The Defining Workforce Question of 2026

Parker Mitchell

Well, it is such an honor to welcome everyone here today to look out over the sea of faces. I have been torn this morning between wanting to welcome so many people who I know and I've had a chance to work with and partner with, and I wanted to spend the time doing that.

And we'll see in a moment how our AI coach Nadia has foreseen my behavior this morning, the morning of summit. I've spent the last few minutes doing the final edits to slides to make sure that this presentation is going to go well. But I am delighted to welcome everyone here today. And everyone here is busy. Everyone here has a million things that you could be doing today. So why did you take the time to spend a day wrestling with this question?

And we think that the question that is most important — the question that five years from now we will look back and say we wish we spent even more time exploring and trying to answer — is how well did we help our workforce transition to this new human-plus-AI era? And we think that's probably the defining question of 2026. And 2026 is the year in which the trajectories will start to get hardened.

From Experimentation to Transformation

Parker Mitchell

When we first held this summit — this is our third annual AI in the Workforce Summit — how many of you were at the very first one? Maybe a couple of hands. I see Austin, Lucy, and a few other hands. It was a very different AI world. We were still in early days. We were still experimenting. People would tell their friends that they had ChatGPT write a sonnet for their partner's birthday, and that was the big exciting thing. And fast forward two years, I think we all know that AI is going to change work. It is going to change jobs. It is going to change the companies that succeed and fail. And we are all wrestling with how do we bring our workforces along in this transition.

One of the things that we're excited about with Summit is we bring together two different sets of worlds — two different sets of folks experiencing AI in very different ways. We get a chance to hear from people who are at the frontier of how AI is scaling and growing in its capabilities, as well as people who are on the front line of how AI is being adopted, how it is being rolled out, and how it is changing work.

Our very first summit we had a chance to hear from Geoffrey Hinton on the frontier side of things — sharing his stories about what it's like to be on the exponential curve. And the thing that struck me most about my conversations with him was how he said, despite being the godfather of AI, the Nobel laureate, despite being as close to this technology as anyone, he underestimated how quickly the capabilities would grow. And so this is the exponential world we're in.

Why the Gap Between Frontier and Frontline Exists

Parker Mitchell

For many of the people in the room, we're wrestling with this: the experience that we have with AI in the workforce doesn't match what we're hearing about the quality of the models and the capabilities and the changes that we see possible. And I think bringing those two communities together to talk through, to exchange ideas, to learn from one another — that's one of the main purposes of summit.

One of the reasons why we think there's such a gap is because of how hard it is to understand and wrestle with this idea of AI. It is not like anything we've experienced before. It's a form of intelligence and it's hard to figure out how to work with intelligence.

My best friend described it using an analogy from Rain Man. He said, "I've been using these LLMs for a year and a half now. And I never know — am I going to get '246 toothpicks,' or am I going to get 'I can't cross the street'?" For those of you who know Rain Man, those are two iconic scenes. And that's how we feel about AI. You never know if you're going to get this miraculous wow moment, or you ask for four items and it comes back and says there are three, and you go back and forth on that.

The Shift to AI Coming to Your Workers

Key Takeaway: How the Enterprise AI Shift Changes in 2026

2025 was the year employees had to go to AI — to try to understand what it was. In 2026, the shift reverses: AI comes to workers where they are, building an understanding of them rather than requiring them to build an understanding of it. Valence CEO Parker Mitchell describes this as the defining transition of the year — from AI as a tool you seek out, to AI as a proactive coaching presence in your daily work.

Parker Mitchell

2025 was the year we had to go to AI — we had to try to understand what AI was. But at Valence we've been really focused on this idea of personalization. You'll hear in a moment the story of how we think AI is going to usher in an era of personalization and how powerful that is. What we've seen in the underlying architectures and the power of the models and our ability to incorporate them into an AI coach is that 2026 is going to be the year in enterprise where AI is going to come to you and AI is going to come to your workers where they are — and it's going to try to understand them instead of them going to AI and trying to understand AI.

Valence's Journey: From Engineering to Leadership Development

Parker Mitchell

I want to share a little bit about this, but I want to begin with a couple of threads that tie together why we at Valence are here and standing before you today. I want to go way back to the 2000s. I studied engineering. I did a minor in cognitive science. I was fascinated by how the brain works. And the brain works in neural nets. My favorite course was Systems Design 422, machine intelligence. We had a chance to build very small back-propagating neural nets. This is the foundational technology for LLMs — but they were in the order of 200–300 nodes instead of 200–300 trillion nodes. It was just a very, very different experience. That was the AI winter. But that fascination, that curiosity, was always there.

Chapter two: I founded an organization called Engineers Without Borders, and we had a social mission — to mobilize the engineering profession to contribute to eradicating world poverty. But what I quickly learned is as this organization took off and went from 100 to 500 to 1,000 to 5,000 to 10,000 people, most of my job was about culture and how to bring people along in this movement. I got some very clear feedback, bluntly delivered, that as an engineer I fit into the engineering stereotype — maybe my EQ was a little less than my IQ. And so I realized that if I was going to help this organization achieve its mission, I needed to become a student of leadership.

If you looked at my bookshelf, you would have seen all the classic books — Pat Lencioni's Five Dysfunctions of a Team, Bob Kegan's work on adult development, Atomic Habits — anything that I could look to to say, how could I apply lessons that other people have learned to my own life? And I began trying to bring that to other people. The thing I very quickly realized is the thing that worked for me might not be the thing that worked for someone else.‍

The Founding Insight: How Teams Work Together Drives Performance

Key Takeaway: What Research Says Is the True Driver of Team Performance

A 2016 Google study led by Prasad Setty's people analytics team found that the driver of team performance is not who is on the team — it is how the team works together. This insight was foundational to Valence's founding thesis: that organizations should invest in how people collaborate, not just who they hire. AI coaching makes it possible to develop those collaboration skills at scale, personalizing guidance to each individual's working style and relationships.

Parker Mitchell

In 2016, there was a magazine article in the New York Times called "The New World of Work." It featured a study by Prasad Setty's team at Google. Prasad was the founding father of the people analytics team at Google, and their research was unequivocal: when teams come together, the driver of performance is not who is on the team — it is how the team works together. That was something that resonated deeply with me. I was working at Bridgewater, which was very much an individualistic culture, even though the data suggested that how we work together was the most important thing.

That concept was the founding idea of Valence: how we work together, how we collaborate together, to drive performance. For five years, we had tools that really tried to help leaders and managers understand themselves, understand their teams, understand the dynamics of their teams, and use digital tools to bring best practices to life for leaders.

Going AI-First: The Only Path That Made Sense

Parker Mitchell

As soon as the publicly available large language models for reasoning emerged, we quickly knew we had basically two paths — and really only one was the right path. The first path: add AI on to our existing SaaS software system. The second path — the path we quickly decided was the only one that made sense — was to say this technology is going to be the most transformative shift and we have to reinvent ourselves as an AI-first company. With that AI-first lens, the scope of possibility, the way of bringing new ideas to life, is just an entirely new lens and mindset.

Is Jeff Dalton in the room? Jeff is our head of AI. He is a Turing Fellow. He is a professor. He has had teams of PhD students studying these questions of how you build intelligent conversational assistants — finding answers to questions that the rest of the world is just starting to ask over the past year or two. And so in 2023, we launched Nadia.

Key Takeaway: How AI Coaching Scales Personalized Development Across Enterprise

AI coaching enables organizations to deliver personalized development support at a scale that was never possible with human coaches alone. Valence's AI coach Nadia builds an understanding of each individual's work style, relationships, and calendar context — then proactively surfaces guidance in the moments that matter. The goal is not to automate coaching, but to make it personal, timely, and continuous — available to every employee, not just those with access to dedicated coaches.

How many people here have had a chance to experience Nadia? I have a very interesting relationship with Nadia. On the one hand, I'm always very excited about the capabilities she has. And on the other hand, I know that every version, every time I try her, every time you try her, it is going to be the worst version of Nadia you've ever tried. Our mission is to just accelerate that growth.

When we kicked it off, the question we kept getting asked was: would people even talk to an AI coach? Obviously, that question's been answered unequivocally. All the research says people are more comfortable in some cases talking to AI than they are to humans. But by late 2024 there was this general sense that Valence had pioneered this category of trying to bring an AI coach into the enterprise.

Reinventing Talent Management with AI Coaching

Parker Mitchell

Last year we partnered with folks in this room — people in the HR function — and asked: what are the questions? What are the things you're wrestling with? And there was this belief that we could reinvent a talent cycle, a talent strategy, a talent management and performance management system that probably most of you feel is a little bit outdated — maybe not the experience you'd like to deliver to your managers and employees.

Key Takeaway: What AI-Powered Performance Management Actually Looks Like

AI coaching can transform performance management from a box-ticking exercise into a continuous, personalized experience. Nadia works alongside HR and L&D teams to reinvent OKR and goal-setting conversations, performance reviews, onboarding, and learning programs. After 12 months of this work, Valence found that Nadia had moved beyond individual coaching to become the foundation of a new talent management platform — one that makes performance processes faster, easier, and more meaningful for employees.

Parker Mitchell

Our customization and solution engineers work alongside your team to reinvent OKRs, goal settings, development conversations, performance management conversations, onboarding, and learning programs. What we found over the course of 12 months of doing this is Nadia has moved from just an AI coach that can be offered to individuals to beginning to be a new talent management platform that can bring the visions that you have to life in a much more personal way — making it easier and faster and better for your employees to do those performance processes that are core to driving performance and productivity, but that have often felt like a box-ticking exercise or a heavier process than they need to be.

I want to say a deep thank you to everyone who has brought Nadia to life in some sort of performance management or talent management process in the past year. I know that bringing a new technology in is not easy. I know that bringing a new vendor in is not easy. We would not be here without the partnership and the trust you have placed in us. Our mission has been to repay that trust tenfold.

The New Generation of Nadia: Proactive, Personalized, Collaborative

Parker Mitchell

What I want to do is turn to this new generation. I talked about that gap — the difference between the frontier experience and the frontline experience — and this belief that personalization is going to be a huge driver. We have asked our team, given the new architectures we were able to roll out, to really focus on how we can bring Nadia to your employees. How we can have Nadia understand the world that each of your employees is in and give them the guidance and support they need in the moments that are most important to them.

How Proactive AI Coaching Works: The Calendar-Aware Demo

Parker Mitchell

Think about what a coach should know. A coach who knows everything about human nature has a helpful set of expertise. But the coach needs to get to know you as an individual — and that takes many, many hours of conversation before they understand you. But imagine if this coach, all they were doing 24/7, is focused on understanding you and your world and how to help you. And imagine they had access to your calendar. Imagine they got a chance to know each of the different people you work with — what their work styles are like, what their personality is like, what some of the dynamics between you or the group might be.

What Nadia has been doing on a daily and weekly basis is surfacing insights to me. She's looked through my calendar and identified what we call high-stakes meetings. She's saying: there's potential friction I want to surface to you. "Ana and you have very different definitions of ready." She talks about the summit coming up. I have an emergent style — I am happy winging demos. Ana is probably a little bit nervous wondering how her part of the demo is going to go. But that is a good thing to know.

She's asking me: "What does Ana need to know from you before Thursday?" And she's giving me some suggestions. Is it just confidence? Is it clarity? Is it air cover if something doesn't go as planned? I'm a busy executive. I don't have time to think through all the ramifications of things. So if Nadia is doing this and bringing it to me, it's an extraordinarily helpful experience.

Why Calendar Data Is the Real Source of Team Truth

Key Takeaway: Why Calendar Data — Not HR Systems — Reveals Who Your Team Really Is

Enterprise HR platforms like Workday rarely reflect who employees actually work with day-to-day. Valence CEO Parker Mitchell notes that calendar data is the real source of team truth: Nadia analyzes recurring meetings and collaboration patterns to build an accurate picture of each employee's working relationships. This allows AI coaching to be grounded in real team dynamics — not org charts — and to surface friction points between specific people before they escalate.

Parker Mitchell

Where do you find the source of truth about the teams you're on? Is it Workday? No. HR systems, we've discovered, are not the sources. The actual source of truth is really your calendar information. Nadia goes through and asks: who are the people you have the most meetings with? She can begin to assemble them into teams based on the types of recurring meetings you have. And almost all of us are cross-functional — so this gives a far more accurate picture of who you actually work with than any org chart can provide.

Building Personalized Coaching Through Work-Style Profiles

Key Takeaway: How AI Uses Work-Style Profiles to Personalize Coaching

Parker Mitchell

Nadia builds personalized coaching by incorporating work-style and personality frameworks — such as DISC or Valence's Perspective assessment — into each user's profile. This allows Nadia to adjust coaching based on whether someone is pressure-prompted or an early starter, whether they prefer direct feedback or a gentler approach, and how they communicate in group settings. Valence found that employees actively want colleagues to understand their work styles, which has driven strong adoption of shared collaboration profiles.

At the heart of this new highly personalized experience is the profile that Nadia is building of you. There's a private profile just for me that has information about my organization, my team, my goals. We also support a range of work-style and personality frameworks. If you like DISC, you can have people connect and upload their DISC profiles. We have one called Perspective that we've been using — hundreds of thousands of people in the corporate world have used that.

How many people here would say they are pressure-prompted — they do more things towards the end of a deadline than at the beginning? Now how many people are more early-starting? The coaching for those two people is going to be utterly different. You need very different coaching for that. So these personality profiles and work styles are very helpful in adjusting the coaching.

The thing we weren't sure about but we discovered quite quickly is that people actually want others to know about their work styles. They want to be able to say: here's the best way to work with me. So what we've been able to do is have Nadia say: if you would like to create a collaboration profile, the best way to work with you, we can do so. You get full control over it, and you get to reveal it, and other Nadias can understand this and give specific coaching on this.

Ana Martinez: AI Coaching from a New Manager's Perspective

Ana Martinez

Hello everybody. My name is Ana Martinez. I'm the head of engineering at Valence. Like Parker mentioned, I've been here for about four months, so I'm still onboarding — it doesn't feel like I'm new anymore. But before that, I spent five years at Slack.

The Onboarding Gap AI Coaching Solves

Ana Martinez

Slack had a reputation for the best onboarding process in the industry. They did a fantastic job. By the end of my week of onboarding, I felt like I knew the company, its values, its culture. I knew how to fix a bug. I even knew where the best coffee in the office was. But then you're left to your own devices. And I was like: but I don't know how to do my job here. I don't know who's working with me. I don't know who in my team is burning out. I don't know who my colleagues are. Who do I need to be building trust with?

That takes months. We're working with people. People take a while to open up to you. The engineer who is a high performer might be afraid to tell me things are not going well because he wants to show he has everything under control, even though he's interviewing and at the brink of burnout. I might not know what dynamics are in place. In the meanwhile you're expected to also deliver with your team, onboard new members, interview people and figure out what personalities are going to work well with your team.

Not only that — you do a great job and then suddenly: all of these new humans are under you. You went from 10 to 26. There's no onboarding for that.

What AI-Assisted Onboarding Looks Like for Engineering Leaders

Key Takeaway: How AI Coaching Compresses Manager Onboarding from Months to Days

AI coaching gives new managers access to team insights that used to take months of relationship-building to develop. Ana Martinez, Head of Engineering at Valence, used Nadia's people page to immediately understand the personalities of her 23-person engineering team — who needs careful feedback delivery, who carries too much without saying so, and where the friction points are. What previously required quarters of one-on-one conversations now surfaces in the first days of a new role.

Ana Martinez

In my people page, I can quickly add who my engineers are — who are the people working with me — and I can look at their personalities and really understand who I need to be careful delivering feedback to, and who really prefers a frank conversation. I'm a very blunt speaker and I've been given feedback about this. So it's great to know which of my engineers will shy away when I'm trying to give them feedback or understand why they're not performing.

Spotting Burnout Risk Before It's Too Late

Key Takeaway: How AI Coaching Surfaces Burnout Risk That Employees Won't Self-Report

High-performing employees rarely disclose burnout — especially to a new manager they haven't built trust with yet. Ana Martinez of Valence describes how Nadia flagged that one of her engineers, Chris, was carrying too much — information Chris would never have volunteered himself. Nadia also noted that Chris becomes hypercritical of himself under pressure, giving Ana specific coaching on how to approach him carefully. This kind of insight previously took months of relationship-building to develop.

Ana Martinez

As a new manager joining a new team, I want to know immediately who in my team is at risk of burnout. In this case, Nadia is telling me: Chris might be carrying too much. Let me tell you something about Chris. I've worked with Chris for the past four months. Chris will never tell me he's burning out. Chris is a team player. If I tell Chris, "Can you do this for me?" Chris will say yes, even if he's working at 2 AM and feels like burning out.

As a new manager, it's fantastic that I can see Chris is at risk of burnout. I need to make sure I'm working with them. Not only that, but Nadia also says he becomes hypercritical of himself under pressure. That tells me: blunt Ana, please be gentle with how you talk to him. Don't scare him off.

Preparing for High-Stakes Meetings as an Introvert in a Room of Extroverts

Ana Martinez

I also have the high-stakes meeting prep. I have a meeting with the leadership team where I'm the only introvert in a room of nine. I never speak. It was really interesting to see this insight because I thought: oh, this is why I feel like I always want to say something and by the time I've made it in my brain and practiced it a few times, they've moved on. I'm always the annoying person who says, "Sorry, can we go back to that last thing?"

It's been really helpful for me to know I need to get out of my comfort zone and be a little bit more assertive when my fellow leadership team members are talking at 100 miles per hour.

Leveraging High-EQ Colleagues Through AI Insight

Ana Martinez

For John — I've been working with him for four months. He has an incredible ability to read people. He can tell me really precisely who the people I need to be careful about are, where the friction points are in my team. I learned this through many conversations with John. But having this insight in Nadia might tell me: pay attention to what he's telling you, because his EQ is actually pretty high and I can't be everywhere with 23 direct reports.

Being able to get these insights immediately — without having to build this level of trust through months or quarters — is fantastic. This is one of the reasons I wanted to join Valence. I am a very passionate manager. Managers make mistakes with people, which hurt people. And by the time you learn how to do things, your top performer might have left, or you might not have delivered the tough conversations that needed to happen.

The Vision: AI That Helps Workforces Navigate the Human-Plus-AI Transition

Parker Mitchell

To bring this back to full circle: this idea of proactivity is the key thing we are weaving into this idea of an AI coach. There are different proactive coaching options you're going to be able to have, different types of nudges, and you'll have full control over that.

Key Takeaway: Why Proactive AI Coaching Is a Leadership Imperative in 2026

Helping workforces navigate the human-plus-AI transition may be the most important leadership challenge of 2026. Parker Mitchell of Valence argues that organizations will see a power-law distribution of AI fluency: some employees will be pioneers, while the rest will need support building that fluency over time. Proactive AI coaching meets employees where they are — not just to improve performance and reduce friction, but to actively support their transition to working effectively alongside AI.

The idea here is a bigger step. To bring our workforces along in this journey — and 2026 is going to be one of the most challenging moments for us as leaders as we try to help our workforces navigate this — one of the key things we need to do is try to put the most helpful and powerful and personal and augmentative AI into their hands. You're going to get some folks who are the pioneers and are going to be pushing the boundaries. For the rest, it's going to be a journey to try to help them build that fluency. And so we are actively working to put proactive AI into employees' hands — not just to help them perform better, not just to help reduce some of the friction of how people work together, but also to help them make this transition to the new human-plus-AI era.

We wanted to just showcase to you some of the things we think are possible at this intersection of the frontier and the front lines. Thank you.

‍