The Atlas Retention Method

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Julia Nimchinski: Thanks so much, Jose. Pleasure hosting you. And now it’s gamesite time

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Julia Nimchinski: as we bring on Tori Jeffcoats, director of product marketing at gain site and Roman Delicia Vp. Of customer success. Welcome! How are you doing.

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Roman Dalichow: Hi! It’s nice to meet you doing great today, hey, Tori?

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Tori Jeffcoat: Great to be here. Hey, Roman.

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Julia Nimchinski: Great to host. You Atlas retention method.

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Julia Nimchinski: You just unveiled your new platform in a conference not too long ago. Correct me if I’m wrong. But how did I go?

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Roman Dalichow: That’s

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Roman Dalichow: it’s really exciting. It’s really exciting. We’re doing. We’re doing a lot in the go to market space. Obviously, you know, customer success has come a long way and excited to talk a little bit about some of the journey that we’re on, how we’ve gotten here. As well as how we’re thinking about. You know the future of Cs and using AI and agents to help drive more retention at scale.

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Julia Nimchinski: Just, haven’t it?

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Roman Dalichow: All right, let’s do it 1st of all, welcome, everybody. I’m gonna do a quick introduction. My name is Roman Dalichow. I’m the Vice president of Cs. Here at Gainsight, and for those in the room that might not be familiar with gainsight. We’re A. b 2 b Saas company that has been specializing in transforming the Cs industry. For over 16 years.

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Roman Dalichow: I myself have been an operator in Cs. Since 2015, and I can tell you that I am re-energized, and I am pumped at not only where we have come, but also where we’re going to go with AI

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Roman Dalichow: for today. I’m really excited to talk to you about the future of success at scale. I think that at scale parts really important as well as the expanding role of artificial intelligence, and not just AI as a trend, but as a transformational force to multiply what it is that we’re doing today.

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Roman Dalichow: So very specifically, we’ll focus on autonomous agents that tackle the most critical challenge in business today, which is keeping your customers said differently. Retention.

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Roman Dalichow: So over the next, let’s call it 2530 min. We’re gonna explore why we’re so excited here at gainsight, because we feel like there’s an opportunity for us and go to market and post sales to finally get help.

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Roman Dalichow: get help in flipping the script. And that’s using agents. And here at Gainsight, we’re building AI for Cs, specifically, not just for AI’s sake. And that is so we can do 3 things. One is make retention predictable. Again.

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Roman Dalichow: things have gotten complex multi products really hard. But we want to be in a position where we can help our customers spot risk before it’s too late.

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Roman Dalichow: Gainsight uses AI to surface early warning signals. That’s across products that’s across sentiment that’s across how we engage with customers so that we can act quickly and not get blindsided.

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Roman Dalichow: 2 is we want to surface expansion opportunities right? Like we all love growth. We’re all all in business for business succeed and do well together. And so we’re figuring out ways to automate playbooks that are triggered by real time signals that will also help your product. Get in the hands of your customers and turn your Cs team into a growth channel, and then 3. When you combine better retention with more expansion, you can scale your business in a more effective way, not necessarily meaning you need to scale headcount accordingly.

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Roman Dalichow: So right now, we’re at a point where we need to think about the concept of workforce augmentation. And I don’t mean in terms of like temp labor or contract labor or hiring people, but a true reimagination, not human replacement. You’ll hear me mention that multiple times throughout this presentation. And so, instead of thinking

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Roman Dalichow: about deploying agentic resources to do things that are quite frankly, just, simply unscalable or uneconomical. We want every one of your customers, large or small, to be able to feel like your most important customer.

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Roman Dalichow: or if we could jump to the next slide, and I don’t mean slide 2 to be a spoiler by any mean, or spoil the mood. By by starting with the like. The the sense of hey, it’s it’s not you. It’s me breakup scenario. But the fact is like, if you’re in the zoom room with me right now, you’ve probably heard the dreaded words from one of your customers before. We’ve decided not to renew, and that is just a nightmare.

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Roman Dalichow: And it’s not just a nightmare for us or our team members. It’s a nightmare for our CEO, and it’s a nightmare for our company.

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Roman Dalichow: And the simple reason for that is that churn is a growth killer, right? The whole power of the recurring revenue model comes from the fact that it compounds on itself. And that’s when things are going well. It’s also very predictable when you can forecast out how how much revenue you have over over a month, over a quarter over a year, depending on your contract durations, and so, when you use forecasting to also build your business and your headcount, your tech stack and build your budgets. You can’t have churn get in the web.

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Roman Dalichow: so it kind of goes without saying that it’s critical to not only maintain your install base of customers right, but also to grow it, because when you grow and maintain your install base, you have opportunities to bring new products to market that you can then sell into your customers with.

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Roman Dalichow: But what what if that doesn’t happen? And I’m just gonna walk through a scenario that might be familiar to some in the room. And that’s when a term pops up, and it generally goes something like this. You get the. We’ve decided not to renew message from your customer that’s usually over email after they’ve dodged a couple of your calls. So it’s like, Oh, Oh, something’s wrong. Let’s flag the account.

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Roman Dalichow: So in this case it’s a big account. So your executive team finds out immediately. And what does that mean? Like depending on the like. The the actual size of your account, relative to other ones like it could ruin your your day, your week, your month, your quarter, your year or your career right? This fire drill begins.

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Roman Dalichow: And it’s it’s usually pretty futile, because you’re probably too late in the game already. You’ve been reactive to too long, and the adoption is disconnected from the promised value. You told the customer all about when you sold them the contract, and so the Roi is disconnected from the renewal. So they’re turning on you. Unfortunately, the scenario here is. It’s it’s common and because we’ve been over overly reliant on people historically, because we had no other option. But today.

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Roman Dalichow: so no one is perfect and things can fall through the cracks. So even your best Csms have had this happen to you.

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Roman Dalichow: And so, finally, when you are too late, you pay the price in terms of revenue.

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Roman Dalichow: I like always like saying, any good person or trainer will tell you. One of the 1st things they’ll say is that you can’t out train a bad diet.

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Roman Dalichow: 1 1 of the things that I like to say is, you cannot sustain outselling churn. So it’s very similar to that.

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Roman Dalichow: The truth is that it’s not just your teams, but also your systems that are disconnected and broken.

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Roman Dalichow: And so I I’d say, if we agree on something on this slide today, it’s probably in agreement that keeping your customers is not easy. It’s hard. That’s why account management teams exist in the 1st place. And so if anybody on this call has a silver bullet for keeping all your customers across a variety of industries. Please let me know I’d love to learn from you. But the fact is, retention is hard and fundamentally, it’s a systemic issue that we all have to deal with.

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Roman Dalichow: And so a couple of things I’ll go out on a limb and say, here is that I bet your sales team. So your go to market teams, your Csms, your aes, anybody else who’s touching your account? They’re not communicating as clearly and as effectively as you might think they are. So your teams are siloed across your business. That’s 1,

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Roman Dalichow: 2. As a result of that, your customers are, gonna have some disjointed experiences. Now imagine working with multiple different teams like you can see where the experience that your customers have starts falling apart because they’re dealing with different humans. All who have different work styles different backgrounds and even different preferences on how they communicate.

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Roman Dalichow: The fact is that humans, we, as humans, are instinct driven decision makers. Because, hey, that’s what makes us unique, after all. But when it when it comes to business and customer retention, why does this matter

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Roman Dalichow: so? Your customer might shift what their plan is, or your product strategy might evolve. And so if your teams aren’t coordinated and siloed, they can’t keep up, and it’s your customer who’s impacted there internally, you start scrambling and retention ends up feeling like you’re just taking a guess. And Cs leaders in general and sales leaders probably fall into this bucket, too. It’s really hard to actually coordinate which activity is moving the needles for retention.

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Roman Dalichow: And then the real slap in the face, as I like to say is that once you realize things are off the rails, your customers seem to continue to always ask for more. They’re raising their expectations. They’re escalating. Just the temperature keeps going going up, and you have less time and resources to actually do anything about it.

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Roman Dalichow: And so, as I mentioned earlier. The fact is that half of like go to market leaders cannot tie activities to outcomes, and nearly half of Csms are burned out. So when you add those 2 things together. That’s not optimal. The need for efficiency is no longer just an optional thing. It’s survival based. If you’re in the Sas game

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Roman Dalichow: and customers don’t stick around if they do not see a value out of their investment.

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Roman Dalichow: So on the next slide, I’ll talk a little bit about what we’ve been focused on, because for years we’ve been engaging with customers and listening to what they’re telling us. We’ve also been working really hard to understand the issues that impact businesses post sales specifically and game sites. Customer OS isn’t just a rebrand of our of our product suite, but it’s a total reimagination of the customer journey.

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Roman Dalichow: and when I say customer journey, I think most of you will know. What I’m talking about is that one page slide that you have that’s in your pre sales deck that tells the customer. Hey? You’re in a in a land. Adopt, expand, renew phase. These are the different people on the account team that are gonna come in and and work with you to make sure you get value from the product. But the fact of the matter is that, like your customers don’t really care about that. They’re not sitting

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Roman Dalichow: in their internal meetings saying that like, Hey, I think we’re, we’ve moved from the land to the adopt phase with with this vendor. What do we think we should ask about that? No, that’s not how they think that’s not aligned to what they need.

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Roman Dalichow: When customers buy technology, they want to buy something that works something that is an extension of their business and makes them more effective. They also want to work with partners that deliver new capabilities and generate immense value. There’s an roi that’s associated with it.

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Roman Dalichow: And so at gainsight, we’re thinking about a single system that helps customers learn, adopt, connect, and succeed by guiding them through 4 things.

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Roman Dalichow: one. To deliver personal, self-paced education of your products.

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Roman Dalichow: that adapts in real time based on the user.

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Roman Dalichow: Then we guide users inside your product with relevant nudges, AI facilitated walkthroughs and feed that information back to you. So you can build vibrant AI moderated communities that drive a pure learning, experience, and advocacy. And if you’ve been in account management and Cs, and even in sales, you know the importance of advocacy, because that is the best sales rep that you have. It’s having another customer. Speak volumes about what it’s like, not only buying and using your products, but doing business with you

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Roman Dalichow: and then succeed. We help you detect signals with AI before the churn strikes is a trigger. The right place at the right time to retain and grow customers. And what’s exciting is that we’re supercharging all these applications with what we’re calling the Atlas family of AI agents

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Roman Dalichow: that will work as an extension of your team, your digital teammates that will help you reach especially that long tail of customers where it’s so hard to deliver a white glove. Human support, experience!

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Roman Dalichow: Can you hear me still? Sorry.

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Julia Nimchinski: Yeah. Now again.

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Roman Dalichow: Oh, sorry I had a an Internet snafu there. Alright.

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Julia Nimchinski: It’s okay.

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Roman Dalichow: And so we’re gonna focus on agents today and first, st before we talk about agents and what we’re excited about with Atlas, I’d like to go back to what almost feels like the stone Ages of Cs at this point, and that’s that’s when Sas started.

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Roman Dalichow: So Cs was born to manage, churn, and ultimately, through managing churn, extend the lifetime value of customers. Now

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Roman Dalichow: it’s evolved over time, and it’s matured into a more strategic pillar, aligned to growth, revenue, and profitability. But now we’re entering a new phase, and this is where AI agents power us to help go beyond just dashboards and playbooks and drive outcomes autonomously. If you recall from a previous slide

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Roman Dalichow: selling into your existing customers is super important, because that’s where 70% of your revenue is going to come from

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Roman Dalichow: yet. Most of our retention efforts today still rely. Love this image, rely on human heroics to really, really try to save your revenue, but that’s not scalable. And when we think about what business leaders, investors, and executives really care about, it’s finding more durable and sustainable ways to retain customers and grow your revenue.

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Roman Dalichow: and let’s just face it. It’s a lot more fun to be on a winning team than constantly be battling against churn on a regular basis.

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Roman Dalichow: Now on the metric slide, Tori, this is a little bit of an eye chart that we have going on here, but

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Roman Dalichow: just think about all the different points of influence that we as go to market leaders need to have. And I like to think about how this has evolved over, like the last couple of years in 3 buckets. So pre 2021 big emphasis on ipos, a lot of Vc. Money going into the markets. A lot of growth at all costs going on, and the cost to serve your customers didn’t really matter that much, because it was mostly about growth.

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Roman Dalichow: Obviously the financial landscape changed a little bit. Post Covid and money tightened up, and companies that solely relied on growth and not margins, were really punished.

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Roman Dalichow: And now we’re in a situation where it’s both.

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Roman Dalichow: and that’s really hard. Becoming. A rule of 40 company is very challenging, and it becomes really critical to place your bets in the right spot to have your people focused on the right things, but also focused on retaining your accounts across the entire business.

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Roman Dalichow: And that brings us to where technology really comes in. And very specifically artificial intelligence.

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Roman Dalichow: Many of us are already using AI today, we’re baking that into our daily lives. And we’re probably selling it some form in the applications that we have today.

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Roman Dalichow: And so what is an agent that might have been talked about in previous sessions already. But I’d like to share a little bit about how we think about agents here at gainsight and we. We define it as an intelligent system that’s capable of making decisions and then acting on your behalf to achieve a specific goal.

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Roman Dalichow: Right? You could say it differently, and saying that it’s a convergence of machine learning and generative AI to extend impact.

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Roman Dalichow: That’s another way of saying it which I which I really like when we think about machine learning, it’s about identifying patterns and then using Gen. AI to do something about it when you combine that it gets really powerful. And so we also think about the 4 components of an agent. One is an agent needs to have a goal, and that goal is specific. It can be narrow and stackable.

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Roman Dalichow: It needs context on what it’s trying to accomplish, and how. So what’s happening? Who’s involved and why?

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Roman Dalichow: There’s a reasoning layer that is attached to it.

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Roman Dalichow: Llm. Logic layer, and that informs the action that the agent is going to be performing, and we’re very excited to to show some concepts about that in a little bit.

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Roman Dalichow: But we take the expertise that we have at gainsight on Cs. We pair that with millions and billions of data points that we’ve collected over the time and are ingesting from a variety of different sources.

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Roman Dalichow: And those data points are analyzed and reasoned on by in-house models and market available Llms. And those trigger actions in our systems, or even push to other tools.

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Roman Dalichow: And the advantage that agents have over people is that they can very quickly learn on all those data points, learn from previous engagements and continue building better outcomes with precision and consistency. One of the things that I think about is like the version of AI and agents that you have today is going to be the least performant

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Roman Dalichow: that exists in your career because they learn they improve, and it’s always going to keep getting better.

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Roman Dalichow: And so I I like thinking about health scores as a really good examples. That showcase the evolution of where we have been on the onset of AI not too long ago, and where it’s going and where it is today.

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Roman Dalichow: So when we think about health scores, let’s take a look at a couple of things going from left to right.

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Roman Dalichow: The 1st application where health scores benefited from AI was on machine learning. We had large sets of data. Ml. Could identify patterns in that data and help humans make rational decisions about what to do about it. That’s great. That seemed game changing at the time. The next phase was Gen. AI. It helped us fill gaps in the data. It helped us summarize multiple, unstructured data sets and tied them together to surface the insights that gave us intelligence about more complex set of customer information than we ever had.

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Roman Dalichow: And today we’ve learned about that, and agents are already doing things that are making us more proactive and autonomous. Actually.

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Roman Dalichow: they’re sending signals to alert people on the team that there’s been a change in something that’s happening in a customer, whether it’s usage sentiment from a conversation that just happened or updates to a health score.

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Roman Dalichow: And we’re benefiting from that already, like I said, and it’s already putting us on the front foot. When we look at the problem statement earlier on saying that we’re way too reactive.

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Roman Dalichow: But what’s really exciting is tomorrow’s agents. We think about those as your strategic partners. They’ll simulate scenarios, they’ll forecast outcomes, and they’ll recommend the best path forward and depending on what you want it to do, even execute the best path forward to drive the action while you’re doing something else, maybe even asleep.

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Roman Dalichow: And so, AI like I said. I think everybody knows on the next slide, Tori. It’s a great tool for efficiency, but alone it’s human, reliant.

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Roman Dalichow: This is an improvement over. We’ve had in the past. But agents can do work for us automatically, whether we’re logging emails or looking at sentiment from customers

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Roman Dalichow: to flagging alerts when something happens and knowing what to do about it.

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Roman Dalichow: Agents work really well in the long tail of your business.

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Roman Dalichow: This is really where the cost to serve gets really important and tough business decisions need to be made about, what do we do here? And so the answer, in our opinion, is, agents to help serve this area of the business which has been traditionally underserved, because we all need a more reliable process and a source to drive the outcomes we need in this space.

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Roman Dalichow: And it’s a new type of work like another thing to think about. It’s a little bit scary, but like agents, they don’t sleep. They’re tireless.

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Roman Dalichow: They’re always learning. They’re always improving.

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Roman Dalichow: And they aren’t just orchestrating workflows.

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Roman Dalichow: They’re delivering outcomes. So when we think about this, they help your team scale things like personalization. The elimination of busy work like, we’re probably seeing some of those benefits just individually when we’re using Chat, Gpt, and other other sources, and they reduce our cost to serve without compromising the experience.

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Roman Dalichow: And so, finally, that brings us to Atlas.

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Roman Dalichow: And, as I mentioned earlier, Atlas is our next generation of agents, that is purpose built for Cs. And I’ll say this one last time today, this is a reimagination of the customer journey and not a replacement of humans. Atlas agents will handle renewals, adoption, risk, detection, community moderation all while freeing our teams up to do more strategic work. And with that I’m excited to introduce story to walk us through a quick demo of our agents.

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Tori Jeffcoat: Thank you so much. Roman. Really, really great points in terms of the scalability of our current human focused efforts and some of the challenges that we face in serving, particularly the long tail of our customers, where it’s just not scalable or feasible to have enough humans to serve the vast majority of of customers. Typically in your smb segment, low touch, there’s a couple of different names you might use to refer to that group. But agents really help us scale, and again extend our teams

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Tori Jeffcoat: to reimagine how we deliver work for some of those segments in particular, but also across our customer base. So I want to show 2 quick things in terms of what we’re building at gainsight and how we’re thinking about agents and leveraging this type of technology to help us better serve our customers in in our case. But.

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Tori Jeffcoat: the one I want to start with is really staircase, and just a super quick setup before I jump into staircase. One of the big foundational components of any effective agent. And I think Roman implied this in a couple of the slides earlier. But it’s really having good data and a foundation of understanding your customers in order for AI agents any process really to take effective action. So one of the key things that staircase really brings to the table is really helping to automate the collection analysis and

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Tori Jeffcoat: just consolidation of all of those conversational touch points you’re having with your customers. Taking your emails, phone calls, support tickets, product usage, all of the different signals that can be overwhelming or or siloed in some systems, and really bringing them all together to give you that full, clear picture of where your customer stands.

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Tori Jeffcoat: to show you a little bit of what this looks like and kind of bring a lot of it to life. I’m gonna flip over into our staircase executive dashboard. This is where, for an exec or a team leader, you can see at a high level where all of your accounts are, what’s at risk where you need to engage how activity is trending for different accounts. It’ll also show you at a glance some of the things and signals you probably want to pay attention to for your customers. For example, accounts that have gone dark where you haven’t had outreach or connection with those accounts.

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Tori Jeffcoat: Probably not something without the AI. Analysis and insights, and surfacing those signals and alerts that you may know or see for all of your customers. Hopefully, at least on a quarterly basis. You take a look and see who you haven’t talked to, but on a quarterly basis might be too late.

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Tori Jeffcoat: Or depending on the number of accounts you’re managing. That might be a challenging thing for a team to do. So a staircase. You can actually flip into any account

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Tori Jeffcoat: any customer and see exactly where they are. All of this data pulled in completely, automatically. So eliminating a lot of the historical human heroics. Roman mentioned a lot of the Csm.

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Tori Jeffcoat: adding emails, logging things to a customer timeline, for example, all of that’s automated with staircase so that you can spend more time understanding those signals. Flagging things like extremely negative messages. Where in staircase you can actually go in and see what the sentiment was of that message open and see the content respond to that message and take that quick action for every customer account at scale.

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Tori Jeffcoat: It automatically pulls in your sentiment. So analyzing again every email, every chat, every phone call that you’re having with your customers flagging where you have a negative sentiment, or where maybe there’s things that you as a human, if you’re a super optimistic, pretty positive person. Maybe you don’t catch when a customer has a couple of high risk things. But AI can understand in the context and in the customer success post sales context, where some of those signals might be a negative sentiment, for example, and help you to flag those and take better action.

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Tori Jeffcoat: What’s really cool about staircase, too, is it’ll flag these insights. So it does an automated totally autonomous analysis of all of those conversations to flag. When again, an account has gone dark, when you haven’t had a Qvr. Meeting. If there’s a churn risk or a stakeholder change, for example, things that you, as a human might find it challenging to see and understand. For all of your accounts.

04:25:27.480 –> 04:25:55.180
Tori Jeffcoat: it also helps you with stakeholder understanding of where you have strong or weak relationships. So one of my favorite features in staircase is that I can actually see where I have strong relationships with a customer when they’re responding effectively when they have a positive, informal sentiment. Maybe we have a good personal relationship for me to know when to engage with that stakeholder or champion to drive an account forward, or where maybe you only have a couple of strong relationships, a couple of single points of failure, perhaps, or negative relationships with your customers as well.

04:25:55.540 –> 04:26:08.370
Tori Jeffcoat: and then the last thing I’ll show really quickly in staircase. Is a lot of the out of box out of the box reports. That are super impactful for how you manage and understand your team and their time. The one I’ll highlight really quickly. Here is our team efficiency report.

04:26:08.670 –> 04:26:34.889
Tori Jeffcoat: and you can see where the AI is analyzing how much time and effort your team is spending on an account compared to how much arr they’re bringing into your business, and where you might be over or under investing in certain accounts. So this is a really great way for you to understand where your team’s time is going, where you might need to think about changing segmentation or shifting around your teams to better support your customers and focus on the key parts of your business, where you need to to be spending that time and effort.

04:26:35.180 –> 04:26:58.260
Tori Jeffcoat: So staircase is a really exciting way for you to again take all of this data in, understand it, aggregate it, and make informed analysis to better serve your customers at scale, automating away so much of what used to depend on humans to flag, understand? Know their customers again. Spend all of that time logging things into an account, in the 1st place, to be able to understand and absorb those signals.

04:26:58.370 –> 04:27:15.349
Tori Jeffcoat: The last thing I want to show just a couple of quick slides on after staircase. Is kind of the future of agents that Roman touched on with our renewal agent. So gain sites in the process of building. This is not a live Demo. But just an illustrative example of how we’re thinking about renewal agents and the Atlas agent.

04:27:15.380 –> 04:27:33.639
Tori Jeffcoat: layer of gainsight. Our renewal agent helps to assign work and support, extending your team again to things like your long tail, where maybe you don’t have a human to engage your customers today. So if you’re engaging a renewal agent in this example, assigning a call to action or a task is what we call them in gainsight, but assigning a call to action to a renewal agent.

04:27:33.660 –> 04:27:58.639
Tori Jeffcoat: the agent will automatically go back and analyze that customer. 360 support tickets that customers submitted diagnose. If that customer is at risk, or what the issues were in those support tickets to understand. If that’s something that needs to be escalated to a human, or where an agent can kind of engage, understand your usage patterns? And just understand what your customer needs are, and if they should proceed, bring in a human or can complete an outreach to the customer.

04:27:59.140 –> 04:28:15.949
Tori Jeffcoat: The agent would then craft a complete email to that customer, including their usage. What successes they’ve seen, information about their renewal all the things that a human typically would have to kind of absorb. But agents help to scale and automate so much of this process that we just haven’t been able to to do before.

04:28:16.140 –> 04:28:19.109
Tori Jeffcoat: And emails, phone calls to your customers are possible

04:28:19.280 –> 04:28:45.050
Tori Jeffcoat: ultimately, always making sure that your humans managing your agent program have a way to see where that agent is engaging. How many companies they’re engaging with, what the uplift on in this case renewals for a renewal agent is as well as where they have in flight jobs where things have been escalated to a human where they’ve reached out and completed a renewal for an account. So you always have a clear view of where you stand, where agents are headed and what to do from there.

04:28:46.260 –> 04:28:57.840
Tori Jeffcoat: So I know we are at time. I think, Roman, I’ll hand it back over to you very quickly to complete just a super quick takeaway slide, but hopefully, a good visual of some of the things we’re building and the things we have live like staircase around. How Gainsight’s thinking about agents.

04:28:57.840 –> 04:29:01.863
Roman Dalichow: Thanks Tori and I love the renewal agent. Just I just think about how many times like

04:29:02.230 –> 04:29:28.930
Roman Dalichow: a renewal process is broken and somebody doesn’t get the renewal paperwork, and they make a decision to do something else, even though they want to keep going. Yeah, as Tori mentioned, I’m gonna I’m gonna wrap us up here with a couple of tips, and one of them Tori already mentioned when she spoke. But, like your AI agents, they won’t be able to fix or work on broken foundations. Right? So you need the right programs in place. You need the right data in place. But when you have that agents can sit, sit on top of that and really help amplify your strategy.

04:29:28.990 –> 04:29:35.759
Roman Dalichow: It’s important to identify also which processes can be most easily and successfully accomplished via AI.

04:29:35.870 –> 04:29:58.129
Roman Dalichow: I would not recommend going to your most complex processes with your biggest customers, with an agent the 1st time you install it. Today’s agents, even though they’re already helping us reimagine some workflows and and drive administrative efficiency. Tomorrow’s agents are going to do much, much more than that right. They’ll simulate the outcomes. As I mentioned earlier, they’ll analyze probabilities, and they’ll recommend the right course of action, and then even execute if you want them to.

04:29:58.180 –> 04:30:13.729
Roman Dalichow: And so you have to be willing to let go a little bit and delegate work to technology and data and let it make some decisions for you. And that requires change management as well as strong leadership across not only your go to market teams, but executive teams as well.

04:30:13.830 –> 04:30:38.470
Roman Dalichow: And then, finally, if you’re selling technology today, you know, some of the hurdles around security and privacy within your customers. And so if you’re looking at exploring AI technology and bringing it into your organization. Getting ahead of those conversations is really important, so that you can really benefit when a vendor brings something that would be a 10 X impact to your business, and that just knowing that data is going to be massively impacted

04:30:38.470 –> 04:30:49.480
Roman Dalichow: for you. As you think about the future of your organization. And so with that from Tori and I thank you so much. We’re excited to continue to innovate and go to market and march towards the future together.

04:30:50.770 –> 04:31:00.350
Julia Nimchinski: Thank you so much, Tori. Thank you so much, Roman. To all of you. Ask question in our slack. Please do reach out to Roman and tori directly.

04:31:00.720 –> 04:31:07.259
Julia Nimchinski: And yeah, what’s what’s the best way to get into the gain side universe scan the code or.