2025 Year in Review with Thor Olof Philogène

Speaker A: Foreign. Welcome to the Insiders Club Podcast, brought to you by Stravito, the enterprise knowledge management solution that drives impactful decision making. I'm your host, Ross Dempsey, and each episode we'll be speaking with insight leaders from across the industry to hear how they're turning insights into business impact. Hi, everyone, and welcome back to the Insiders Club. Now, at this point in the year, we'd normally be gearing up for a big retrospective, a look back in the rearview mirror at what shaped the last 12 months. But honestly, it feels far more important to look ahead, to take a pause, take stock of where we actually are right now and what that really means as we step into 2026. Because I think it's fair to say that 2025 hasn't just been another whirlwind year of AI acceleration, new tools, and rising expectations. It's really been a year of structural and fundamental change in the insight world. The kind of change that doesn't simply resets, it redefines. And that's not just my interpretation. It's really come through loud and clear in our conversations on the podcast this year, and actually has been reinforced in the latest report from Green Book. And their message is pretty stark. We're no longer navigating temporary disruption or a cyclical dip. We're operating in an entirely different market, one that rewards new capabilities, values, different types of offerings, and frankly, is far less forgiving of some of the behaviors that used to guarantee success. And what really stood out to me in that report and, uh, throughout our discussions this year, in fact, is the growing recognition that AI, for all its impact, isn't the strategy, it's the infrastructure enabling the strategy. The real competitive advantage now sits in what Green book called their 3U's of Data Uniqueness, usability, and utilization. In simple terms, do you have something truly distinctive? Can people across your organization actually use it? And does it consistently help the business make better decisions? Because AI can accelerate all of that, but only if the human judgment, the culture, and the operating systems are in place. So, monologue over in today's episode, that's exactly what we're going to unpack. Where the Insights function really stands at this inflection point and what it's going to take to thrive in the market as it is, not the market as we remember it. And to help me map that out, I'm genuinely delighted to welcome someone who's been right at the center of this shift all year, Stravito's founder and CEO, and of course, former host of this Podcast Thor. Olaf Filigeen. Thor, welcome back. Great to have you with us again.

Speaker B: Thanks Rasat. Great to be back. And, um, what can I say? Well, what you've just described really captures the moment we're in. And this isn't just another chapter for the insights function. It's a, uh, genuine inflection point. So just like you, I'm, I'm excited to dig into it with you and uh, hopefully I'll be able to add a bit of clarity, uh, as to where things are heading.

Speaker A: Thanks, Thor. And maybe let's start right there because as we stand here at the end of 2025, after a year marked by rapid AI, uh, adoption, I think it's fair to say, and actually new expectations for insight teams, a real shift towards systems thinking. And I'm curious what's genuinely stood out for you? What are the signals that you've been paying attention to and really what do they tell us about where the industry is heading into next year?

Speaker B: M. Yeah, but, uh, I think you framed the moment exactly right, Ross. Uh, because if I look back at this year, what really stands out is we've collectively moved into a more grounded, more honest phase of the AI conversation. Uh, there's been a lot of, you know, I would agree, incredible excitement, especially around agentic AI. Uh, but if we reflect on it, I think 2025 has also been the year where many organizations have realized something fundamental. AI on its own won't solve the structural challenges, uh, that we haven't yet addressed. And that's not a failure, it's simply maturity. So if you study the pattern it actually mirrors earlier. Technology shifts, the hype arrives instantly, but the transformation happens gradually. Cloud computing, uh, followed that path. And agentic AI is actually not very different. Most organizations are still building the data foundations, uh, the processes, and frankly the governance required for autonomous systems to create real value. And um, we've seen the evidence of that. The mid year MIT and Fortune report that I'm sure many of you have seen, uh, showed that a majority of generative AI pilots are actually struggling. And they're not struggling because the technology was weak. They're struggling because the organization wasn't ready to absorb it. And uh, Gartner made a similar projection around agentic AI. And again, these failures are not about innovation, they're about readiness. So for me, the real shift this year has been that move away from acceleration for its own sake towards a far more thoughtful integration of AI into the way teams work. Uh, the organizations that are seeing meaningful impact are using AI to enhance human capabilities, not replace it, and to build systems that support faster, more confident decisions. And, um, as I see it, it ties to a second shift I've seen, which is around how companies define good when it comes to sharing insights. We're moving past the novelty factor, past experimenting, because something is new and, you know, we all love new things, towards building insights that truly endure, insights that are reusable, cumulative, and genuinely able to guide the business. In other words, we're treating intelligence as infrastructure rather than output. And I think that's a very big shift. And that's also why I think this moment is so important. We're no longer transitioning into a new market. Guess what? We're already in it. And the organizations that will win are not the ones that deploy agents the fastest, but the ones that build with intention, with the right data foundations, the right strategy, and a clear understanding of where human judgment needs to sit in that wider loop. So if I had to summarize it, I'd say this. 2025 has been the year we realized the power of AI isn't so much about automating decisions as elevating them.

Speaker A: Yeah, that's a really, I think, a very apt summary. And I think it actually brings us back to one of the defining themes that we touched on earlier this year, actually. We talked about insight teams shifting from. From being producers of reports to becoming essentially the central nervous system, if you like, of their organizations, you know, powering decisions, not just documenting them. And what's fascinating, I think, is how many leaders have been echoing that shift, particularly in the second half of the year. So I think it feels less like a metaphor now and more like a genuine operating model that businesses are actively trying to build toward. So I'm curious, what change have you seen since then? So how is the role of insight evolving now that companies are moving beyond, you know, static knowledge repositories and starting to build true intelligence systems, really sitting at the core of how they work.

Speaker B: Yes, it's been fascinating to watch this evolve, Ross, uh, because if you think back even just six months, a lot of insights teams were still defining themselves by their deliverables, the reports, the decks studies. But what's become increasingly clear this year is that insight is shifting from output to infrastructure. It's becoming something the business depends on to function, not just something it consumes when needed. And we're actually seeing this across our own customers and across the industry. Teams that are really progressing are the ones building systems that enable consistency in decision, create alignment across stakeholders, and integrate Intelligence into the flow of work and not just the flow of research. But I think there's an important nuance here that we need to make. Uh, centralizing knowledge is only the first step. The real challenge, and frankly the real opportunity is operationalizing it. A lot of organizations have made smart investments, really smart investments in repositories or platforms where all of which is great, but they haven't yet evolved the behaviors, the rituals, or the incentives around using them. Insights still gets treated as a destination instead of a natural part of how the business thinks and how the business acts. And that connects directly to something that Jane Frost raised earlier this year on the podcast, the idea of intelligence capital. Treating Insights as an asset that compounds over time. But like any form of capital, it only creates value when it circulates. If it stays static, if it sits in a system untouched, it actually depreciates, it loses relevance. It becomes unrealized potential, if you will. And what I've seen is what the, uh, most forward thinking teams are doing now is making Insights truly reusable. They're creating mechanisms that allow intelligence to travel across markets, across teams and across decision cycles. They're not just storing knowledge, they're activating it. And that, to me is the real shift. Insights is no longer a library on the side of the organization, becoming a core part of the operating system, if you, if you want to call it that way, absolutely.

Speaker A: And this is something actually my team has been seeing in real time. You can organize your research and Insight very well, make it centralized and searchable, and even make it very engaging and used well. But the sticking point becomes what's the story when the cmo, the CEO, uh, the senior decision makers need the narrative of what they need to think about this year, next year, the five year plan that I think is the new fertile ground that Insight teams, uh, are really moving into. So definitely seeing that from my end as well. So let's build on that then, because it takes us straight into another theme that I think was another defining topic this year. AI, of course, dominated almost every conversation in 2025, whether we're talking about agentic systems copilots or the wave of automation reshaping research workflows. But the thread that kept surfacing across the podcast was really that it's not really about scale for scale's sake. It's about sense making. It's about judgment and context and that very human capability to really interpret what matters and then use AI to accelerate, not replace the that process. I'd love your take on this because I see a lot of chatter about this in the industry, so I'm really interested in your, your perspective here.

Speaker B: Well, the good thing is I actually think, uh, this is where the conversation has really matured over the course of the year. Uh, Ross, Um, because the gap between the hype and the meaningful adoption of AI has become impossible to ignore. And we've all seen the numbers, we, we talked about it earlier of the MIT and Fortune report showing that, uh, more than 90% of generative AI pilots are failing. And that was a real moment of pause for a lot of leaders. And if you dig into it, those failures aren't really about the technology falling short. They're about organizational readiness, missing data foundation, unclear processes, or simply a lack of a human strategy to guide how the system should work. And this I think, in my opinion, connects directly to what we've spoke about in the mid year episode. AI is an amplifier, not a replacement. And when you have clarity, AI is great, helps you, you will be able to scale that clarity. But, uh, when there's fragmentation or ambiguity, AI scales that uh, as well. And that's why the vision of fully autonomous agents is still further away from most organizations than people originally thought, because the underlying infrastructure isn't quite there yet. Now what I am seeing real progress is in, uh, something much more fundamental. Uh, Jake Burkhardt described as, uh, turning research waste into research wealth. Love that, by the way, so well put. Uh, many organizations are sitting on years of insights that have never been fully activated. And AI is helping to change that. It's surfacing connections across studies, revealing patterns in past work. It's bringing forward knowledge that was essentially hidden in plain sight. Uh, and that's where the technology is already creating a ton of genuine value today. And then there is the rise of human centered AI. These are tools that automate the mechanical, repetitive parts of the workflow so teams can focus on what truly matters. And uh, Candace Walton articulated this beautifully with her idea of a storytelling newsroom inside the insights function, AI isn't writing the story. It's creating the space for people to do the interpretation, the creativity, the narrative. Ah, shaping that, uh, you know, what's actually going to move organizations. So, uh, again, if I had to summarize 2025 from an AI perspective, I'd put it this way. This was the year the industry stopped thinking about AI as a standalone solution and started recognizing it as an ecosystem, a set of capabilities that free people to do their best work again, provided the foundations are in place and that human judgment remains at the center, definitely.

Speaker A: And something you said stood out to me. There we were calling back the episode with Candice. And as a career long storyteller, I can absolutely confirm that AI, you know, I could have seen potentially as a threat to my creativity, coming from a, uh, background as a writer. But for sure, I'm doing work that used to take weeks, that I can now do in hours for my team, for customers. And I definitely think that's a very specific and variable use case of where AI can be seen as an accelerator, as an enabler to, to efficiency, not as a replacement to human expertise or experience. So I'm definitely seeing that as well. So I think one theme we haven't touched on yet, but we absolutely have to, because it surfaced itself again and again. Data quality. A subject close to the hearts of many in the insight industry. And when Jane Frost from Mrs. Joined us earlier in the year, she used a phrase that's really, really stayed with me. She said, poor data is like a bad ingredient. It poisons everything downstream. And in an era where AI is accelerating so much, so much of the insight workflow, in fact, that point feels even more urgent. And if the inputs are compromised, the outputs just don't make the mark anymore. They can actively mislead, I would say. So maybe we phrase it like this. How do you see leading organizations safeguarding quality today? Because with more data flowing into systems, more automation shaping, analysis, and more democratization across the business, the risks are arguably higher than they've ever been. So I'm wondering, what does good look like now? And how are companies making sure that the insight they're relying on is actually, quote, trustworthy?

Speaker B: That's such a good question. And that was such a powerful quote you started off from. This is an area where the gap between ambition and reality has been incredibly visible this year, Ross. Because while many organizations have moved quickly to democratized data, the pace of democratization has far outstrip the pace of data literacy. And when you open up large volumes of data without the right guardrails on the right training, you won't get better decisions. You'll get more misinterpretation. Jane captured this perfectly with, with her analogy. Uh, it's such a good quote. If the ingredients are compromises at the start, everything that follow is at risk as well. And what the leading organizations have done from my vantage point is go back to fundamentals, governance, provenance, integrity of the data supply chain. And before you can scale agentic AI or even trust the outputs of basic automation, you need clean data, interoperable systems, and clear governance. Without that, you're building sophistication of top of the, what really should be described as structural instability. And we're seeing a very clear pattern emerge. The most successful deployments are the ones where the speed of AI is paired with the judgment of subject matter experts. When domain leaders are involved early, helping shape the questions, uh, define the use cases, validate the outputs, very often success rates rise dramatically. And interestingly, the biggest wins are not coming from the ambitious big bang projects. They're coming from focused, high value use cases that solve a real problem for the business. And this is also why we put so much emphasis at Stravito at building trusted knowledge ecosystems. Access alone isn't enough. You need confidence in where information came from, how it's been curated, and how it connects the rest of your organizational intelligence. That is no longer a back office responsibility. I think that's an important point to remember. Transparency and curation have become leadership responsibilities because they're materially influence the quality of the decisions being made. And I think it's important to underline that this can't sit with Insight's team alone. Cross functional accountability across data science, product marketing, legal is becoming really essential. Quality cannot be the burden of a single function when the consequences ripple across the entire organization.

Speaker A: Yeah, I think that's definitely true. And I think alongside everything you've just described there, uh, actually with the teams I've been working with this year, sometimes there's, there's an additional very simple solution to this. And it's really empowering Insight teams to communicate boldly and loudly, to lead as the experts. This is what we think, this is what we're telling decision maker is the best route to go. And I think sometimes alongside building those ecosystems you described, it's often the missing ingredient that's the simplest to fix. And thinking about storytelling, it's really a theme that has underscored almost every conversation we've had this year. Whether we were talking about AI as we are now, knowledge management more broadly, data quality, or even organizational silos, eventually everything in some form or another circles back to communication. Because I think at the end of the day, Insight only creates value if it lands, if it sticks, and if it actually moves people to act. And we've heard so many leaders emphasize that the real differentiator now isn't just analytical or uh, technical skill, it's narrative skill. It's the ability to shape understanding, not simply present the information. So Thor, let me put this one to you. Why has storytelling become such a critical power Such a critical skill for insight teams. And how is that changing the way organizations communicate? An act on insight today, from what

Speaker B: you've seen, Ross, I'm so happy that you brought that question because honestly, I think it's one of the biggest capability gaps we're seeing across the industry, but also one of the biggest opportunities because you're absolutely right. Many Insights teams are still hesitant to talk about money. They're incredibly strong on methodology, rigor, sampling, segmentation, all of which matter enormously. But within a business, the language of influence is still the language of value creation. And if you're not speaking that language, it becomes very hard to shape strategic decisions. Nick Graham articulated this beautifully on the show, and Jane Frost echoed it as well. Commercial credibility equals influence. If you can't explain how an insight impacts revenue, cost, risks or growth, then even great research struggles to land in the places where decisions are actually made. And this is where the idea of the T shaped leader becomes so important. Deep research expertise is essential, but it's only half the picture. The other half is broadened. Broad fluency across the organization. Understanding how the business makes money, where the margins are, what the growth levers look like, how decisions really move through the system. Because the leaders who understand that context are the ones who can translate insight into action. It starts there. And we're seeing this reflected in some of our own distributor customers, teams that are connecting insight directly to growth drivers, whether that means accelerating product innovation by spotting patterns across markets, or saving millions by reducing redundant studies or eliminating duplication. When insights start showing up in business cases, in forecasts and P and L conversations, that's when it truly begins to move the organizations. So are we there yet, Ross? I'd say we're getting there unevenly. Some teams are already operating as strategic advisors. Others are still positioned. Uh, they've chosen to position themselves as service functions. And the real shift happens when Insight leaders feel confident putting commercial outcomes at the center of their narrative rather than treating them as a add on at the very end. So I'd say commercial acumen isn't about turning researchers into finance managers. It's about helping them connect the dots. What did we learn? Why does it matter? And how does it change the economics of the decision? Ultimately, that's where the influence comes from. Would you agree with that, Ross?

Speaker A: Yeah, I think that absolutely resonates. And of course there's, there's a myriad of challenges within taking that path and certainly in my career, that's something that's, that's really evolved. I, I think there's been a shift from perhaps insight functions looking to educate the business to become more insight literate to maybe a meeting in the middle and also becoming more business, uh, articulate and marrying those two things together. So I'm definitely seeing that from my end as well. And I think that actually connects, if I can use your phrase around connecting the dots, I think that actually connects to another theme that's been ubiquitous this year from our customer summits in Austin, in Amsterdam, in Paris. And that's silos. Not just the classic silos between functions like, like marketing and research and development, but increasingly the silos within insight teams themselves. Because one of the biggest challenges, challenges leaders keep raising was effectively everyone may have access to information now, but that doesn't mean everyone shares the same understanding of that information. Is that something you're seeing play out at the minute, Thor?

Speaker B: Oh, absolutely. I think has been one of the defining challenges, you know, 2025. And uh, what I'm seeing inside organizations is a clear shift from thinking about data as something to own towards uh, thinking about it as something to orchestrate. Uh, instead of each function guarding its own insights, which we've seen for in the past. Still seeing unfortunately is the most forward thinking companies are building systems that allow intelligence to move across marketing, R and D, customer success, essentially anywhere decisions are being made. It's a genuine systems thinking approach if you will. And uh, we actually heard this clearly at the summit. And uh, Kristen Aldjebruins from Cargill talked about embedding insight directly into day to day workflows, not treating it as a separate layer. Uh, Michelle Sullivan from Target made a similar point. Insight only breaks silos when it becomes everybody's responsibility, not the responsibility of the research team. But there is an important reality check here. Uh, Ross. I think technology can absolutely bridge gaps, but culture has to follow. Otherwise you end up with digital silos, nicer interfaces, sure, but they're all sitting on top of the same fragmentation. Installing a platform isn't a, I would say the challenging part. It's the real work is in building shared language, shared uh, definitions, shared understanding. And that's really been a big focus for us at Strido, helping global enterprises connect their insights across teams. So there is truly one source of truth the whole business can rely on. And this year with tools like AI Personas, we've been exploring how to close another alignment gap. The one where different uh, functions describe the same audience in completely different ways. Most recently we've heard from Simone, uh, Ballerini at Lavazza Group who talked about making Insights conversational, taking them out of static charts and graphs and making it possible to converse with them. That's a major shift in the industry. By doing this, teams are able to see and understand exactly how Insights can affect your specific work, whether that's, uh, brand campaigns, marketing, product innovation and so forth. And that's what actually breaks silos, when everyone sees the same customers through the same lens at the same moment.

Speaker A: I think that's actually a really powerful golden thread. That's a really good way to think about an achievable way to break down silos. And of course we've been talking about silos, I think since Insight became an industry, but it actually leads on to something else I want to touch on that I think is becoming louder and louder as the year went by. And it's the idea that Insight teams can't just think in terms of research anymore. And we've touched on this a little bit, but, but they have to think in terms of revenue impact and business outcome because that role of insight, as we mentioned, has really shifted and maybe been a bit more specific. It's no longer simply an advisory function. It's increasingly a growth function, or at the very least a function that meaningfully contributes to growth. And of course that's more important than ever. We live, uh, in a changing and chaotic world and we've heard from so many leaders on the show that commercial credibility has become one of the biggest determinants of influence. And if you can't link what you do to value creation, it's becoming incredibly difficult to earn, uh, and keep a seat at that decision making table. So I guess my question for you, Thor, and I know you've got some strong views on this, is are we there yet? Are Insight teams truly operating with commercial acumen today? Is this still an emerging capability or is it, you know, something we need to put a lot more time, investment and resource into as an industry?

Speaker B: Ross, the million dollar question. This, I mean this is, I cannot emphasize how important this question is. Yes. And, uh, I think it's one. It's been one of the biggest shifts of the year and honestly one of the most encouraging because when we talk about the capabilities Insights Team need for the future, storytelling consistently shows up as one of the critical skills alongside communication, intelligence, adaptability and commercial acumen. And it makes sense. You know, if you can't communicate an insight in a way that the business understands and remembers it, then the quality of the research almost doesn't matter. That's why I loved Candace Walton's 10 year old rule. If you can't explain the essence of your insights in a way a 10, 10 year old could follow, it's unlikely to travel inside a global organization. And in most cases it won't influence anything. But there's an important balance here. We've heard a lot this year about snackable storytelling. It came up repeatedly at the US Summit, and it can be incredibly powerful for democratizing insights. Breaking silos, short videos, internal podcasts, visual digest. Teams are starting to operate almost like their own content studios. And that's fantastic. The risk, though, is oversimplification. You want insights to be snackable, but also sustainable, something that informs in the moment but also endures over time. The best teams are doing both. They create an accessible entry point that captures attention, but they also build the deeper narrative behind it. They're not compressing the story, they're curating it. And we're seeing something interesting emerge from that. Teams are no longer measuring success by how many people attended a presentation, but by a narrative adoption. Who's repeating the story and meeting who's referencing the insight in planning, who's building on it. So, yes, storytelling has become a power skill, but the real impact comes from how teams use it to build alignment M to make insight not just understood, but shared. That's where the influence comes from, 100%.

Speaker A: And, uh, you know, I've had a lot of experience in this field, uh, over the past 12 months and I think a couple of observations from me as well. Absolutely. Insight teams developing the skill to shoot the arrowhead into the business to garner attention isn't a reductive way of sharing insight. It's a way to get the right brains making the right decisions across the work. They will come back for the detail, they will ask for the deep dive. They will, you know, have that presentation from the team to get into the granular, nitty gritty parts of the insight. And I think something that's really interesting there as well is narrative. Something I've seen on repeat from senior decision makers is in some cases a desperate need for a consumable narrative. And I think something we can all do better as an industry, as an insight industry, is move out of the palace of complexity and adopt a momentum over perfection mindset. Often insight comes too late to the table because we're trying to tell the business everything we know all at once in a perfect and unified presentation that's just too dense for anyone to consume. And actually sharing the actionable and timely insight, even if it's imperfect will generate the right conversations and the right actions from the business, in my experience. But looking ahead to 2026, before I wrap up, I really want to take that look ahead because if 2025 was really the year where we learned how to integrate AI and human intelligence, and that's a tbc, then the obvious question becomes what's next? And so you're in a fairly unique position, I think, to answer that. You've really spent the year speaking with insight leaders all over the world. You're watching how AI is actually evolving inside organizations and you're sitting pretty much at the intersection of research, technology and decision making. So I'd really love to get your view on the road ahead. And I think maybe we frame it in a way that we can revisit next year. A, uh, sort of early marker for 2026 if you like. And I wonder if you could give us three things that you think we should be watching. Are there three predictions? Or if you prefer, one prediction, one fear and one hope for the insight world as we move into next year. A tough question, uh, I admit, yes,

Speaker B: yes, AI is still evolving and we're still learning to use it, as you pointed out. Uh, but I'll give it a go. So if I look ahead, Ross, uh, my prediction is that we're going to see the rise of truly hybrid insight ecosystems, systems that are human led, AI accelerated and much, uh, more tightly aligned to the business. Not AI instead of people and not humans doing everything manually, but a blended model where automation handles the scale and people provide the meaning. It's the direction the industry has been moving towards all year, if you ask me. And uh, I think 2026 is when this becomes the norm rather than the exception. Now, because you did ask about my fear and my fear is that we're going to see increasing scrutiny around AI, ethics, sustainability and even the carbon cost of data processing. And many organizations are not preparing for that. As, uh, AI models grow and more organizations run them in production, the environmental footprint becomes very clear. And then you add the governance dimension, responsible automation, data provenance, model transparency. If organizations don't get ahead of this, my worry is that regulation, uh, will force the conversation faster than teams are ready for. And then what I prefer sharing, which is my hope, my hope is, but I will say I'm genuinely optimistic about this, is that we will see a renewed investment in human capabilities, particularly emotional intelligence and critical judgments. The more AI enters the workflow, the more valuable those human skills become. Interpretation, empathy, storytelling, ethical reasoning. These are things that shape decisions and culture. And my Hope is that 2026 becomes the year we recognize that responsible automation isn't about replacing people, it's about elevating them. So if I had to summarize that, uh, that's my trio. A blended ecosystem, a cautious word of caution around responsibility, and a hope for a more human centered chapter of innovation.

Speaker A: Well, I think that's a delightfully concise and perfect note to end on, Thor, because I think everything we've talked about actually really does point to a bigger shift happening across the industry. You know, insight no longer being a collection of outputs, it being a living system, something that really learns, adapts and strengthens over time. And I think if 2025 was about building the foundations for that system, I think next year it's really going to be the year where we start measuring impact and not just the activity. And it'll become less about how many reports were produced by how many decisions were improved and less about how much data we collected, but how much intelligence was actually used. I think that's the direction of travel and it's a really exciting one. Thor, thank you as always, not just for joining us today, but for the clarity and perspective that you've been providing all year. From all of your interactions with Insight leaders and to, uh, our listeners, thank you again for being part of this community and these conversations we've done, virtual and, uh, live conversations, and they've all been really, really interesting. We'll be back in the new year with more voices, more stories and more insight, of course, into what's shaping the world of research and intelligence. But until then, stay curious and we'll see you in 2026. The Insightus Club podcast is brought to you by Stravito, the enterprise knowledge management solution that drives impactful decision making. To learn more about how STRO helps leading brands make the most of their enterprise knowledge, visit stro.com be sure to click follow so you don't miss out on any future updates. And if you would like even more insightful content, you can subscribe to the Insiders Club newsletter at, uh, the link in the show notes. On behalf of the entire team here at Stravito, thank you for listening.