Hande Cilingir: Welcome, everybody – today we are discussing a very timely and critical topic for CMOs and Marketing and Customer Engagement Leaders; that is, The AI Reset: or, more practically, what we can call it is “How CMOs Will Succeed or Fail with Agentic Marketing in Customer Engagement.” So, that’s what we are going to talk about today. I’m joined by our guest speaker, one of the most knowledgeable people in the industry. And I’m pretty sure that I’m going to enjoy the conversation with him. Rusty Warner, VP Principal Analyst, Forrester. Rusty’s research focuses on enterprise marketing technologies, and he works with vendors like us and B2C marketing leaders, day in and day out. And Rusty, thank you for being with me today. I think it not only means a lot for me and for Insider One, and also it means a lot for this audience, because you are one of the experts in this industry.

Rusty Warner: Welcome. Thank you Hande, and it’s a pleasure to be here. I talk about AI a lot with lots of different people, but I have to say, some of the questions that we’ve gone through to prepare for today’s conversation really made me put my thinking cap on. So I’m really looking forward to the discussion

Hande Cilingir: Same Rusty, thank you very much. It’s my pleasure. Maybe we can start straight away, and maybe we can start with a number, which is 60%. So, what do we think that number represents? Let’s think for a moment. Let’s pause for a moment, and let’s think what 60% means in today’s AI-dominated world. Well, ladies and gentlemen, 60% of AI’s total value creation in sales and marketing will come from agentic AI. So, agentic AI is something that every single marketing leader should be knowledgeable about and reading about. So that’s also one of the reasons that we are running this seminar, this webinar, today with Rusty. At the same time, McKinsey also predicted that by 2028, 68% of customer interactions will be handled by agentic AI, which is not, I think, too far into the future. So, Rusty, your own research also highlights that 2026 will be a pivotal year where AI becomes embedded through the tech stack and workflows. So, what are you seeing at Forrester? And what is your take currently? 

Rusty Warner: Absolutely, Hande, we see the same trends that back up the numbers that you just showed from McKinsey, where, by 2028, there will be a large number of organizations that are leveraging agentic AI capabilities, but we think we’re off to a fairly slow start in 2026. As you can see here, we think that fewer than 15% of organizations will be able to claim that they have fully agentic capabilities. But don’t panic, between 15% and 68%, we do think that there will be some embedded AI capabilities, where there will be agentic AI for task-specific functions inside applications across at least 40% of our applications by the end of 2026. So we are accelerating rapidly, so that some of those numbers you showed, I think, will turn out to be reality by the time we hit 2028. We see that, for the organizations that do adopt agentic capabilities, they’re seeing some great returns, up to an hour a day of productivity is gained for some of these agentic applications. What’s important for me is where that efficiency comes, as you can see here, up to 10 times faster campaign development. So, if I’m able to do campaigns 10 times faster, think about the opportunities for marketing in terms of how they can engage at scale with their customers in new and better ways. Of course, I think the biggest change that will come, and 2026 will start to see this change happen, is how we think about AI from a worker-centric perspective. I think, right now, many people think of AI as an assistant. So, if you’re a marketer, you might be developing an audience and you ask AI for help, or you might be developing some content and you ask AI for help. You might be defining a campaign workflow and you get some help, but with agentic AI, all of that will change. Instead of getting some help with all of these human-oriented tasks, the humans can define the guardrails. I might say I would like to figure out how I can engage with customers that might be interested in a certain product or service, and I let the AI figure out the audience, I let the AI figure out the campaign, content, and the channels, and, in some cases, then even automate that. And that’s a very different world when we think of the humans defining the work and the AI performing it, instead of AI just being there as a bit of a helper when the worker might need it.

Hande Cilingir: Well, thank you, Rusty, this was really insightful. I think we are already beginning to see winners and losers emerging, as some CMOs are breaking through the AI pilots phase to start driving value from their AI initiatives and embedded across marketing operations. But I think still, it’s a small group pulling ahead, and also it’s one of our intentions to increase our number of CMOs by helping them to be more agentic AI adapted. 

Hande Cilingir: So, why do I say that? Across Fortune 250 companies, more than 80% still report no significant gains or meaningful returns from their AI initiatives, and I think that’s a pretty alarming statistic. So, maybe at this point I can, I can try to explain a little bit why CMOs are failing with agentic AI, and maybe how or what they should do, these slides will follow. But first of all, the reality for many CMOs is that either they don’t know if they have the right technology to allow them to unlock agentic AI or, more fundamentally, Rusty, they are not knowledgeable enough about agentic AI. What makes it different from other forms of AI? So they don’t know how to drive meaningful impacts or output from agentic AI yet. I think that’s why many get stuck in the experimentation or pilot phase and become one of the 80% who are not driving value from their initiatives, and they cannot embed agentic AI fully across workflows or operations. And I think for those CMOs, they still see AI as a collection of tools with MarTech instead of what it’s becoming, the decisioning layer. The entire customer engagement ecosystem is being redefined. So decision ownership is shifting from humans to systems, as we all know and hear, but in practice, although agentic AI is evolving beyond co-pilots and campaign tools into intelligent systems, and that’s my take, by the way, still, CMOs are struggling to increase their adoption in that. And, Rusty, as someone who is actually following the industry very closely, and maybe even you are influencing it from time to time, what you are hearing from the conversations that you are having, we would like to be pretty much happy to know your thoughts on this.

Rusty Warner: Sure. Well, I have to say I’m hearing similar things to what you just described, and it’s because agentic AI is so new. We have seen predictive AI, we’ve seen generative AI and how it gets used to support conversational AI, but agentic AI is new because of the intelligence that also has autonomy, and I think that’s the thing that a lot of people struggle with. There are no playbooks here. There are no best practices. And, as you pointed out, I think a lot of people don’t know how to measure the impact, so they don’t set goals for these pilots. Or, if they do get something from experiment into production, they haven’t really thought about the business impact. And, if they can’t articulate that, then, even if it’s a great new capability, it might get shut down because the business is just not seeing the return on that investment. In fact, we think maybe as many as a quarter of the experiments that go into production will get shut down in 2026 if they don’t demonstrate that ROI, so it’s incredibly important. And then, when it comes to the learning, we know about data, we know about models, we know about applications. But what changes with AI, again, is that autonomy, which adds that extra layer of complexity, and there has to be a learning curve associated with that. What I mentioned earlier about how you wouldn’t just leverage the AI as an assistant or a helper, but you would actually entrust the AI with a task, that will require some changes to the way people think and the way they approach a workflow within any number of marketing tasks, so we have to take into account that learning curve. It will require time to build up confidence as well. Our research shows that only about 37% of workers today say that they trust the autonomy of AI. So, until we get more confidence, those workers are never going to think about how they need to change their day-to-day work or the workflows that support them. They’re just not going to be able to get there until we build up that trust. So we will have a lot of work to do in order to prove the value if we want this to be a pivotal year in 2026 that leads us towards some of this change.

Hande Cilingir: You’re right. I totally agree. And thank you Rusty. Maybe at this point I can also briefly talk about how some CMOs are, pulling ahead. And I think the CMOs who are pulling ahead are able to do so, firstly, because they have a solid understanding of the evolution of AI and the different forms of AI. That understanding, I think, most of the time, is pretty much critical to then be able to unlock the full value of agentic AI. When you understand and believe in this value, AI, a new architecture for marketing and customer engagement is being built, and then you have more awareness, and also urge to leverage agentic AI. And brands need AI at the core of their technology, technical ecosystem, not simply as a tactic to drive growth, but as they see it, as the foundation for scalable, autonomous revenue generation. I think this mentality is pretty much critical. So, let’s first get a solid understanding of altogether in this webinar how AI has evolved in a customer’s engagement. So, I think it started with predictive, which has been around for more than a decade. At Insider One, like many years ago, we were one of the first technology vendors to incorporate predictive AI for commerce use cases. And then came generative, where AI could help marketers create, generating subject lines, immediate images, copy, and then it turned into conversational AI, where insights could be drawn through conversations. And today, agentic AI, where agents really become the autonomous operating layer, and decision ownership transfers from humans to agents. So, Rusty, I think that can be the brief definition of where we are today and the evolution of AI. And I think you had a great slide which explained the difference between agentic AI and agents. It’s one of the, by the way, most common questions coming from digital marketers. What is the difference? At this point, we will be happy to hear your thoughts. 

Rusty Warner: Yeah, we get that question a lot, because everyone is talking about agentic AI, and often that foundational system that underpins agentic capabilities gets confused with the agents themselves. But we really think there’s the need to understand the complexity of the systems that would support agents themselves. So the tools, the architecture, including the data, the models, the rules that you would apply are necessary if you’re going to build agents and have those agents actually perform autonomously, and eventually not just serve as agents capable of tasks, but actually start to replace full application capability, because they will have the reasoning and the autonomy that’s necessary to do that. What I like about what you laid out, about the evolution from predictive through generative, through conversational to agentic, is that that, I think, is what will be required for people to understand especially CMOs and marketing teams, so that they can build more trust, if they can see the systems underneath and how that underpins the agent, so that the agent is acting autonomously, but based on intelligence from within the organization, I think that in will accelerate the trust and the confidence issue that we’re seeing right now. It will also help you figure out exactly what elements of the business the agent can impact, so that you can begin to put those measurement frameworks into place, so that you can improve ROI.

Hande Cilingir: Very well explained. Thank you very much, Rusty, I think it’s going to be helpful for all CMOs and digital marketing teams out there. Critically for CMOs, I think the key difference to know is that what makes agentic AI unique compared to other forms of AI is that it’s proactive, strategic and has the ability to be fully autonomous. And in this model, human intelligence and artificial intelligence operate as one. I think that’s also important to know regarding the understanding of how agentic AI works, and what we are seeing is not only standalone LLMs. Today, agents and agentic tools, but I think, a new architecture of agentic systems that will give way to entire agentic ecosystems within organizations where AI is no longer the tool. It’s now the operator. AI is the operator. So let’s bring the conversation, Rusty, back to the short term and immediate term. What are you seeing as the biggest outcomes and immediate use cases that you think will deliver impact for CMOs? 

Rusty Warner: In marketing, we’re seeing a number of use cases. Of course, if I back up to 2024, when we were first seeing the generative AI use cases appear, of course, that was building on what we’d always done with predictive AI to treat content differently, to generate copy, to generate images, to maybe even bring natural language capabilities to some of those predictive AI models that we’d had for years so that they became more accessible for marketers and for business people, and it made it easier for them to use them and get value from them. But now, as we look ahead to agentic AI and that greater reasoning capability, and more importantly, that autonomous capability that comes with agentic AI, I think it finally gives marketers that opportunity to achieve something they’ve talked about for years, which is the concept of always-on marketing, so that it’s not just me sitting down and planning a campaign and sending it out to a lot of people, I can create an environment which is always on so that when customers are engaging with the brand, I can, in a more autonomous way, respond to their needs or understand what they’re looking for, in a better way address the preferences they might have For different channels, so that I’m not desperately trying to reach them on email if I’m able to serve their needs when they’re engaging with my commerce platform. What that will mean for the organization on a broader scale, I think, is marketing coming together with the commerce team, with the customer service team, with sales, with people that are focused on customer experience. So that we can now think about this, not on a campaign level, but on a journey level. And keep in mind that at Forrester, we really define the journey as the customer’s path. So it’s not your workflows, it’s not what you put on a canvas inside a campaign tool. It truly is the customer’s path, and so agentic AI gives us the opportunity to be more responsive to that customer and able to serve their needs in the way that they expect from the brand. And that happens because of the embedded intelligence that starts with the data, but then builds as a layer on top of that so that it supports the way we think about understanding our customers, the way we think about our brand strategy, and the customer experiences that we want our customers to have, all the way through to the way we develop content for different channels, and the way we operate in marketing as it comes together with transactional opportunities in commerce, or indeed in new ways, we’re already seeing how we can check out if we’re in OpenAI and ChatGPT, or we can now make purchases from a search engine which is AI-enabled, or we maybe even can click on an ad and make a purchase inside a social media channel. So connecting marketing to all of that in a more autonomous way will really change what we’re able to do today, even as good as predictive or generative or conversational AI, as there are just so many new opportunities with agentic AI.

Hande Cilingir: I like the saying always-on marketing, and I think that’s where the world is heading today, we are already there. So that’s why we built Agent One.  Our autonomous and purpose built agents specifically for customer engagement. And the reason Insider One built Insider One’s Agent One is, we have built this like agents for marketers and their end customers. These agents are fully live and operational today and always-on, and as a CEO and founder, what I have been blown away by is the adaption and usage of these agents across our clients currently. If you are looking at how and where to get started with increasing agentic revenue generation, I think then this is a great starting point. Let’s start with our agents, which have been built to interact with the end customer. The first one is and the biggest friction points in e-Commerce today is product discovery, as we all know. So the first one, the first agent, is actually solving for this. Our Shopping Agent can be integrated across your own channels, like website or app, or across third party channels like Instagram or WhatsApp, and it helps drive the shoppers to buy. Imagine a shopper simply asking, I need a lightweight running shoe for marathon training. Shopping Agent doesn’t force the customer to do the work. It responds like an expert associate. It understands the context, asks questions to recommend the best products, it asks clarifying questions. And this contextual intelligence is what sets the Shopping Agent apart. And not only it doesn’t only deliver a better experience, but it also delivers better results. And it does this by combining first advanced search and merge capabilities that semantically understands a constant consumer’s query, and it can detect the context. Second, it has deep behavioral understanding through an integration to our own CDP, which means we can identify individual customers and ensure that insights and data feed both ways for meaningful interactions. That means our AI recommendation models learn from every single interaction, and this unlocks three outcomes. First outcome, it accelerates product discovery. Second, it increases purchase confidence, and third, it maximizes the value of every interaction. Shopping Agent can drive revenue autonomously. Customers like Miele, Braun, Slazenger are already driving significant gains like 30%, more than 30% conversation rate for normal customers, 22% higher average order value. So Rusty, here, I have one more question for you after talking about the capabilities of the Shopping Agent of Insider One, what was the best shopping agent that you have experienced recently? And honestly, please, let’s answer this. I know that you’re a very direct and honest person. Honestly, what was the best shopping agent that you have experienced recently?

Rusty Warner: Well, it was a shopping agent, but it wasn’t related to commerce, per se. I had a great experience when I was traveling. And I won’t mention the brands, but I was traveling, I was out of the country, and I was traveling with an airline that I don’t typically use, but they had built an agent into WhatsApp so that when I received my “it’s time to check-in” message. It was in WhatsApp, as opposed to another type of message. And then the agent actually asked me if I would like to upgrade to business class, and I clicked and the price looked good. So I said, sure, I’ll upgrade it. Then it was able to connect to my bank’s app on my mobile. Again, I’m out of the country. I don’t have a relationship with this airline, but it connected to my banking app so that I could approve the credit card transaction, and then immediately brought me back to WhatsApp. So I did everything within WhatsApp, as opposed to going to a website or clicking on an email or anything else. Now, obviously, there was a lot going on behind the scenes, and it wasn’t all in WhatsApp, but for me, the agentic approach and making that possible in WhatsApp, which for me, was a familiar channel, as I was traveling out of the country, I thought that was a pretty good experience.

Hande Cilingir: That sounds pretty much familiar. And thank you very much for sharing this beautiful experience. Now, let’s move from buying experience to serving experiences, because the moment a customer needs support is one of the most, I think, critical moments in the entire relationship with the brand. I think most support experiences today still feel broken, long wait times and the secret queues, but support has the potential to be a loyalty engine and instead of a cost center. That’s why we built our Support Agent. Insider One Support Agent is an agent capable of resolving issues autonomously, intelligently and most importantly, with context. What makes Support Agent different from normal bots is the in-depth understanding it has about the customer because it’s connected to our CDP, CRM systems and other customer data resources. It doesn’t treat every conversation like a blank slate. It understands who the customer is, their purchase history, their behavior, their preferences, and even the micro moments that led them to ask for help. And also, Support Agent can answer questions, troubleshoot issues, guide customers without waiting for an available human agent and quitting human dependencies and obviously increasing the efficiency a lot. It can even take autonomous action with consent from changing an order, processing a cancelation, upgrade, upgrading a subscription, the agent doesn’t just answer questions, it can actually completes the action for the customers safely and securely, similar to the story that you shared, and because It understands context, behavior, and intent, every response feels personalized. Customers don’t feel like they are talking to a bot. They feel like they are talking to someone who actually understands them and supports them. So instead of support being reactive and expensive, it becomes something entirely different, unique, personalized, proactive, intelligent leader of customer experience that resolves problems faster, builds trust and turns service movements into loyalty moments. So you can see on the slide some of the results that Insider One customers are seeing today from a trend 29% reduction in the cost to serve per customer to improve CSAT and 51% automatic resolution without human intervention. But we didn’t only create agents for customer interactions. We also build agents for marketing and customer engagement professionals. It shouldn’t be helping only to improve the customer’s experience of the end users. We believe that agents with their capabilities should be also able to help the marketers themselves. So marketing teams are running multi-million dollar campaigns across channels, across segments and different life cycle stages, keeping on top of everything is near impossible for marketers. So they don’t need more dashboards. They need an intelligent analyst working beside them in real time, and that’s exactly what Insights Agent delivers. Insights Agent analyzes campaign performance, audience behavior and channel signals. And it doesn’t just surface metrics. It explains what’s happening, why it’s happening, and makes suggestions and takes actions on what should happen next. So instead of digging through reports, exporting data, marketers can ask questions like, “Why did conversations drop today?”, “Which segment is driving the most revenue now?”, “What change will improve performance immediately?”, and the agent provides clear answers and recommendations just in seconds. It detects campaign risks before they become problems, and Insights Agent identifies anomalies and performance drops early, allowing marketers to adjust campaigns in real time and protect revenue. And it also identifies and scales winning strategies. The agent continuously analyzes what’s working across journeys, audiences and channels, and at the end of the day, it helps replicate those patterns so success can scale much faster. On top of that, Insights Agent anticipates trends before competitors even see them, by analyzing real time signals across channels and subscriber behavior and Insights Agent also surfaces emerging patterns that help marketers adjust strategy earlier. So long story short, instead of marketing teams constantly reacting to yesterday’s report, thanks to Insights Agent, they finally gain something far more powerful. 

Hande Cilingir: So in addition to these purpose built agents, we have also released our MCP Server to give marketing and customer engagement teams the ability to use their data inside LLMs they already use and prefer. MCP server allows our customers to connect any LLM directly to Insider One, whatever you use securely in real time and with read only access. So instead of exporting data, your teams can simply ask, and the LLM retrieves the answer instantly from live data that saves such precious capability, no dashboards, no manual reports, no delays, open, flexible AI access through our MCP Server with enterprise grade security and governance for sure. And Rusty, I talk too much at this point. I’m also wondering if your opinion about the feature of the stack is more open. Can we say that? Is that fair? I will be very happy to hear your thoughts on this.

Rusty Warner: Sure. Well, I think what you showed was great, but even reading between the lines, we can start to see how these agents that are customer facing or marketer facing are going to change things. For example, when you talked about your Insights Agent. It’s great that an Insights Agent could give you actionable recommendations to improve a campaign, but what I see is the real opportunity is leveraging that Insights Agent to give you insights on things as they’re happening. Imagine you’ve got a customer using the Shopping Agent or using the Support agent, and then the Insights Agent can see what’s happening in real time and provide you insights that let you adjust your engagement strategy with that customer or customers who are similar to that person. And you can do that without looking at what it would take to improve a campaign that’s going to run tomorrow. You can do that now, and that only happens if you’ve got this kind of embedded intelligence that would let you connect the dots. What we’re seeing, just like you showed, is that every channel becomes interactive. Email is no longer a sending channel because of AMP-enabled email capabilities or agent capabilities that are connected to that email, it becomes interactive. The example I shared about WhatsApp wasn’t just a message. I was able to actually do something and complete a transaction and purchase an upgrade. So every channel becomes interactive. There’s a constant flow of data coming in from customers as they’re using those agents. And so an Insights Agent becomes critical to help you process that in real time, adjust and evolve your strategy. The other thing I’d say is I thought it was really important that you shared a customer facing example and an employee facing example. Those are two of the agent types that we are seeing more and more as agentic AI is in development in organizations across different industries. We then are seeing some agents that are more under the covers, where there might be an automation agent or a governance agent that might sit underneath. So it is doing a lot of important work behind the scenes, and those, of course, are necessary to bring to life what we saw in your examples with the customer agents or with the marketing agents.

Hande Cilingir: Very insightful. Thank you so much. It’s always great to hear your thoughts on this. I think on the consumer side, there are also huge shifts happening in how consumers find information and make decisions currently. For years, teams optimized for search. Now, customers don’t search. They ask, What should I buy? What is the best opinion for me? And the decision is increasingly made inside that conversation, interfaces like ChatGPT are quickly becoming the gatekeeper of discovery and conversion. And as a brand, obviously you need to be part of it, but most are completely disconnected from it. So conversations are happening, but they are invisible. They are not personalized, and they are not driving measurable outcomes. That’s the challenge at the moment. That’s why we built our innovative integration with ChatGPT Apps. This allows Insider One campaigns to live inside ChatGPT itself. So instead of waiting for a customer to come to your website, you meet them at the moment of intent, right within the ChatGPT app. And this allows brands to deliver relevant recommendations, personalized offers and context aware experiences and most critically, every interaction flows back into Insider One, into the customer profile, into your campaigns, into your revenue reporting, everything. So, helping you turn ChatGPT into a part of your customer engagement ecosystem, and it drives revenue at the end of the day, which is our which is the ultimate purpose, obviously.There is a one important distinction in here, the ones who are talking about that, the ones who can really execute that Insider One currently executing it. And we would like to have marketers out there to execute AI-native and autonomous campaigns, so Rusty, anything you would like to add or comment on what’s already developed or the roadmap. And also, anything else in terms of what we have talked about so far. So this is just the beginning. We all know this. We all feel it. And also this is just the beginning for Insider One in terms of our products, our roadmap. It’s roadmap, at Insider One, our roadmap, our product and development team is delivering against the most ambitious product and AI roadmap to help marketing and customer engagement teams so the teams, customer engagement teams moving from what they need now to execute at scale, that’s also what we are helping through things like agents, integrations and our MCP server to what they need next so AI, builders, design and copywriting agents to eventually achieve the ultimate goal of the autonomous revenue generation where autonomous agents are acting as the operators and executors and marketers set the strategy that’s some of the things that we would like to help, we are helping on customer engagement teams and where decision ownership is shifting from humans to systems. I know that we are hearing this a lot, but that’s the reality and agentic AI evolves beyond co pilots and campaign tools into intelligence systems that ingest live signals and determine the next best action in real time and orchestrate customer engagement across every channel and interaction and in this new paradigm, brands need AI at the core of their technological ecosystem, not simply as a growth tactic, but as the foundation and core of their technology. That’s the vision behind the first multi-agent platform built for customer engagement at Insider One which operationalizes AI decisioning at scale to enable end-to-end autonomous management of customer engagement for every individual customer. I know that most of the time, those are the things that marketers hear a lot. There is one important distinction here, the ones who are talking about that, the ones who can really execute that. Insider One is currently executing it. And we would like to have marketers out there to execute AI-native and autonomous campaigns. So Rusty, anything you would like to add or comment on what’s already developed or the roadmap. And also, anything else in terms of what we have talked about so far.

Rusty Warner: Sure. Well, first, you said a little while ago in the presentation that agentic AI is not just a tool, it’s an operator, and we agree wholeheartedly with that. And I would encourage people to think about agentic AI, not just as a technology investment, but as a new operating model for the company. We have a real opportunity here to reboot what we’ve been doing with our so called stacks that weren’t fully integrated, so that we can actually turn them into a more interconnected ecosystem where we can connect not only the different aspects of marketing, but we can connect marketing with commerce and other functions within the brand, as well as with what customers are doing outside of the brand, as you showed with open AI and ChatGPT or with WhatsApp. So there’s a lot of opportunity here to actually see agentic AI as the catalyst for change, and to embrace it as a new operating model beyond what it provides at a technology level. And I think the people who embrace that and are willing to do all of that hard work with the change management that will be required in 2026 those will be the people that are able to say by the end of 2028 they’re part of those 60 or 68% that McKinsey mentioned, who are getting real value out of agentic AI.

Hande Cilingir: That’s right. I totally agree. And I think the next 12-14 months will define competitive positioning for years to come. Everything is happening so quickly and CMOs, who successfully move out of pilot mode and into enterprise scale will build out defensible advantages in brand recognition, customer loyalty and technical expertise that will compound and make it difficult for their competitors to catch up I think. So, the next 18-24 months is so crucial, I think, for the brands and those who, who struggle to define a clear vision, execution and align internally and build capabilities with the right partners, will be, unfortunately left behind. What we are seeing at Insider One working with our customers, is that those doing well, they start with intention. They are not blindly testing and experimenting with agentic AI and I think so many CMOs and leaders feel the urgency to experiment, but without clarity. This is our checklist that we use with our own customers to accelerate AI initiatives and provide better outcomes for customers and teams. So step one, get clarity for yourself and your leaders, acknowledge the biggest challenges and opportunities you are facing as a business and as a marketing organization. And accept that workflows and operations will need to be rebuilt as agentic AI evolves, then give ownership to each of those challenges and opportunities. So the other one is getting knowledgeable, learning the limits, limitations of build versus buy, and understanding deeply the AI and product roadmap of your existing vendors. The other one is giving ownership to each of those challenges or opportunities. You should be defining who will champion AI in that area, to upscale and increase savings for the entire team. One of the other ones is getting visibility on what your champions are working on. Define a blueprint for measuring success of initiatives and have regular cadence of dedicated meetings to share, share learning and results. And as a last one, ladies and gentlemen, get action oriented. Move out of the pilot phase. Once you have a program, program or initiative that has been proven to be successful, give that champion the resources and means to build that into your workflows and share it with the wider organization too. Those are our advice, Rusty, any other advice that you can share here?

Rusty Warner: Well, I would emphasize that all of the things you see here are important, so all five of them are going to be critical if you’re going to do a good job here. But for me, the two words that jump off the slide and have the most impact here meaningful outcomes, because you should definitely think about what you are trying to deliver, how that will bring impact and change to the business, and find a way to measure that, and that will be how you prove the value to the CFO and the other people who are investing in that capability. It’s how you will build trust and confidence with the people who are using the solution internally. So make sure that you think about that meaningful outcome at the start of the process, measure it throughout, and make sure you then communicate it at the end so that you can keep the momentum going.

Hande Cilingir: Very good advice. Thank you so much. And Rusty, at Insider One, we believe that the future of customer engagement is agentic, autonomous and open, and that’s in this new paradigm. Brands need AI at the core of their technical, technical ecosystem, not simply as a growth tactic, but as the foundation for scalable, autonomous revenue generation. And I know that it’s something that we have repeated since the beginning, but I think it’s very important for brands to understand that we cannot maybe even talk about the like, AI-native solutions, or AI adoption, etc. It should be built by AI with all the two-way conversations current capabilities of brands. I remember one of the sayings, earlier, one day every company will be a software company. I think it’s a time that we should, we should see and for we should foresee that every company will be an AI company one day. So that’s the vision behind the first multi-agent platform built for customer engagement, also Insider One which operationalizes AI decisioning at scale to enable end-to-end, autonomous management of customer engagement for every individual customer. I think this is the time I need to say first, thank you to our guest speaker, Rusty and as mentioned in the beginning, he’s a person that the industry is learning from him. We are learning from him. Hopefully, he’s also learning from us. And it’s always good to see that Rusty is a great supporter of the technologies built beautifully, and a great believer of AI and AI is going to be the most disruptive era for brands, for changing their customer engagement style. Thank you very much for joining us today Rusty. It’s always our pleasure to listening you and for information on any of the topics that we have discussed today, please visit the Forrester or Insider One websites for more insights, and maybe before ending the conversation, Rusty, you may, you may want to take those on liberty to say thank you and bye to our to our audience.

Rusty Warner: Yes, I would like to say thank you to you for hosting me, and thank you for everyone who’s joined. You paid me a lot of compliments, but I have to say I’m constantly learning in this space, and I learn from vendors like Insider One. I learn from every brand and every marketer that I talked to, and I can tell you, maybe is just one thing to finish what, what has come clear to me is that anyone who is out there still thinking of AI as a tool that you can bolt on to the top of what you’re doing, as opposed to using it as a catalyst to change what you’re doing and change your entire operating model, you’re going to find it very difficult to have any meaningful impact until you make some of those more fundamental changes.

Hande Cilingir: I agree. I agree. It’s great. Thank you so much, Rusty, it’s our pleasure. Thank you all very much.

Rusty Warner: Thank you all.