent to do, kind of rethink on their process, how they can really optimize it? How can they really, like, I think that I… to go back to what Amanda said, I really like what he said about the process with the SDRAE, but also with the sales engineer, that sometimes they would want someone to join the call, and sometimes they wanted to ping by Slack, but the intent to do a change and, like, rethink on their process is there. So, so, so this is make it a bit easier.
Braydan Young:
I think… we’re getting better with AI tools of figuring out ROI, too. I would say last year, the year before, it was more like billboards. Like, how many people saw this ad? And so it was like, I think that we started with AI being, like, hours saved, which is kind of a bullshit metric. You’re like, you’re like, I think this saved an hour, and so, like, now we can look at, like, did this help speed the deal along? Did this help bring deals that were dead, that came back in the pipeline. And so, because the data’s there, because all of our companies are… just have more data to look at, I think that we’re getting better at actually proving ROI, which helps bring in bigger logos and close more deals.
Nicolas De Kouchkovsky:
ties back to what you were saying, Amanda, to be able to look at the revenue as the ultimate metric. Versus, kind of intermediability, metrics.
Braydan Young:
That’s where you start every board meeting. First slide.
Nicolas De Kouchkovsky:
It was right.
Braydan Young:
revenue last quarter.
Rachit Kataria | Centralize:
So, can you give other examples of companies that were able to basically.
Nicolas De Kouchkovsky:
Change some of your customers, change entire sales plays. Leveraging AI.
Rachit Kataria | Centralize:
I have a fun one I could share, Huge, huge fan of, one of our favorite customers, HiSpot. They’re… a lot of them, you guys probably know them, sales enablement space, they’re… everyone probably listening has heard about them. Their team thinks very, very strategically on the idea of what does it mean to be power-threaded above the line, on, below, high and wide in an org, because, again, it comes back to people, and people that care about what you’re building, who you’re solving for. And the biggest problem was this idea of just flying blind. It was like. Let’s do some very simple math. I’m a rep that has a book of 50. I might have 5 or 10 people in that account I have to think about. That means at one point, I’m probably having to keep track of 500 people. What they care about, are they still there, their relationships, their priorities, and that’s shifting every single day. Daniel, you’re my frontline manager, you have 10 reps, you’re expected to inspect 5,000 relationships at scale. Amanda, you’re my CRO, you’re probably like, what the hell’s happening in this account? Like, the company hopefully is moving underneath me, and we’re moving in the right directions and tracking things, but… It’s near impossible to get that level of visibility, let alone include the fact that it’s not just the AE, it’s the SDR, the CSM, the SE, it’s team selling, it’s the frontline manager, it’s… the CRO throwing in an exec touch to make sure that we’re getting the right things. It’s the investor throwing in a ping to make sure that we’re getting the right board, exec sponsorship. There’s a lot that goes on in sales, I’m sure everyone listening can resonate. But… Being able to do that at scale is the hard part, and being able to have the same place where you’re progressing your deals, inspecting is almost equally harder, and that’s pretty cool. They brought in Centralized not too long ago, and they basically ran every QBR 101 and delivery in the last three quarters. Using that flow. This is a picture that just creates itself. Here’s who we’ve talked to, here’s what they care about, here’s who we missed, here’s how we fix it. And that has just changed the entire, like, don’t spend 45 minutes out of 45 of a deal review getting to the baseline. Spend the first two knowing exactly what’s happened, and the next 43 on strategy, and fixing, and changing the story. That’s how you don’t get to end of quarter in deals slip and stall because you were too low, too single-threaded, got happy years. You need that answer day one, and agents can bring you that answer to get you to the last mile of doing something about it. There’s still a human at the end of all of this to take the action, which is the AE, or the person who’s gonna sell the deal. Like, someone has to go do something. It’s, where do you point them? What does that stop along the way, or the left or right turn? That’s kind of the analogy I like to use. But just an anecdote, been really, really cool to say.
Nicolas De Kouchkovsky:
Yeah, and I love it. I mean, this issue of dealing with the buying committee, this concept has been coined, I mean, 10 years ago, I think it was a very serious decision. Everybody has struggled, and keep on struggling, on how to operationalize.
Rachit Kataria | Centralize:
You guys can probably attest, like, everyone here is selling… I think everyone here’s.
Nicolas De Kouchkovsky:
Very nice example.
Rachit Kataria | Centralize:
Buyer committees are getting bigger. Like, 50K deals are going to CFOs these days is kind of rough. Like, you have to get a lot of people involved in many cases, and yeah, navigating that, I think, is what I personally get really excited about seeing people solve for, that kind of relationship orchestration.
Daniel Vassilev | Relevance:
Going back to your question, Nicholas, I was thinking, like, as you asked that, there’s, like, two examples that I think kind of provide context for, like, a lot of the conversation we’ve had today. Like, there’s this notion of reproductivity for existing use cases that you just must do. So when Amanda mentioned, like, we need to have a great buying journey, I think that is the default state every leader is trying to get to. What is the best customer buying journey we can bring to them? And today, there’s certain things that are, like, non-negotiables. That we must do with people that are extremely manual, and we want to automate as much of that as possible to help them. So, less on the… less on the pre-sales part, but on the post-sales part, when you’re coming up for renewal, the quality of your QBRs really matters. So one of our customers would spend about 4 to 6 hours per QBR to look at everything that happened in that order, tickets that were submitted to Jira, conversations that happened, every transcript, every Slack message, every email, summarize that, try to put it into a deck, go to product analytics, pull it all out, put it into a slide deck. That’s completely automated. They do this on their own 15 minutes. They’ve trained an agent on relevance that can go ahead in all those different places, pour that information, synthesize it the way that people do, because it’s all about training people to… agents to replicate the best processes your people do, and then put it into a slide deck. So that’s one use case that’s been, like, transformative. 4 to 6 hours to 15 minutes per QBR, times it the number of accounts you have. The second interesting one is from Autodesk, and actually. On… in early January, January 14th, we’re launching a series called Agents at Work, where I’ve basically just gone around to all of our different customers and interviewed them. Like, how do you do this? How did you succeed? Because I think they know better than I do at this point how to succeed with agents and go to market teams. And the one at Autodesk is really interesting. It’s about lifecycle marketing. It’s about thinking… Or not so much lifecycle marketing, but more thinking about, like, that buying journey. How do we nurture those prospects in the best way possible? Today, there’s just so many of them that we cannot give a good experience to. It’s some generic default experience in Marketo. That is the way the world operates today when it comes to nurtures. Templates in Marketo. We can do much, much better, and that’s an aspirational use case that’s less about rep productivity, but it’s about doing something you could never do before. So in that case, they can train an agent on a process they’ve never done before, but they know if they had a person doing, would be excellent. And if you train that agent to do that instead of some generic mumbo jumbo from a Marketo instance, you can have a lot of leverage in your business and your customers and improve that buying journey. So I think we’re gonna see, over the next year, massive amounts of productivity increases, and also these aspirational use cases that do things we just could never do before.
Nicolas De Kouchkovsky:
Yeah, like, the use cases… Okay, one final…
Amanda Kahlow:
Oh, go ahead, go ahead, Nicholas, sorry.
Nicolas De Kouchkovsky:
No, no, please, please.
Amanda Kahlow:
I was just gonna say, like, the… anyone who has a commercial or SMB business. Right, so just the ability to support those customers is probably where you have your highest level of churn. You can’t put as many people at it. You know your conversion numbers are lower than where they need to be. They could be higher if you could have higher value conversations. So I think it’s just, like, going back to, like, the earlier point where there is no business model for a human. to elevate the experience for your buyers, then that’s where they can do the full end-to-end. Like, our superhumans can do everything from, sure, create a lead, but actually close, and onboard, and support, and answer questions, and go through and do, like, academy work with them, etc. So it’s… it’s super exciting, because those are the areas where we know, like, in the early, like, 2012, when I started Sixth Sense, you know, it was all about… everybody was going after, like. you know, SMB and starting with smaller deals, and now there’s a lot of companies who are kind of moving enterprise, like, Sixth Sense was always enterprise first, and OneMind has been enterprise first as well, but I think it opens the opportunity for more companies, because you can build something so fast, to go enterprise out of the gate, and that hasn’t been… that hasn’t been the world we lived before.
Nicolas De Kouchkovsky:
Yeah, awesome. So, any, From, guiding customers to have those conversations, not about just… Perfecting our workflows, but thinking more strategically. about not just even the workflow, but the customer journey. So, how are you driving Those conversations with your customers, or steering To make those conversations happen.
Amanda Kahlow:
I think you just gotta get back to where there’s the biggest, like, pain point in the organization. So it’s, like, one-on-one selling of, like, what are you trying to solve right now? Where do you have the biggest point of friction? across your cycle, across go-to-market, what is your board mandating that you fix right now? Is it fixing your commercial segment at enterprise? Are you fixing time-to-value? Fixing your ACV, your competitive win or loss? And then, as a result of that, that’s where we go in and, you know, deploy different agents or superhumans, or whatever it may be.
Braydan Young:
This is a good time to have some conversations. Sorry, go.
Stav Levi-Neumark | Alta:
So, for us, it’s a bit more about, like, understanding what is the go-to-market process that they have, and, like, helping them understand where agents can, be mostly helpful, so it’s… it’s like starting with, like, discovery process. I can give one example, maybe with… Cloud Kitchen, they’re doing, like, ghost kitchens all across Europe, and they have a lot of different regions. Every region is really acting differently. And they have inbound, they have outbound, they have, like, a lot of different motion, every, every motion in every region, have different cadences, different time, from, like, time to close a deal. So, it’s a lot about understanding where is the best fit to start, how to scale it, and, and, like. And I think it’s really… it’s, it’s really neat to be kind of an expert look. And it’s not easy to understand where is it going to be really a good fit or not, and I think that there are a lot of people that is, like, really good at understanding, like, an expert at understanding where agents can be really a good fit and where it’s not, and saving a lot of time. Of deploying, things that won’t give value, in the, in the first day. And I think it’s a, it’s like, it saves times on the iteration. that they will do, and a lot of the conversation is really map the process with them, and understanding what is their KPI, and how we can get there the fastest possible.
Nicolas De Kouchkovsky:
Awesome. We’re getting close to the end of this panel, so what I would like is to give you back some time. To make your recommendation for the audience. Where to apply AI, or where to think through differently on the, on the, on the sales play, sales process, whatever you… and, how to do it, and… and… maybe give a little bit of color of what… why they should prioritize it. Once we go first.
Daniel Vassilev | Relevance:
I’ll just dive in, I’ll say, I don’t think sellers sell, I think buyers buy, and so I think the best thing that we can do is educate folks, and so I actually really recommend right now, in such a linchpin moment for people out there who are buying, take as many calls as you can with potential vendors, not as less. Take as many go, educate yourself. I spend most of my time educating, not actually selling, because I think this is… everyone wants to do more with AI, but how you get there is very critical. And that’s why I also think learn from your peers. like, the whole reason we want to do Agents at Work series is so that you could learn from others who are succeeding with AI, and I think that’s really, really critical. Learn from your peers, take as many vendor calls as you can, learn what’s out there, because it’s changing very quickly.
Stav Levi-Neumark | Alta:
So start soon, I think, because it will come, and you will use it, so start as fast as you can. This is, like, number one. And I think, like, focus on what works, although it’s kind of counterintuitive, like, a growth effort and not zero-to-one effort will be much better to implement AI in, because you will know how to measure it much better. Like, you will know how to measure the ROI better in an effort that already works.
Braydan Young:
Like that, I think just experiment as much as you can, and then make sure to take notes and everything, because AI is only as good as the data that you have, so take notes on every call, make sure your CRM’s up to date. Sure, how many times did your CEO tell you that? Why your CRM’s not up to date?
Rachit Kataria | Centralize:
Yeah, only thing I’ll add is that, the unsung heroes of all this, we haven’t said it once, are the RevOps people that have to get inundated with 50 tools a day on people building in this space and understanding what to do. And I think everyone that I talk to in RevOps that is making decisions is basically saying, it has to tie into the workflows. You could have the most amazing Jarvis in the world, and if it doesn’t actually flow into the day-to-day of the person. no one’s buying, they’re not gonna adopt, it’s a waste of engine, it’s a waste of resources. So, make sure what you’re opting for is actually tied to what you’re trying to solve on an actual rep-level workflow that, they’ll use, because at the end of the day, it’s people on both sides, and they have to lean in.
Amanda Kahlow:
I’ll just be really quick, we don’t capture demand… sorry, we don’t create demand, we capture demand. That’s what most of, like, marketing, automation, and demand generation programs do. So to focus on the more of the brand and the storytelling, we’re in a world where anybody can build anything, that storytelling is the most important. And I would also say that, stop thinking about things incrementally and point solutions, and how I can make today’s process better, and how, if I could start fresh with the tools I have today, what would I do? And so I think, like, that top line, and for the leaders out there, that it’s change management, so we really… it’s on you to figure out what the next step is, not to tell your team to start going and using AI. And how to put that change and process in place.
Nicolas De Kouchkovsky:
Thank you so much. I know we’re a little bit over time. Julia, you put me on the spot asking for prediction, which I carefully dodged. After this panel and the discussion on innovation, I would say we’re going to start seeing the buying journey being reinvented because of new things that we are able to do with AI, not just trying to do better existing things. So, over to you.
Julia Nimchinski:
Love it. Exciting times. Thank you so much for this super insightful panel, Nicholas. What’s the best way for the community to support you?
Nicolas De Kouchkovsky:
I’ll connect on LinkedIn, and we’ll take it from there.