When Work Becomes Learning: Redesigning the Employee Experience with Samantha Murray

Clover Leaf is an AI-driven coaching platform grounded in the validated behavioral assessments you already know and trust, like disc, anyagram, and 16 types, delivering deeply personalized science-backed coaching that meets your people right where they work and drives real behavior change, trusted by 45,000 teams to help leaders improve communication, collaboration, and performance with 86% reporting more effective teams in as little as 30 days. Clover Leaf turns talent data into practical coaching insights that scale across your organization. Learn more at cloverleaf.me/podcast Welcome to ATD's Talent Development Leader podcast, featuring monthly conversations with the greatest influencers in the talent development field. We cover the latest trends, hot topics, and future-focused ideas that current and aspiring TD leaders need to know. Learn more by visiting www.td.org and searching for talent development leader podcast. Today, I'm joined by Sam Murray. Sam is the founder and CEO of Aligned CX, a strategic advisory firm that helps B2B companies design scalable systems for learning, enablement, and growth. With over a decade of experience in go-to-market, education, and experience leadership, at Shopify and DoChable, Sam brings a rare perspective as both a buyer and builder in the learning technology ecosystem. Today, she advises executives and learning leaders on how to design intelligent systems, aligned journeys, and modern operating models that drive adoption, retention, and business impact. Hi, Sam. Thank you for joining me today. Thank you so much for having me on, and I'm excited to chat. Today, we're talking about the employee experience and how we might redesign work to optimize it. As we're recording, it's January 2026, so I think this is an ideal topic for a new year thinking about how to reimagine, redesign, in a recent report by McKinsey & Company, and this was back in the fall of 2025. The future of the CLO, leading in a world of merged work and learning, CLOs are charged to embrace three transformational changes. Lead beyond the learning function, get serious about data, and align learning with strategic business outcomes. I found this report super interesting, and I wanted to start our conversation today by hearing from you your perspective. At a high level, what's your reaction to these three transformational changes? I think McKinsey is naming what many modern and progressive learning leaders have probably felt for many years, but haven't necessarily always been empowered to actually act on, because none of these changes on their own are radical, but when taken together, it fundamentally redefines the role of the CLO, which is actually really exciting because it transforms CLO from provider of programs, which would be focused on outputs, to I think they call it architect of how work gets done, which is a lot more focused on outcomes. I think it's a huge responsibility shift, and it requires CLOs to sit a lot closer to the functions that they've probably wanted to sit closer to for many years. Strategy, operations, technology, and not just HR itself. I think what McKinsey is really saying here is if learning leaders want to stay in the training lane, then they are at risk of becoming irrelevant. This is the year to really make the changes happen. There's a discussion and there are around data. I have this conversation all the time with learning leaders. We've over-indexed for way too many years on vanity metrics. In rates, hours learned, satisfaction scores, these are things that tell us almost nothing about the capability building and business impact that learning can actually unlock. What's exciting about all of this in the conversation that we're having is the shift towards learning in the flow of work, skills data generated in the flow of work, which I know we're going to get into later, and learning that's actually aligned to business outcomes, which we've needed to do for a really long time. To me, this is less of a learning transformation and more of an operating model transformation. What we're really saying is that learning needs to become how the organization evolves and adapts in this new digital AI world that we're living in. Not something that happens alongside the work, but it's the thing that actually transforms work itself. I think, like you said, we've been talking about this forever. These are perennial issues that pop out. Totally. When we talk about transformation, I think it's interesting how you've mentioned getting how do we get actionable about this? How can CLOs actually make change by not staying up here, but you said sitting closer to the function. I'm super interested to hear your insights on that, especially, because I would love for us to not keep talking about exactly things we need to do, or else become irrelevant. Let's home in on the third change there, transformation, aligning learning with strategic business outcomes. If I've ever heard something said more than this, it always pops up. Clearly, it's a nut that we can't crack that our function has a hard time with. The report states the future of learning is not about abandoning structured programs. It's about reimagining their role. Immersive learning programs, including classes and webinars, will remain essential for passing on culture and leadership. But for skill development, the real opportunity lies in the merged coexistence of work and learning. And work is developmental. Employees can build and refine skills in real time, while still directly contributing to business outcomes. And to me, I think there's the meaning there is making work developmental, like maybe that's how we can really move the needle. What are your thoughts on that? That in and of itself is such an interesting perspective to think about, because again, it changes the conversation from learning as an activity that needs to happen to what is it look like to design work, to remove friction from the experience of work? What is the people experience? What is their experience? And that's the way to get to development during the flow of work, I think. What I appreciate about all of this is that it reframes learning from something that is interrupting work. That's always been the mentality is, okay, I need to pause what I'm doing. I've hit some sort of roadblock. I've hidden a point where maybe I don't know how to do this. And I need to go and log into my LMS. I need to go and search the curriculum that's available to me or the coursework that's available to me. I need to go and figure all of this stuff out and interrupt my flow of work to go and learn and then go back to the job that I was trying to accomplish. And what we're now saying is that's no longer the thing. That's not an expectation that users have. So if you think about employee development in the context of work is a product and we're thinking about designing the product of work for the end user that's experiencing work itself, then our job is to infuse learning in the flow of work and in the context of the job to be done. That's how we get to this place where skill development can actually happen because the skills develop in the moment of need. They develop in the context of decision making and problem solving and getting feedback while the work itself is happening. So I think this is where the role of learning fundamentally changes because instead of asking what program are we going to roll out, what courses do our employees need. The question actually becomes like where in the work do people experience friction or need better support and how do we actually design for that. And this is where I think we talked about this in earlier conversations like customer journey mapping. We call it customer journey mapping. But end user customer employee doesn't matter, right journey mapping and service design blueprinting becomes a really powerful tool for learning leaders because the friction points that we identify in a journey are almost always where skills break down decisions get delayed in the context of work service quality drops and people end up getting frustrated or burnt out because they're not able to achieve what they want to achieve. And this is also where the business feels the pain. So journey mapping is the thing that helps us see the work as it's experienced. Not how like job descriptions describe the work. And then when you do this, you start to really see what are the business outcomes that we want to drive, where are employees experiencing friction in driving those outcomes. And that's where you start to design work itself as the development and not just a learning program as an output. Talk about transformation. Yeah. I'm curious in your work with learning leaders, this sounds like a mindset shift to talk about like the metrics that are constantly focused on butts and seats. That's just what has been hammered into people in this field for so long. So to shift from that to this complete redesign. So looking at you said designing work is a product and integrating learning in the flow of that work. To me, as a mindset shift and curious what your experience has been working with learning leaders on some of this. Yeah. After a percent, it is a mindset shift because typically what happens in learning design, it's like, we know that employees need, let's say we've decided that they need a course on like better stakeholder management or communications or something. That might be helpful in certain contexts. But when you look at the friction that the employees experiencing and you look at what they need to be able to do it. their job effectively, the learning intervention might be like redesigning the handoff between teams, adding some sort of decision checkpoint for leaders, embedding some sort of coaching prompt directly in the flow of whatever it is that they're trying to do. An SOP, right? These are learning interventions, even if they don't look like traditional learning. So that's the mindset shift, it's less on curriculum design, course design, learning outcome, or learning objective, and more on solving for the friction. They're moving friction and that fundamentally looks different and it does require us to think less about maybe learning in the traditional contexts and more about, again, if I'm designing a product for an end user, what does that product need to look, feel, act like in order to unblock the user in accomplishing their job to be done? That's the mindset shift. And I think the product operating model is a really good frame of reference for learning leaders to dive into, to help them understand how to execute. Yeah. I think it's changing vocabulary, too, around what learning is and isn't, and being able to tell that story in a way that the organization can understand and buy in. 100%. I've heard so many learning leaders over the years say, I want the seat at the table, I want I want to have a seat at the table, I want to be taken seriously. But the challenge, I think, has always been maybe learning leaders staying in their own lane of traditional learning, I know I need to develop a curriculum, I need a leadership development program, I need an onboarding program for new employees, these are outputs. When you embed yourself with your chief strategy officer, when you embed yourself with your chief technology officer, your AI officer, right, all of a sudden these new roles that are evolving, that means understanding what's the business trying to do, what does transformation look like for our business, what problems are we trying to solve as a business, how does our workforce, what is the role of the workforce in achieving that transformation or getting to where we want to go as a business, and then leveraging the workforce through learning and learning interventions to get to where we want to go, that's how you get the seat at the table. What an incredible synergy, too, so that moment, opportunity, conversation about redesigning work and that experience of work to address those business problems, those business challenges. So it's about people experience and people development and solving for what's most important to the organization, it's bringing it all together. The conversation has to move, as I said, beyond learning altogether, it can't just be about learning, journey mapping and service design, these are tools in the toolkit, they're really powerful because they help us see where work is breaking down, where employees are feeling friction, where decisions are slowing down, where quality might be suffering, but identifying the problem is only one piece of the equation. What we really need to do, and where I think the real opportunity lies, is in pairing those insights that we uncover with the products operating model, because that's the thing that allows us to actually redesign work in a way that is measurable for one, which is critical at this moment in time, testable, so really running experiments is the model, and I think we'll speak a little bit more about that, and aligned to the business outcomes that the business actually cares about, though when you start to treat work itself like a product and you start to shift your mindset from traditional learning to I'm a product manager, and I'm designing the experience of work, your employees become the users, your workflows and processes are the experience, and business metrics become your success criteria, that's the bridge, that's the bridge between people experience and business performance, instead of just launching some sort of large, one size fits all onboarding program, teams can really start to think about redesigning workflows, defining what better looks like in business terms, so is it speed, is it quality, is it retention, what do we actually care about as a time to value, understanding deeply the metrics that you're trying to drive towards or what success looks like, running experiments, measuring the impact of those experiments in sprints in short cycles, and then iterating and continuously optimizing until you know for sure that it works, and that actually solves such a major problem I think in learning, because we have this tendency to ship big programs that take a lot of time to produce and execute on, and then we wonder why no one's actually adopting the programs or why there's crickets inside our LMS, guys, like all you had to do was break it down into a really small chunk, co-create with your users and make sure that it actually works before you ship a huge, long, standing program. And what a relief to take the pressure off in that sense, right, agility is about, like you said, breaking it up, testing, continuing to iterate, and I think just that approach in itself would be revolutionary, and that's why I see all the time when I work with organizations and learning teams, sometimes that's the easiest mindset shift for them, because I think there's this sense of overwhelm around, oh, transforming from the way that we do things now to working in this like product operating model feels like such a massive transformation, it's too big, we don't know how to do it, and it's applied the model to the transformation. Like you don't need to boil the ocean, you can literally just focus on one single business objective and one friction point that you know is preventing your employees from supporting that business objective, find out what your leading indicator success metric is that's tied to that like larger business objective that you have and design something small that takes you only two weeks to ship and make sure that it works for a small subset or segment of your employees. Does it work? Yes or no? If it didn't, why? Get really curious about why that happened. That's all it takes. I just think learning leaders become overwhelmed by this large transformation and it's no, it's actually so simple when you break it down, but it just requires a curiosity and an experimental mindset and a different approach to how you do things, think of how much of a win that is when you can be like in only a month in two sprint cycles, I proved that this thing is actually removing friction and moving the needle on the thing that we wanted. So imagine being able to go to your executive team like it took only a month and we did this thing and I'm going to double down on it. And honestly, we don't have time to do any other way in the age we live in now with digital transformation and AI with things changing constantly for sure. And we have the tools for the first time in a really long time. We have not had the tools to successfully do this operating model is one great piece of it and it provides a framework for executing on the work, but we've never had the data at our disposal to validate whether or not what we're doing is working. And now with AI, we do. We have all of the things that we need to be able to operate in this way. We're suddenly in a situation where there really isn't an excuse anymore for not operating in this manner and not validating and proving that you're working towards business objectives and that your work as a learning leader as a CLO is to drive the business in the direction that you want it to go. You're the bus driver. It's not the other way around. It's not like I'm sitting in HR and I'm this like reactive function. You're responsible for driving the organization to where it wants to go using the workforce. Absolutely. Gosh, talk to execs all the time about getting them in the driver's seat, getting their functions in the driver's seat, being the ones who are, as you said, driving this forward. I want to talk a little bit more about the layers of the employee experience. Obviously, you know a lot about customer experience, employee experience. When we think about process and workflows in previous conversations, we've talked about the overwhelm of how much work potentially there is to do. How can listeners define what work is most valuable for employees to focus on that will drive business outcomes and what they want to offload to AI? When you think about how we can automate, how we can make our lives easier, more efficient, and then how do you actually elevate the work itself for these objectives? I love this topic. It's so top of mind, I've spoken to so many leaders over the last few months that are thinking about this because they have this mandate inside their organizations to figure out, what can I take over, where are their opportunities for AI to automate things so that we can reduce, not necessarily reduce headcount, but just reallocate folks to more high value, high impact work that actually drives the business forward. And mentally, you cannot optimize the employee experience until you actually have visibility into what people are doing all day long. The first thing is like most organizations I've spoken to are thinking about work redesign and they're trying to redesign work with opinions and like really high level views instead of task level understanding of the jobs that are actually being done across all of the functions and across employees. So the first thing that learning leaders need to do is work with their HR team to map tasks and essentially build what I would call like a lightweight task inventory for a team or a workflow. So pick one team. You don't have to boil the ocean again. If you think in sprints and you think in experimentation, you pick one team or one function to focus on one employee segment and do a task inventory, map the work tie tasks to outcomes, understand what people are actually doing. What does it actually look like? What are all the tools that they're using in their day-to-day, all of those things? And once you have that inventory, you can evaluate those tasks in a really simple two-by-two. So decisions don't turn into debates within the organization. And that two-by-two would look like on one axis, you've got like value impact for the organization and on the other AI automated Is that a word? I'm going to make it a word. Automateability. Okay? I like it. If we do this thing better, faster, does it move a KPI that the business actually cares about, right? Time to value, CSAT, employees satisfaction, win rates, quality, whatever risk caused doesn't matter. Does it actually move a KPI that the business cares about? And on the other axis, on the AI automation side, is it repetitive? Is it rules based in some way? Is it pattern heavy? Is it text-based? These are all things that AI can reliably assist with or automate. And so once you have that two by two and you start to map all of your tasks inside these kind of four quadrants, high value, high automation, high value, low automation, low value, high automation, and low value, low automation, you can really start to see where are the things that you can augment immediately through some sort of co-pilot, automation, AI, etc. What do you want to keep and maybe just redesign? What do you want to automate very aggressively? Because it's super repetitive and you don't need humans doing that work. And then what, these low value and low automation in that quadrant is it even necessary. Do we actually just eliminate this work? Because if it's not providing value and we can't automate it, then do we even need it? Just find this framework provides a really practical view into what makes the most sense to automate. And then another layer that I find super interesting, I think I had mentioned to you in a previous conversation has come to be called beamable. I'm a huge fan of what they're doing because they actually have a tool that makes this process easier. So for anyone listening, please go and check out beamable, they have an awesome solution to this. But they also layer on this idea of joy. What do employees actually like doing? Because we don't want to automate everything just because it can be automated doesn't mean that you should because if employees love doing something and it makes them feel really good about coming to work every day, don't take that away from them, right? Because coming to work every day and enjoying the work that you do is naturally going to lead to higher productivity, it's going to lead to all of the outcomes that you want to drive for. You can't erode culture because that does happen right when we try to automate everything through AI. So I really like that layer and you add that on and see, okay, of the things that are higher value and can be automated. What are the things that we actually do not want to take away from our employees? And that requires speaking to your employees. It requires running focus groups and having conversations, having coffee chats, continuously talking to your users, just like a product manager would and understanding what they care about and what they enjoy, what they don't enjoy, so that then you can layer that on to your two by two. That is cool. I know. So they have such a cool product. I'm a huge fan of their tool and I just think it's a really powerful one right now at this moment in time, most organizations could really benefit from that type of solution. Absolutely. And I love this framework you've provided, Sam, and I also think, for me, it addresses some of the uncertainty, caution about AI and the process of automating, for the sake of automating, making things more efficient because you can. When you put it in this context, and ultimately the end result is the work product, which includes the experience of the employee and the factor of culture. And when we're looking at meaning and purpose and joy and work, and that's part of the equation, that makes AI less scary essentially or the future of AI less scary. I love this. Yeah. I found it helpful to, because I do think that organizations, again, this is another area where they tend to feel a lot of overwhelm and usually overcomplicate it. And this is just a really practical and easy way to understand where the opportunity lies for automation. And then you can really, going back to the product operating model, you can use experimentation to pick one or two things that you might want to automate, figure out how to automate it, use your AI tools, work with your IT team to figure out what that looks like. And then you need to also figure out, once you've done that and you've taken off the work from the plate of the employee, what does their new day-to-day look like? You can't forget about that part of the equation. So that's where the product operating model comes in, redesigning the experience of work, once you've taken away the thing that you've automated, tied to business outcomes, design it as an experiment, work directly with them to co-create what that looks like, and then validate and continue iterating and optimizing to perfect it over time with the people that are actually experiencing the work. Not only does that make them feel like awesome because they have less of the things that maybe they don't like doing, those things have been taken off their plate. They feel like they have ownership over driving meaningful impact for the organization. And they feel like they have a seat at the table and co-creating with their learning team, their HR team, they're going to be way more invested in their work. When I've seen this done well, yeah, you're automating some stuff. And you're inevitably going to see some efficiency gains. If done well, the culture transformation that happens is wild. And that's where the real long-term gains are. That's where the long-term revenue gains are for the organization because everyone's invested in the company and doing what's best for the company. It's just such a game changer. And I've experienced that myself on opposite ends of the spectrum. I've been very fortunate to be with an organization that placed a really high importance on this kind of stuff and the culture was phenomenal and everyone was really bought into the mission. And I've been in organizations where that was not true and I experienced the opposite end of that spectrum. It's night and day to see how much acceleration the business can have in the market just by simply placing this kind of high importance on the employee experience. I think a lot of employees feel out of control when it comes to their careers and having that sense of ownership and buy-in and being able to co-create, I just think, would make all the difference. Yeah. A hundred percent. Let's talk about, and I know you love data and tracking and measuring outcomes and you've given a lot of thought to data and data architecture. I think data was another one of the transformational changes that the McKinsey report noted, one of the three. So we know traditional methods of analyzing performance are somewhat subjective. Talk to us about a different approach to data tracking and performance measurement. Yeah. I'm so glad that McKinsey called this out in the report because I think this is unfortunately where most organizations are furthest behind and where the biggest opportunity lies. So the core issue, I think, isn't that performance data is necessarily subjective. It's that we're measuring the wrong things and in the wrong systems. This most performance measurement data is living in an isolated system, right? You have your performance reviews, you've got your engagement surveys, you have data that exists in your learning platform. So all of this stuff is disconnected. It's sitting in an HRIS, it's sitting in maybe you've got Qualtrics, you've got your LMS. And what ends up happening as a result of that disconnect is you have to retro-specatively analyze the data and it's largely trying to correlate bits and pieces of things to get a picture of what the employee experience actually looked like. You can't actually see anything until it's a lagging indicator and it's too late for you to really do anything about it. You end up with manager bias, you end up with these static little snapshots of performance that aren't reflective of the reality of, again, the total employee experience. And that makes it really difficult to answer the question that leaders actually care about today. Are people actually getting better over time? Are they improving their performance? Is our investment in learning and redesign of work improving the outcomes that we want to see and where are the skills gaps and the capability gaps that are preventing our workforce from like driving the business in their direction that we want to go? One thing that I think about with this that, again, let's keep it super simple, make it really easy, you've got a business objective. Let's say your company's goal for 2026 is to reduce churn, right? Churn is a big problem for the organization and so we're really focused across the company on reducing churn. That requires us to identify churn risk. It requires us to investigate the improved customer satisfaction, improve the experience of the customers. You can't do that without improving the employee experience of work and their ability to conduct their jobs and provide an experience to the customer, right? When you have, let's say, churn a reduction as your business outcome, your primary business outcome, you can break that down into leading indicators for your function that you're responsible for. A learning leader that's responsible for, let's say, the support organization's development, it might look like optimizing the handoff from implementation to success and support, watch that moment in time is more seamless and therefore time to value improves and leads to that longer-legging indicator of churn reduction over time. It requires you to break things down, continuously break down your KPIs into smaller and smaller and smaller bits until you've got something that you have control over and it can be very small. But once you have that, you can not only design interventions that drive towards that, but now going back to the earlier point about data tracking and measurement of the thing, employees are using digital tools from 90% of their work these days. So there's no reason why you can't actually track and access how they're using those tools in their day to see what performance actually looks like. Are they using their knowledge management tool the way that we put it in front of them and the way that they expected that we expected? Are they using their customer success platform and the way that we need them to? Are they using Microsoft Teams if you're a Microsoft shop or are they using Slack correctly? Like how are they using all of these tools in the context of their day-to-day? That data exists. It's there for you to take and learn from. And so this is where, for me, coming from the customer experience side, this is stuff that we do like on the daily, right? We look at product usage, we look at adoption of the tools. And so again, going back to mindset shift, if you do that, if you actually look at adoption of tools and you look at how your employees are using their tools in their day-to-day and you track adoption and performance inside the tools, it gives you a much greater picture of how they are performing in their job in the moment versus you run a performance review six months later and you find out that, oh, maybe they're not aligned to the objectives that I wanted. Like it's immediate. I think that's really what it takes is like, number one, figure out what the smallest KPIs that you have control over, number two, try to get access to data from the tools that your employees are using on a day-to-day basis and see how they're adopting and using those tools and then piece that together in a way that forms an immediate picture of what their day-to-day looks like. And then that's how you continuously optimize and iterate and create these experiments because you have the visibility into the friction that they're experiencing. That's fantastic. And as you said, my beef with data has always been just about the lagging, right? When you take what exists and you fit it to make a story and you can do that with anything. But this is all about taking ownership and being in control, being in the driver's seat as you said. You can do that with data, too. What's cool, too, is that like AIDs days, there are so many interesting tools coming out on the market. Going back to what I said earlier, there's this disconnect, right? You've got your performance data, maybe sitting in your HRIS, you've got some sort of engagement survey tool, you've got your LMS, none of these are correlated, unless you've got a very sophisticated team, you've got the support of your engineering team, you're maybe pulling that together in a data warehouse. There are incredible AI tools and capabilities coming out that stitch together that data in an immediate way, right? If you design your systems in a way that can correlate that data and follow the employee journey through their life cycle and through the touch points that they're experiencing in a day-to-day. Once you have that full visibility, if you design your systems intelligently, it unlocks immediate value and immediate visibility that we've never had before. Again, it's like there's no more excuse, like 2020 is the year that I really believe we stop talking about these concepts and it becomes action. We're going to see a huge amount of transformation this year, I'm really confident in that. Yes, I love it. I appreciate Sam so much, all of the examples, too, you've provided. I think this will be so helpful for our listeners the way you've broken us down, so thank you so much. What are we missing? What haven't we talked about? What do you want to touch on that you haven't yet? Maybe just to go a little bit deeper on the systems that I just touched on, I think this is an area where most organizations have the biggest opportunity is to think about system design and think about the underlying architecture that is required to unlock data visibility, because if you continue thinking in silos and you continue thinking about what do I need in terms of data from each of these systems so that then I can try to figure out with my data science team how to correlate these things and prove value, you're already behind because what you're then doing is shipping a program and trying to prove its worth, you ship something and then you're trying to prove its value and trying to justify why you did it. That's the wrong approach. If you design your systems in a way that allows you, that you have an underlying architecture and an integrated system architecture that gives you the data, the knowledge, all of the stuff that intelligent AI needs in order to act on. If we want to get to a place in future where we have a lot of automation, where we have red thread has spoken about self-healing learning, concept of learning programs that adapt and are completely personalized to the employee, we will never get there unless we have this underlying system stitched together and unless we've thought about what that data architecture looks in the integration between those systems actually looks like. A huge piece of advice for CLOs and learning leaders that are listening to this is work with your technology team, with your IT team, with your CIO to really understand your system architecture and figure out how data moves from one system to the next because if you want to get to a place where you have really intelligent systems design and you can identify skills gaps and you can design content that fixes those capability and skills gaps and you're continuously optimizing and proving it's the system that matters the most. That's the thing that will unlock our ability to get to this place that we all dream of like self-healing, personalized, automated, it's not possible without that. Yeah. It's that underlying layer. I've seen often people dealing with symptoms of if they could just get to the core of what you're saying. And it's so hard having done this work inside an organization, I know how hard it is. It's really hard, I think the reason why it's hard to be honest is because we say we want to see that the table, but we don't understand the system. So go out and educate yourself, understand integration architectures, look at mapping data flows from systems. What are the data points in the KPIs that you actually need, right? There's some, I think up leveling and some education required on behalf of learning leaders because this is skills that have not traditionally been in our skill set. Because it's a little bit foreign to a lot of learning leaders, that's the thing that unblocks to see that the table, that unblocks your ability to speak to your strategy officer, your information and technology officer confidently and really drive the organization where it needs to go. Yeah, you got to the heart of it. I think a lot of our field, they were learning people first and they're learning how to be business people. And I think we're getting there though. I hear more and more the past few years, people, they know what skills they need to attain to get there. And they're going after them. And I think the approach that you've outlined today, again, super actionable, helping us to reimagine work in 2026 and design. Before we wrap up today though, we'd love to hear in your research, reading, work, anything that's brought you to Tiffany and that's gotten you super excited that you'd like to share with listeners. I'm just going to throw it back to be mobile. I am so impressed and it's not just beamable. There are a lot of really interesting tools coming out on the market right now that are giving me hope and a lot of excitement about where the learning field is heading. There's just so many cool stuff happening, so much cool stuff happening around AI that stretches beyond the typical conversation that we've been having over the last couple of years. I'm not that excited anymore about talking about what AI can automate. We know that it can automate repetitive tasks. What I'm most excited about is the impact that's going to have on culture and on performance and on experience of work and on making people feel good about coming to work every day. That's the unlock. That's the thing that actually matters most and it really gives me a lot of hope for the future of the corporate world because I think we've had a little bit of a dip over the last few years and there's a lot of scary stuff happening in the market, a lot of layoffs, a lot of challenge as we go through this transformation and I'm seeing, we're starting to get onto the other side of it and if we can just grasp this opportunity, it's going to be so incredible for the organizations that make it to the other side of this. It's really exciting. What do they call it? The trough of disillusionment, getting out of it, or climbing out. Exactly. You got it. I know listeners are going to want to follow up with you. How might they do so? How might they connect with you, ask any of their own questions and continue the conversation? LinkedIn is probably the best place so I'm on LinkedIn. You can find me, Samantha Murray. My website is aligncx.com. I focus largely on customer experience and customer education side of things, a little less so on specifically L&D, but also do some coaching. Feel free to reach out to me. LinkedIn is probably the best place and I love to chat. I love coffee chats. I love hanging out with people and meeting new people, so don't hesitate to reach out. Wonderful. Sam, thank you so much for taking off so much from me on. What a pleasure. Thank you so much for having me on. Thank you to our sponsor Cloverleaf. Thank you for listening to this podcast by the Association for Talent Development. If you found this show insightful or useful, please be sure to like, subscribe, and share it with a colleague.