KEY TAKEAWAYS

• Trust is the foundation, and it takes time to build. Anonymized analysis of the first ninety days of coaching shows new managers typically begin with personal anxiety, peer conflict, and managing up before they engage Nadia on team leadership. Trust is what makes deeper coaching possible.
• 2026 is the year AI comes to you. Nadia 2.0 introduces a proactive intelligence layer that surfaces coaching moments based on calendar data, HRIS signals, and conversation history, then delivers nudges in the channel where the manager is most likely to act on them.
• Collaboration profiles let coaching land. Nadia 2.0 incorporates working style assessments for every member of a team, so coaching considers both how the manager prefers to communicate and how each direct report best receives feedback. The result is messaging that lands with each individual.
• Performance management becomes continuous. With thousands of data points gathered across a year of coaching conversations, Nadia 2.0 helps managers approach reviews with full context, walks them through reflective questions, and keeps the manager in the driver's seat on judgment calls.
• Organizational intelligence turns coaching into a strategic signal. Aggregated, anonymized insights across thousands of employees show talent leaders which skills are actually being built, where collaboration is breaking down, and how CEO priorities are landing in real time. One 30,000-person high-tech manufacturer used this layer to track strategic priority adoption across the organization.
• The biggest CHRO investment of 2026 is the workforce transition itself. Parker argues the question CHROs will look back on is whether they invested enough in helping managers and frontline leaders move into the human plus AI era, and that private, dedicated leader support is what drives the strongest response.

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FULL TRANSCRIPT

Nadia 2.0: The Future of AI Coaching for Leaders and Managers

Welcome and the Foundation of Trust in AI Coaching

How does AI coaching build trust with leaders and managers?

AI coaching builds trust the same way human coaching does: through consistent, private conversations across a range of personal and professional challenges. Anonymized analysis of the first ninety days of coaching at Valence shows new managers typically begin by working with Nadia on personal anxiety, peer conflict, and managing up before they engage on team leadership. People share more with an AI coach as they learn how helpful it can be, and that accumulated trust becomes the foundation for deeper coaching.

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Parker Mitchell (00:04 - 12:08): Good morning or good afternoon, everyone. I'm Parker. I'm the CEO of Valence, and I'm so excited to welcome you here today. We always take a minute or two to allow any stragglers to trickle in, but this is going to be a really fun presentation of some of the new features and capabilities that our product and engineering team has been so hard at work building.

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We want this to be interactive. We know that this world of AI has so many questions around it, so we have a chat enabled. I think you should be able to find the chat button on your screen quite easily. We'd like to invite you to introduce yourself, your name, your company, where you're joining us from. If you have any questions about features that we're showcasing, about anything that's on your mind, whether it's about Nadia, Valence, or just AI in general, please put it in the chat. We've got a few folks who are dedicated just to answering your questions there.

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I'm going to be joined today by two of our great staff leaders. We have Jennelle, who is leading up a number of initiatives across product, and we have Daniel, who has been working with a huge number of both our customers and folks who are getting to know Valence to learn more about the capabilities of Nadia. I'm going to be welcoming them later on to actually walk us through what this product experience is. But what I wanted to do is just step back for a moment.

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We're going to be talking about the future, what we think is the future of AI coaching. And before I do so, I want to take a moment and step back and talk about our experiences in how we got here. From looking at some of the names that are coming in on chat, there are folks that I'm familiar with, folks that we've worked with for a number of years, and there are some new names, and I want to make sure that people get that grounding.

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At Valence, we were pretty well the first company to invest heavily in this AI world. We deployed Nadia almost three years ago in the first pilot beta form, and we've been evolving her ever since. She is now the most widely deployed AI coach across the Fortune 500 and is being integrated not just as a coach to offer supplemental support for individuals, for leaders, for managers, but also being much more deeply integrated into talent programs and beginning to help forward-thinking talent leaders think about how they might reinvent the performance management function, the talent function, and it's really exciting to showcase some of the new capabilities for that.

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These deployments aren't just small pilots. We have been working directly with CHROs across North America, across Europe, now increasingly in Asia, to try to solve some of the most pressing problems that they're facing as they help shift their workforce from a just-human workforce to a human plus AI company way of doing work, and as they think about how AI is going to allow them to reinvent parts of the talent function. So we've spent a lot of time thinking about how we can help folks like you on the call.

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But one of the things that we're most inspired by is learning about how we help the individual managers. We've had millions of conversations now, some spanning almost two and a half years of a journey. We've learned a few really interesting things about what AI coaching needs to be for leaders and managers, and that's the foundation that's going to help us rethink how we can reinvent basically the talent processes.

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At its heart, when we talk to managers and when we do anonymized reviews of conversations, what's clear is managing is actually a high stakes, sometimes high risk, and emotional journey. If folks on the call think back to your first moment, your first months as a manager, as a leader, I would imagine there was a sense of overwhelm, a sense of, wow, this is not exactly what I was expecting it to be, a sense of new sets of skills that you had to build. When you think about having a difficult performance conversation, or onboarding a new team member, or repairing a damaged relationship, or navigating a conflict between two team members, these are high stakes moments, and often managers report that they don't feel they have anyone to turn to.

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At its heart, an AI coach has to have that trusted relationship to be the place where a manager will go to ask for that kind of help. So what we found, I want to share just a quick snapshot, because it takes time to build that trusted relationship. We've done a series of anonymized assessments of the first ninety days of coaching conversations. We do an interview with the person as well to learn more about how they've been using it. If they're willing to give permission about the anonymized journey that they've been on, we're able to share it. So this was a fascinating insight as we peel back what is on the manager's mind. We have hundreds of thousands of these as we've watched these journeys evolve.

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What has struck us and our team is that some of these elements, if you think of this green line at the bottom, leading the team, that's often what an HR leader might say. Hey, that's what's important. I want to make sure all my frontline managers can lead their team well. But what you see from this, and this is typical of many of the relationships, is that it takes time for leaders to build that trust. The first set of conversations that Nadia had with this leader was around managing anxiety. In this case, finding their voice, rehearsing their words for a session that was coming up. Then they had to navigate peer conflict and trust because there was a sense of betrayal that they were experiencing, and they turned to Nadia to understand how to approach it, and the tactics of how to draft a message, how to address the message, how to explore the follow-up.

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They also had a series of issues around managing up. I think many people would acknowledge that you have relationships to your team, but also to your managers, to your peers, and there's some delicacy often in managing those.

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All this to say, it takes time to build that trust, and that's at the heart of a coaching relationship. What we've discovered is people trust Nadia. They trust an AI coach with more and more information as they learn how helpful it could be. With this foundation of trust at the center of it, what we're going to showcase is how Nadia can add new layers of capability.

From Reactive to Proactive: AI Coaching in 2026

How does proactive AI coaching work in practice?

Proactive AI coaching means the coach reaches out before the user asks. Nadia 2.0 analyzes signals across the user's calendar, HRIS data, communication channels, and prior conversations, identifies moments where coaching would be most valuable, and delivers nudges in the right channel at the right time. For one new manager in the demo, Nadia surfaces a coaching moment in Microsoft Teams the moment a promotion is logged in the HRIS, before the manager has thought to ask for help.

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Parker Mitchell (continued): What we're going to showcase is how Nadia can gather more context through a deep set of integrations, which we've been launching over the course of Q1, and how Nadia can plan over that information in a way a human coach never could, because she has access to a lot of information. If you choose to give it both as a company and as an individual, she can plan over that, and she can become proactive.

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We've talked about 2025 being the year that you had to go to AI. You had to go to a chatbot. You had to ask a question. You had to go through the mental process of saying, I'm having an issue, what should I do about it? Maybe I'll go to some solution. I'll go type something in or talk to it using voice. There's a series of steps that make it harder to get over those hurdles.

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But 2026, we believe, is going to be the year that AI comes to you, that AI starts to get to know you, starts to get to know your context, and is proactive in trying to get ahead of the issues that you might face. We're going to walk through a year in the life of a manager. What you're going to see is, underlying this, how Nadia's context engine is building a profile of you, building a profile of your team, building a profile of the goals that you have, building a profile of the team members who are on it, and then also getting to know all your colleagues across the organization who you might be interacting with, as well as your organizational goals and your talent processes. She's able to weave those together in a really powerful way.

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I'm going to switch now and walk through what this looks like. Many of the people on this call have either a direct or a dotted-line responsibility for how do we bring to life the talent processes that for our company reflect what we think our best practices are, that we want every leader, every manager, to do. How do we bring those to life to drive performance? For decades, it's been a series of big moments because that's what we've known how to do. That's what the technology allowed us to do, to run a process, to set goals, to ensure that people do midyear reviews, that engagement surveys are acted upon. Many of us would say this doesn't land particularly well with our leaders and managers. It often might be a little perfunctory. It's often done at the last minute. We don't know what the goal quality is.

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These are what we have at our fingertips right now to drive performance. But if we were to step back and say, what actually drives performance? The answer is the thousands of small moments that are happening every day across the organization. If you can layer those top-level goals into these thousands of small moments, that is a powerful new capability that you'll have to drive way better performance.

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We're going to walk you through a year in the life of an individual. Her name is Maya. She's a first-time manager. She has eight direct reports, and you'll see how she navigates that first year as pressure compounds on her. This is a hypothetical, fictional example, but you'll be able to see how Nadia 2.0 comes to life in these moments. The power of AI is being able to layer those top-level goals you have with these day-to-day moments and to actually drive how your individuals lead, how they incorporate those big talent moments, and how they react to the organizational dynamics, the reorg, the layoffs, the AI transformation initiative, the new priority of the CEO, and how Nadia is able to weave that all together for a seamless, supportive experience for any leader, any manager, anywhere in the world on any of the teams that you're responsible for.

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With that, I'm excited to turn it over to Daniel to give us a little more context.

A Year in the Life of a New Manager

How does AI coaching help new managers?

AI coaching helps new managers navigate the high-stakes transition into people leadership, starting with the moments most managers report feeling unprepared for: difficult performance conversations, peer conflict, managing up, and onboarding team members. Nadia 2.0 sets development goals at promotion, tracks progress across the year, and surfaces specific coaching moments based on what's actually happening on the manager's team rather than working from a generic checklist.

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Daniel Owens (12:08 - 16:50): Thanks, Parker, and thanks everyone for joining. It's good to see so many familiar faces and so many new names here as well. My name is Daniel. I'm a director here at Valence. Over the past couple of years, I've had the opportunity to talk to quite a few of our users and to work with quite a few of the companies that we've been partnering with, some of which I think are on this call.

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It's been an inspiring journey over the past couple of years to see not only how Nadia has been helping users and driving performance, but also, in thinking about this Nadia 2.0 release, how we can take this a step further and act on a lot of the feedback that we've gathered from both users and a lot of the people on this call. This Nadia 2.0 release is a big step forward that I'm excited to show you how it shows up in practice with the story of Maya. I'm going to be joined by Jennelle, who's our principal product manager.

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Jennelle, I'll ask you to come join me here, and we're going to walk you through four moments with Maya of how she's been working with Nadia throughout the year. So, Jennelle, if you want to pull up our first page here, let's start with Maya logging in to Nadia. This is going to look familiar for a lot of the people on this call who have their own Nadia accounts. Maya, a recently promoted manager like Parker mentioned, has been working with Nadia as an IC and has now moved into this role as a new manager.

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Today, what we're actually going to walk through is four distinct new moments or features that are part of this Nadia 2.0 release. They show how Nadia is using a lot of this new context and new information to drive behavior change with Maya and with her team. As Parker talked about earlier, moving into a manager role is quite challenging. There's a lot of information to process, a lot of new skills to build, and so we're going to show you how Nadia actually helps Maya throughout this tricky transition.

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The first thing we're going to talk about is this new feature we're calling journeys, which Jennelle's going to highlight right here. A lot of the feedback that we hear from the companies we partner with is that people set these development goals and then forget about them throughout the year. We're going to watch Maya as she gets promoted, work with Nadia to actually set relevant development goals, and then see how Nadia works with Maya throughout the year to be an accountability partner and to drive completion of these goals over time.

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The second thing we're going to walk through is collaboration profiles. A coach is only as powerful as their understanding of the people they're working with. We're going to watch how Maya is wrestling with how to give feedback to some of the people on her team, and see how Nadia uses this new collaborative intelligence to make sure that the messaging lands with the people on Maya's team.

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The third thing we're going to walk through is called the convergence, which is really our coaching moments. What we found is that a lot of people don't know exactly what they can engage with the coach on, or what could be a coachable moment. With this feature, we're going to walk through how Nadia is connecting the dots and becoming a proactive coach, surfacing coachable moments that she can work with Maya on.

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The last thing we're going to cover is performance management, which is something that Nadia has been helping on for a couple of years at this point. What we're going to highlight today is how Nadia uses a lot of this 2.0 functionality to transform this performance management moment from a one-time event into something that's continuously happening throughout the year. How she's using a lot of this new functionality that we're launching with Nadia 2.0 to make Maya more effective and to drive a more productive and efficient performance conversation at the end of the year.

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So, Jennelle, if we go back to our year in the life of Maya, we're going to start with moment one, which is Maya first kicking off her year as a new manager and working with Nadia on thinking through what are the development areas and what are those goals that she wants to set as she's stepping into this new role as a manager. I'll pass it to you to introduce yourself and walk us through this first moment.

Moment 1: Setting Development Goals with Journeys

Jennelle Nystrom (16:50 - 20:19): Thanks, Daniel. My name is Jennelle. I'm the product manager on our AI team. My job is really fun. I get to analyze all of our data and look through all of the conversations, all the information flowing into all these systems, and think about how we can leverage those to create these really interesting coaching moments.

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As we shift from Nadia 1.0 to Nadia 2.0, it's been really fun to see how Nadia can anticipate and approach managers, because as Daniel said, a manager might not always know exactly what they should get coached on. As we move into this moment, I'll show you exactly what that looks like in practice.

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By the time Maya gets this Microsoft Teams notification from Nadia, Nadia has been thinking through and analyzing all of these signals that she knows about Maya, and she's noticed that Maya has just gotten a promotion. She catches this in the HRIS integration. Because Maya and Nadia have been working together already for a few months in Maya's capacity as an IC, Nadia knows this is a huge moment for Maya. They've been working towards this promotion for months.

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What we see here is Nadia reaching out through the Microsoft Teams application, not only to congratulate Maya on what is a milestone in her career, but also to flag this as a potential coaching moment. All of the goals that got Maya to this point and to be at this manager level are maybe not the goals that she needs now to help transition.

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Nadia wants to flag this to Maya, and she's using our new proactive intelligence layer. What proactive intelligence layer does is it identifies these coaching moments, and it also thinks through where is the best place to put these nudges and these proactive coaching moments so that they get in front of Maya and she actually takes action on them.

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We know that in the busy life of a manager, the wrong message in the wrong channel or at the wrong time isn't going to get read or it's going to get missed. Behind the scenes here, what Nadia is doing is analyzing all of the communication channels that Maya has access to, and she has decided that because this is a super high priority moment that Maya needs to get right, she's going to follow up directly in Microsoft Teams and make sure Maya sees this and takes action on it.

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She's inviting Maya here to take that step back and reflect on her goals, and then inviting her to come and take a look at the journeys page. As Daniel mentioned, this is the page where you can track all of the goals Maya and Nadia can agree on what they're working on together.

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Maya already has some goals here from her time as an IC. She's been working on direct feedback. She's been working on executive presence. It's going well for her because she just got the promotion. Now Nadia has come in and suggested a few more goals that would help her make this transition into management and make sure that the transition goes well on her team.

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One other piece of context here is that Maya, because she was promoted within her team, might have slightly different dynamics to navigate than a manager joining from a completely separate team or from outside the organization. Nadia is flagging those goals here, and Maya can drag the one she wants to focus on to the right. What this does is it powers that proactive intelligence layer even further. Now when Nadia is analyzing all of Maya's data and identifying those coaching moments, she's prioritizing them against Maya's goals and using those as a filter to make sure she's proactive to Maya on the most important moments relative to her goals.

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Daniel Owens (20:19 - 22:50): The interesting thing here is that Nadia is showing up before Maya even asks for it. The shift is from a reactive layer to that proactive coach that Jennelle's describing. It's not a generic new manager checklist that's applicable across a broad set of people. It's hyper-specific to Maya, and even picking up on those potentially political or more nuanced relationship dynamics that Maya is going to have to navigate in this new role.

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You'll see in a little bit how Nadia is going to thread these different goals throughout the year in different conversations. That's really the power of this new journeys feature: not only is Nadia flagging what could be a good development goal, but she'll also proactively work with Maya throughout the year to actually build those skills and achieve those goals.

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If we scroll down a little bit, Jennelle, on the left-hand side, we can start to see how Nadia is building up more and more knowledge of Maya throughout these different conversations. We're not going to go into every single one. The second moment we're going to focus on is how Nadia is working with Maya on an interaction in a potentially difficult situation between Maya and one of her direct reports.

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Before, Jennelle, you walk through that, one of the things I want to highlight is that privacy is a huge pillar of how we designed Nadia from day one. Privacy is what makes a coach a powerful resource that you can confide in, that you can be authentic in. That's something that's not going to change with Nadia.

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A lot of the feedback that we heard from both users and the companies that we've been partnering with is that Nadia could be more powerful if she also understood both sides of the coin. So not just how me as an individual processes information, but also how my team processes information or how my team prefers to communicate. That's the bedrock of this collaborative intelligence layer that we're going to walk through in this next moment. It's a powerful source of information that Nadia can now incorporate as she's giving coaching on these different relationship dynamics.

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What you're about to see now is a coach that's earned the right to push back on Maya and potentially redirect a way that Maya might be thinking about framing potentially sensitive communication. I'll pass it to you to walk through the second moment here.

Moment 2: Personalized Feedback with Collaboration Profiles

Jennelle Nystrom (22:50 - 25:57): Daniel, the key of this moment is that understanding of both sides of the coin. Not just how Maya prefers to give feedback, but how it's best received for each member of her team. What's powering that is we have collaboration profiles. In this example, it's based off of Valence's working style assessment called Perspective. We also allow any organization to bring their own working style assessments, like Clifton StrengthsFinder, if there's another one you prefer.

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It captures these working style assessments for each member of the team. What that means is that in these key coaching moments and communication moments that happen many times throughout the year or even many times a day, Nadia has that context to help make sure that any message Maya sends to her team lands effectively, both so that she conveys what she's trying to say and so it's interpreted in a way that each team member is most likely to hear it.

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Let me show you what this looks like in practice. In this moment, Maya is planning to give Priya feedback. Based on the conversation she's had with Nadia so far and based on the goals that she's working on with Nadia, she knows direct feedback isn't necessarily a skill of hers. It's something she's working on. It's not a natural area of strength based on her own working style. So before sending the message, she comes to Nadia and says, hey, can you review this? Just give me a check and make sure that this looks right.

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Nadia is pulling from Maya's collaboration profile, Priya's collaboration profile, and that goal that she knows Maya has in the back of her head to get better at this. Essentially, what she's saying here is, let's take a step back. She's pushing back and saying, this message is not going to land the way you think it is. To tie in this coaching moment, she's looking across all of those different layers and coaching Maya not just on this specific message and why it might not land, but tying it into the coaching journey that they've been on working through direct feedback.

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She's saying, I know this is something that you're working on. Here is an important moment for us to step back. She's also incorporating Priya's collaboration profile. One of the interesting dynamics here is that while Maya might have more trouble being direct, Priya actually thrives on direct feedback. Nadia is incorporating that here and reminding Maya that this message is not going to land, both because Maya is not being as direct as she could be, and also because Priya specifically thrives on direct feedback. If we phrase it this way, she might not hear it. So Nadia is stepping back and giving Maya this advice before generating an email for her that's going to land more impactfully in this moment.

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Each of these moments will tie together and help Maya get better at not only nailing direct feedback and improving on her own goals and improving that communication, but also showing how each of these little moments throughout the year play out in practice.

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Daniel Owens (25:57 - 28:22): There are two points within that last interaction that I think are quite powerful. The first is that Nadia helped Maya save a little time in drafting that email, but that's table stakes. The huge value of that interaction between Nadia and Maya about Priya was that Nadia is not just drafting the message for Maya, but really making sure that that message is going to land with Maya's goal and also resonate well with Priya. It's improving the quality and the delivery of that message.

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The second thing within that past interaction was that what Nadia is really doing here is enabling a more impactful and authentic human interaction between Priya and Maya. Not coaching Maya to communicate differently in an abstract way, but a very specific and tactical recommendation on how to communicate better with Priya in this specific moment to achieve Maya's goal. That's built into how we're thinking about Nadia moving forward: Nadia is designed to help enable us as humans to collaborate better and to be the best versions of ourselves. The goal is a better holistic relationship between people like Priya and Maya, beyond just generating a faster email.

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If we scroll down, let's go to the third moment, which is what we're calling the convergence. This is one of my personal favorites of the new aspects of the Nadia 2.0 release. In the past couple of months, we've been testing and using this feature internally, and it is quite powerful and insightful, the kind of insights that Nadia is able to generate proactively in this feature.

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By August, you can see on the left-hand side that Nadia's knowledge is continuously growing about Maya, and she has a lot of data points to pull from for this. Parker talked earlier about this aspect of trust being a powerful thing that drives the impact of the coach. We'll see in this moment how, as Nadia and Maya have been building trust, Nadia can now more proactively flag potential blind spots or potential coachable moments that she can be working with Maya on.

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Jennelle, I'll pass it to you for this third moment.

Moment 3: Surfacing Coachable Moments with the Convergence

Jennelle Nystrom (28:22 - 30:50): This one, Daniel said it was his favorite. It's also been the most exciting to build. Behind the scenes of this feature, the AI team and I have been pouring over millions of conversations and millions of moments and doing deep analysis on what are those moments that drive better skill building over time, and where are those moments that can create more trouble down the line if they're missed. The heart of this insight is that, given everything that's going on on a manager's plate, they might miss some key opportunities, and Nadia is going to help them get ahead of it.

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We've been dogfooding this feature internally. That's a term we use for when we're testing things ourselves. I know this feature is working when someone comes to me and they say, oh my god, Nadia caught something on my calendar that I was sort of aware of. It was in the back of my head. But given everything else that's going on, I might have missed it until Nadia came to me with this insight.

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We see that here in this particular moment for Maya. There are many things going on on her team. She's working through a parental leave dynamic between two members of her team. The CEO just introduced a new AI mandate. On top of it all, there's just been an org restructure on an adjacent team, and someone from that team is now joining her team.

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What Nadia is calling out here is that this is a moment where a manager, especially an earlier manager, might go back to doing an onboarding checklist or might not flag this as a super important moment. So Nadia is calling out, I know there's a lot of things going on. I also want to make sure that you get this moment for Kai joining your team really, really right. The reason that's important is because this isn't a normal new hire. This is a person who is joining from an adjacent team. While they might already have contacts in the company, they also just went through a difficult moment through a restructure.

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Nadia is displaying this to Maya, asking her to step back and take action. Maya's like, with everything going on, I haven't exactly had a chance to think about it. I was going to do the default path of pairing her with someone on the team so that the onboarding is through this buddy system. Now Nadia is challenging her to think more about the relationship. This doesn't need to take a ton of time. It's just giving Maya the space to step back and reflect and make sure Kai's onboarding goes well.

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Daniel Owens (30:50 - 33:12): Earlier we talked about some of the feedback we heard from users and from some of the HR teams we partner with: sometimes people don't know what they should be coached on, or what is a coachable moment. That's a powerful aspect of this feature. Nadia surfaces those moments and generates those insights proactively for you to catch things that you might not even know are coachable moments for yourself.

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Now let's move down a little. We're now nearing the end of the year with Maya and Nadia, and it's now performance review season. A lot of the people on this call understand that it is very hard for managers to do performance reviews effectively. A lot of times, if reviews are due on December 15, for example, most people are going to wait until December 14 to start actually writing those memos and prepping for those conversations. That means we have recency bias. We struggle to clearly articulate development goals or pull together threads from throughout the year.

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What we'll see in this next moment is that because Maya and Nadia have been working together over the past year, Nadia has a lot of context. We're up to 4,500 data points that Nadia has on how Maya is working, on how Maya is interacting with her team, that she can use to help Maya be more effective in this year-of-review process.

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A lot of the people on this call have been partnering with us over the past couple of years to integrate Nadia within their performance review cycles. This is a powerful thing that AI coaching can help with, to make people more efficient and effective in this process. What we want to show today is how, with these additional levels of data and information that Nadia has access to, she can help Maya be more objective, more prepared, more holistic in how she's thinking about performance with her team and with Priya in particular. You'll notice how Nadia is going to surface to Maya things that she's been working on with Priya throughout the year in this actual conversation.

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Jennelle, I'll pass it back to you.

Moment 4: Continuous Performance Management

How can AI coaching support performance reviews?

AI coaching turns performance reviews into a continuous process by drawing on data points gathered across a manager's full year of coaching conversations. Nadia 2.0 surfaces patterns about each direct report, walks the manager through reflective questions before any draft is generated, and explicitly flags what it does not know rather than filling gaps. The manager retains judgment over the final review, while AI removes recency bias and improves objectivity.

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Jennelle Nystrom (33:12 - 35:52): Daniel said we have the 4,500 data points at this point, and Nadia knows a lot about Maya and everyone on her team. The key, going into this performance review, is she's using that context to put Maya in the driver's seat and keep her at the center of the conversations, rather than to fill in the blanks and try to automate the process and make it faster.

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The context is a frame that Nadia is using to help understand the dynamics so that she can help Maya reflect. Let me show you what that looks like for a specific relationship here. We've talked about Priya before. In moment two, we saw Maya navigate a tricky conversation with Priya where she felt that, as she ramped up into her manager role, Priya's performance started to slip.

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Nadia knows that part of that dynamic was that Priya herself was a candidate for the promotion that Maya ultimately got. As that transition was taking place and Priya was trying to find her place on the team, her performance was slipping, and Maya had to address it. That moment happened earlier on in the year. Here we are in December. Nadia has been keeping track of all of Maya's notes on her relationship with Priya so that she has this full context. She knows what goals Priya has set for herself. She knows how the dynamic has played out for Maya and Priya, and she's here to help Maya step back and reflect on it.

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One important thing with all of the context Nadia has is she's also aware of what she doesn't know. We don't want her to lead and start filling in the review or start reflecting on the relationship without all of the context. As an AI coach, it's impossible for Nadia to have every single piece of context. She knows what Maya has come to her throughout the year with. She also knows that there's a lot of nuance in there that she might not know. So before we get into writing the performance review, she's reflecting on all the things that she doesn't know. She's reflecting on all of the things that need to land to make sure this performance review goes well, and she's walking Maya through a back-and-forth conversation to help Maya reflect. It's ultimately up to Maya to make the judgment call of what goes in the review and the feedback that she wants to give during this cycle.

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I skipped through a lot of the back-and-forth there. As Nadia and Maya go back and forth, they generate this review together. From here, Maya can submit it to Workday and move on to the next person on her team.

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Daniel Owens (35:52 - 38:38): The point you made about Nadia's role being not just to generate a draft, but really to hold up a mirror and push Maya to reflect and to think critically, is a really important part of how we think about Nadia enhancing the performance process and being a value-add. Also how Nadia can be helping Maya think about this performance review cycle, not as a one-time moment, but as something that's a continuous, always-on performance process happening throughout the year, in each conversation that Nadia and Maya have together.

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That principle is quite important to us. We could have made it very easy for Nadia to just quickly generate a review or a draft for somebody to submit. But we know the value of these moments is quite high if they're done right. We designed Nadia in a way that pushes users to reflect, and as Jennelle said, has Nadia point out the gaps of things that she doesn't know, so Nadia doesn't replace judgment for a user. Nadia gives users the information and helps them reflect in a way that's going to lead to a higher-quality conversation and a more objective review for their team and for individuals as well.

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If we zoom out, we went through four moments with Nadia and Maya throughout the year. These are just a couple of examples of how Maya and Nadia could have been working throughout their entire year. A couple of my takeaways: Maya has now established Nadia as a thought partner that she can work with throughout the year, in each of those moments. Those day-to-day tough moments, like sending an email to Priya, all the way to those really big moments, like this end-of-year review, where you're holistically pulling together a lot of these different data points.

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Because Nadia and Maya have been working together quite frequently, and Nadia has learned a lot about Maya and built up a lot of trust, she's able to be a reactive coach in helping Maya as Maya requests help, and a proactive coach in pushing Maya to potentially change her behavior or flag a gap that Maya hasn't seen herself.

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If we scroll down, Jennelle, just zooming out and looking at the different components of what makes up Nadia 2.0. You saw a lot of these come to life as we walked through the year in the life of Maya. Maybe I'll ask you to do an overview of some of these different components that are now powering Nadia in this Nadia 2.0 phase.

The Components Behind Nadia 2.0

What is Nadia 2.0?

Nadia 2.0 is the next generation of Valence's AI coach for leaders and managers, launching in early 2026. It adds a proactive intelligence layer, collaboration profiles built on working style assessments, deep integrations with HRIS, calendar, and learning management systems, and an organizational intelligence layer that aggregates anonymized signals to help talent leaders see how strategic priorities are landing across the workforce. All capabilities sit on top of the personalization and trusted coaching relationship from Nadia 1.0.

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Jennelle Nystrom (38:38 - 40:28): Thanks, Daniel. We covered a lot of these already, but I'll highlight them one more time. One of the things I want to emphasize here is that Nadia 2.0 is landing early 2026 for a reason. We're drawing in so much context to help Nadia understand each of the environments that all of the people she works with are working in, and that's only a function of model capacity today. On the AI side, we've seen models get so much better in the time we've been working on building this AI coach. Now we're at a point where Nadia can take all of this information, synthesize it, identify those key coaching moments, and build a great experience for each manager around them.

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Some of those context sources: we have org intelligence. We're integrating with HRIS platforms, with your calendar, with learning management systems, with any org customizations that you might bring around your values and what's most important for the organization. We have many tens of thousands of documents right now from talent moments, both documents that managers have shared with Nadia to help them work through performance management, and documents that they've created with Nadia that they then send on as the feedback to their HRIS platforms.

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This new layer is collaboration intelligence: using working style assessments, understanding how each person on the team best works, best receives feedback, so that everyone can work better together.

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At the top is everything that we've had from Nadia 1.0: all of the coaching conversations, all of the personalization. Nadia gets to know each person that she's working with. As she combines that with all of this great context that she has from different parts of the organization, that's collaboration intelligence.

Organizational Intelligence at Scale

What is organizational intelligence in AI coaching?

Organizational intelligence is the aggregated, anonymized layer of insight produced when an AI coach is deployed at scale. Valence uses Nadia conversation data across thousands of employees to surface real-time signals on where people are building skills, where collaboration is breaking down, where attrition or burnout risks may be emerging, and how strategic priorities set by the CEO are actually being implemented. Privacy is preserved by aggregating insights rather than exposing individual conversations.

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Daniel Owens (40:28 - 45:31): We walked through what this looks like for an individual, but the power of this is when this is happening at scale. If we think about Maya and Nadia working together to drive collaboration and effectiveness on her team, and we think about that happening with maybe 5,000 managers across an organization, the value compounds exponentially.

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In addition to the personal coaching benefits people can get from working with Nadia directly, we also unlock what we're calling organizational intelligence. Stepping up and aggregating this data shows how people are actually showing up across the organization, where there could be gaps, where there could be risks worth looking into. It unlocks a rich data source for how people are actually showing up and interacting at work, to help us make better decisions.

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Privacy is still a huge component of Nadia, so all of this is aggregated insights to preserve user confidentiality. It starts to give us directional themes of where people are struggling and where we might want to focus.

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A couple of example things that we've been working on with some of our partners in the past couple of months. First is thinking about skills. Imagine if we could see what skills people are really building across an organization, not via course completions or what people are signing up for, but really what people are working on, what they're talking to Nadia about, and what they're practicing. And where might there be gaps, where there could be skills that people should be building but maybe aren't actively doing that.

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If we scroll down, if we think about how Nadia can show us how people are feeling across the organization, where could there be potential attrition risks or potential burnout signals, not via a once-a-year survey or a quarterly pulse survey, but really as a real-time signal. What are those themes that people are bringing up in coaching conversations, and how can we use this data to make better decisions as an organization?

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If we scroll down a little more on the collaboration side: how are people actually working together well? What's blocking people from working together well? What's getting in the way of cross-functional collaboration? What kind of conversations might people be avoiding or might people not want to be having with each other?

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These are the types of insights we've been starting to pull up at an aggregated level to work with our partners and think about how we can use this data to make better decisions across the business. One example of how we've done this with one of our clients over the past couple of months: we work with a large high-tech manufacturing company of around 30,000 employees that has been using Nadia over the past couple of years in quite a few different use cases.

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Their CEO had a clear set of strategic priorities for the year that was really focused on how this company was navigating change, how cross-functional teams should be working together throughout a period of transformation. The question we were trying to answer with this organizational intelligence layer was, not just, are people aware of these priorities, but really, how are people actually showing up and implementing these priorities, what's working, what might be getting in the way, and what could potentially stop this set of priorities from coming to fruition.

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What we did was map these topics to Nadia's coaching conversations with this company's users, directly with the priorities set by the CEO, and then start to look through that data to see what people are talking about regarding this change, what's getting in the way of people actually implementing some of these changes, what people are avoiding, and what people are struggling with, as a way to get a real-time signal on how people are actually implementing this new strategy that the company is setting out.

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That's what we're quite excited by, and where we see a lot of value: using this data to make better decisions at an organizational level, both on the talent side and on the business side as well.

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With that, I'm going to invite Parker to come back and join us on stage. We walked through a year in the life of Maya, we walked through some of the different components that are now powering Nadia 2.0, and what that can unlock for both the individual and the organization. I'll pass it back to you, Parker, for some closing thoughts on this next step for Nadia.

Helping Workforces Navigate the Human Plus AI Era

What should CHROs invest in to help their workforce transition to AI?

CHROs are best positioned to lead the workforce transition to a human plus AI era by giving leaders private, dedicated AI support, rather than adding more generic tools. Valence customers report the strongest response from leaders when AI coaching is offered as a confidential resource for their hardest leadership moments. The investment most likely to matter five years from now is the one that helps managers and frontline leaders move into this new era with the support they need.

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Parker Mitchell (45:31 - 51:34): Thanks, Jennelle, and thanks, Daniel, for that great showcase of some of the new capabilities. I have actually been busy in the chat answering a number of questions. I almost missed the invite to come back on stage. There have been a lot of questions in there, and I want to wrap. We want to make sure we give you back a few minutes on your hour.

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These bigger questions about what the AI ecosystem looks like, and especially how CEOs and ELTs are thinking about the investments that they want to make in putting AI in the hands of employees. I want to start with a sense of empathy. I want to show a graph that we recently saw from one of the companies that does the overall assessments of the landscape. This is the HR technology and experience bullseye. This is the world that you're being asked to navigate. All the different sets of requirements on the HR world, all the different AI enablement layers that are in there.

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Honestly, I stare at that and I don't know what to make of it. I'm certain that almost everyone on the call feels overwhelmed with AI information coming this way and that way.

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What we've seen is a couple of things. Number one, there's a range of reactions to AI from employees, but there is definitely a thread of trepidation or a little bit of anxiety, which is around: is AI going to automate parts of my job away? Managing that is probably the single most important leadership challenge for a CEO, certainly for a CHRO, in the coming year. If you look back five years from now, the question CHROs would look back on, or heads of talent would look back on and say, what do I wish I'd gotten right in 2026? I think it's: I wish I'd invested more in helping my workforce transition to this human plus AI era.

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There's a suite of tools that are tactical tools that you can go to. What we've heard from people who are strong deployers of Nadia, to their entire manager population, sometimes to their entire organizational population, is they're saying that there is an incredible response from leaders when a solution is offered that is uniquely directed towards them.

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We talked about trust at the beginning. Leaders are going to feel struggle in this transition. Sometimes they're going to feel more affinity with the goals of the company. Sometimes they're going to feel empathy with people on their team, team members who are struggling. Being able to give them support that is unique, that is private, that is dedicated to helping them, support that is not information they had shared to their company, again, all of this is utterly private. That coaching relationship is based on trust. That is a powerful part of that transition.

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There was a question here of how do we navigate this, how do we help our ELT understand that. We're more than happy to showcase a little more about how others have built that.

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There's a series of other answers that are happening in the chat. What we want this to be is a conversation. We know that there's no silver bullet, no one answer, and we're dedicated to helping leaders like yourselves bring the right kind of powerful AI into your companies, help you make sense of the conflicting statements that people are making about what is possible or not possible, about what direction to take, and most importantly, connect you. The biggest thing we think is connecting people who are interested in exploring what different types of AI might look like in the hands of their leaders with many of our customers who have already gone through this journey, who have wrestled with these questions, who have put in practice the ideas that we've just been talking about. They'll be able to share with you their experiences and why they find it such a powerful solution. For anyone who's interested, we're more than happy. Just reach out to me or any team member. We're happy to walk you through this in a personalized way.

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Our wonderful director of marketing, Kira, who is leading up the growth initiative, is going to be sharing with you new webinars that we have. We have a series of frontline webinars coming up, webinars for frontline staff, with Nadia and frontline staff. We have our research stream, led by the director of Project Aristotle and Project Oxygen from Google, who's an advisory board member to us, talking about the impact, the data that we're starting to see in our early customers. We had a great webinar on that just last week. We've also got an AI stream where we're talking to AI leaders. We've talked to Geoffrey Hinton, Ethan Mollick, and others. This is to bring together and create a lively conversation, because we know that we're all facing the same set of circumstances.

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Thank you for joining us today. Thank you for your time. I know how valuable it is. We wish you the best in this journey as you work through the right answer and the right path forward, bringing the right kind of AI into your companies and putting powerful AI into the hands of your leaders and the hands of your managers. Thank you for joining us, and we look forward to future conversations.