Episode 254: What Happens When Every Employee Has an AI Coach? (with Parker Mitchell)
Performance expectations are rising - but the systems designed to support people haven’t kept up.
In this episode of the Digital HR Leaders Podcast, host David Green is joined by Parker Mitchell, CEO and Founder of Valence, to explore how AI is transforming the way organisations think about performance.
Tune is as they explore:
Why traditional performance management still feels broken
How AI coaching can support real-time performance improvement at scale
How trust, context, and timing make the difference in effective AI tools
What changes when every employee has access to a personal coach
The signals that show AI coaching is driving real performance impact
How HR leaders can start small - but smart - when exploring AI coaching
This episode is sponsored by Valence.
Imagine if every employee had a world-class coach in their pocket. That’s exactly what Valence has created with Nadia - the AI-powered coach helping Fortune 500 companies scale development, boost performance, and support leaders at every level.
Learn more at valence.co/insight222
[0:00:00] David Green: For all the noise about AI revolutionising work, most employees would still tell you the same thing: they're overwhelmed, under-supported, and trying to navigate performance expectations that shift faster than their organisations can keep up. Leaders want people to grow, collaborate, and deliver at a higher level, but the systems designed to support that growth haven't changed much in years. And then there's coaching, the thing everyone agrees matters, yet only a fraction of the workforce ever truly receives. That's the gap today's guest, Parker Mitchell, CEO and Founder at Valence, is solving through Nadia, the Fortune 500 approved AI coach. Rather than treating AI as another layer of noise, Valence focuses on how people actually work, the moments where they need clarity, support and reflection, and how coaching can show up in those moments in a way that supports both their professional and personal lives. This is why I'm particularly excited for this conversation today, as Parker and I explore what feels most outdated in how organisations support people, what leaders should realistically expect an AI coach to do, and why context and trust are essential for AI coaching to make a real impact. So, without further ado, let's get the conversation started with an introduction from Parker.
Parker, welcome to the Digital HR Leaders podcast. As the CEO of Valence, I'd love to start with the basics. What is Valence, first of all, and what was the original vision that led you to build the company?
[0:01:51] Parker Mitchell: So, Valence offers what is the most widely deployed AI coach across the Fortune 500. And there's a lot to unpack there, because what an AI coach was in 2023 when we first launched our coach has changed, as everything that is AI-based should change in the course of two years. But maybe I'll take a step back and talk about our founding moment. We were founded in 2018, and that was pre the AI that we know it. We had this vision that we wanted to democratise the experience of executive coaching. I was fortunate enough to have that kind of investment in my learning and growth and career early on, and it truly felt if we could give that to hundreds of thousands, millions, tens of millions of people, we'd build a world, the term we sometimes use is where potential is more valued than credential. And so, if people have a growth mindset, and they're interested in learning, if they seek feedback, if they're willing to experiment, we wanted to have a reward for the people with that approach.
Now, because AI tools weren't able to process language or anything like that, what we focused on was a suite of tools to help you lead your team better. This was about a year-and-a-half after Project Aristotle and Project Oxygen really came to the fore in the point of view of leadership development and organisational culture. The founder of Google's People Analytics programme, Prasad Setty, who's the author of those studies, is an advisor to us, he's on our advisory board. And so, we were saying, "How can you create a suite of tools that helps you understand yourself, understand in relationship to each of the team members, and then understand how your team functions as a whole?" So, we built those tools out. They were very popular in Fortune 500 companies that had an alignment with leadership and culture. If you had a CEO who said, "Hey, this type of investment in leadership is more important to me than maybe strategy", I wouldn't say more important than strategy, but just someone who was aligned with that, they love to be able to offer these tools at scale.
We had that initial in our 2018 through 2022, and then AI came along, AI changes everything. So, I could chat more about the AI coach, but that was sort of the origin story of how you help people work better together in collaboration.
[0:04:18] David Green: That's really good. And I guess what you're essentially doing at Valence is you're democratising coaching, to an extent. Prior to AI, coaching was really the preserve of the few at the top. And what you're essentially doing with Nadia is you're actually democratising and, obviously dependent on the company, you're potentially making that available to much more people within the organisation, which can only be a good thing.
[0:04:45] Parker Mitchell: Absolutely. And I think this idea of democratisation, so there are many, many companies who have chosen to offer Nadia to their full employee base. And I think it's important to understand as well that AI is -- I'm one of those optimists on what AI enables. I think it is going to be the most transformative technology we've seen in our workforce and our workplace, and I think there's pros and cons to that. I think different people experience opportunities and different people might feel setbacks or challenges. So, I'm not a Panglossian thinking everything will be perfect. I think the transition to a workforce where each individual employee leader feels enabled by AI and their AI is something for them to do their job and not AI is something that happens to them, I think that is a really important balance for leaders to get. So, I just want to state that I think it's a powerful opportunity and the path to get there is going to have zigzags and setbacks and things that will be challenging.
But AI, I think it's going to be more than just a human coach. And I've had extraordinary human coaches. And what they weren't good at is they understood human nature, they understood me. They were able to say, "Hey, I've seen this pattern in leaders before. This might be a piece of your psychology makeup that you might want to question. It was helpful to get you to where you are today, but is it going to be helpful to get you where you are in the future?" And that's very valuable. But all they knew was literally what I would tell them every three weeks or so for a 45-minute session. Whereas Nadia, and we're believers in dogfood, so dogfooding our products, so we use Nadia all the time. And where we think she could get better, we feed that back into the product. I probably use Nadia three or four times a day because she sits in my calendar, she sees the meetings that I have coming up, she's seen arcs of conversations I've had about every new executive we have at Valence, about the challenges, what we're trying to build next in product, how do you go to market in Europe, how is that different than North America? These are unique to us, but she can understand that context and is coming to me with, "Hey, you've got this meeting coming up. These are some of the things that you might be normally thinking about. Here's a couple of questions that you want to ask. And do you want 15 minutes before the meeting to prep more?"
So, it's a very different experience than a human coach. It's democratising coaching, but it's actually going to be, I think, more powerful in many ways than just having a human coach that you talk to.
[0:07:28] David Green: Very good. And we're going to get into that in our conversation, Parker, and learn more about Valence and some of the customers that you're working with as well. So, obviously you're an expert in this field, which is great when you're starting a technology company that's going to support many organisations. So, when you look at how organisations currently support people to perform, to grow, and to collaborate at work, what feels most broken or outdated to you?
[0:07:59] Parker Mitchell: I mean, I think one of the expressions I've used is, in my career, when I talk to others, the moment of peak professional incompetence is the day that you were promoted to manager. And most people's patterns is they were very successful as an individual contributor, they were noted to be a potential manager, they were promoted to manager. And suddenly, they have to unlearn all, not all, but in many cases, many of the traits that had them be successful as ICs, individual contributors, and then build a new suite of mindset and lenses and approaches to be a successful manager. And so, day one as a manager, you're saying suddenly, "These people were my peers. Probably one or two of them wanted the role that I now have, and so there's a strange relationship potentially there. I don't really know how to set goals, I don't really know how to motivate people in challenging times, I don't really know all the ins and outs of what the business wants of me". And so, on the surface, you want to show up like the leader that you were just tapped to be. But under the surface, you're paddling like crazy, like a duck trying to figure out what the first thing you should do is. And people often talk about that first year as a manager, very lonely, very little support. Even if the company has a programme, it might not have happened at exactly the right time. And the learning module might be six months in the future. So, there's sort of a loneliness to that.
So, I think the thing that's most broken is, how do you support frontline managers, especially in that moment of transition? And how do you support the managers at the frontline? They are the face of your customer service, they're the face often of your innovation or the face of your supply chains. That's what really makes a company run. And so, I think that's probably how we can support them, not just at that moment of transition, but in the lead up to it as well. I think that could transform the experience of work, but also the performance of companies.
[0:10:01] David Green: What can companies do to get managers ready or potential managers ready to be managers?
[0:10:07] Parker Mitchell: I want to return a little bit to what's broken as well.
[0:10:11] David Green: Yes, please do.
[0:10:11] Parker Mitchell: Because what's broken, I think, is a little bit the answer to that too. But what's broken is, people who are thinking about this just couldn't reach that frontline workforce. They couldn't even reach their frontline managers, let alone being able to say, "Hey, what's the level beneath that? And how do we determine who might be high potential leaders there?" You'd have programmes, but they're still dependent on the idiosyncrasies of human nature, and did someone come in in the right opportunity, or do they come in through a different sort of job classification? And so, I think that ability to reach everyone almost directly has been broken. And we've tried to replace, we've tried to come up with an alternative, which is sort of the, "We're going to train you through traditional ways".
Everyone knows the 70-20-10 model of learning. We talk about it, but we haven't actually ever been able to truly implement it. And so, there's still, instead of having learning courses, we have learning modules, bite-sized modules in the flow of work. I don't know about you, but I've never come across a manager who says, "My challenge is I don't have a good Netflix feed of two-minute videos for me to watch about how to do these following six things". Their challenge is literally at 5.00pm at the end of the day, their to-do list is longer than at 8.00am when they started, and they're trying to figure out how to juggle too many things. And so, I think it's this sense of overwhelm and being able to integrate learning into the daily flow, noting that everyone will be overwhelmed and not wanting to separate out of it. I think the technology, the ability to reach people at scale acknowledging that reality, I think, has been holding us back. It's been sort of a set of handcuffs that we've tried to overcome. But I think everyone who's experienced most learning programmes feels like we haven't quite cracked the answer on that one.
[0:12:06] David Green: So, I guess the question now that's linking the couple of conversations we've had together now, Parker, is how can an AI coach help with that, help those managers, new managers, old managers frankly, people who have been managers for a long time, to address some of the challenges they've got in the flow of work?
[0:12:24] Parker Mitchell: So, I think the starting point is, what are the challenges that someone is working on, and deeply understanding that. And so, we talk about that being embedded in your daily work context. And much of your work context is actually the relationships that you have with others. And so, most managers are getting things done through members of their team. Most, almost every team member, is collaborating with other team members to try to produce whatever the work output is, or interacting with them in some ways. They're often working cross-functionally across other teams as well. So, it's not just sort of a pyramid, but it's more of the matrix or the network-type organisation.
So, the first thing that we try to do with our AI coach is just understand what is your work and how are you working with others? What are the relationships you have? What are you trying to produce and how satisfied you are with that? And so, that's starting from the person and building out. And at the same time, we're trying to understand from the business perspective, what does the business want the various functions to perform? And so, Nadia can, on that second side of things, understand the business OKRs, the goals that a business has, cascading literally down, you know, maybe one function has a very deep set of goals that they have, and it will go all the way down to an individual person, maybe it's just to a leader or team or a unit. But Nadia is trying to always bridge those. So, what does Nadia know about David and David's challenges and what David's doing, and about what the business wants, and trying to bridge that.
So, I think if you understand those two realities, you could start to say to someone if, for example, say they aspire to be a manager, "Well, who's a manager that you look up to? What are the things that she's doing well? What are you noticing about how she delegates?" With someone like you, maybe we'll say David is conflict-averse, and this is something that you've had a conversation with Nadia about. Nadia could say, "David, you're going to have to give challenging feedback when you become a manager. Who does that well? How can you take a small experiment to try this in a safe-to-fail moment, rather than wait till the stakes are too high?" So, it's that ability to understand work, know where someone's going, know what the business wants, and being able to create a path that feels smooth in the flow of work to help you build, in micro moments, those experiments on the field -- we do a lot of sports analogies in North America -- not watching the video of what someone else does, but trying it yourself and getting feedback.
[0:15:00] David Green: We do sports analogies over here in the UK as well, maybe different sports sometimes, but we definitely do the sports analogies as well. So, you kind of hinted at it there, Parker, I guess one of the challenges that people might offer is, does an AI coach just offer generic advice? But I think you've explained there how, by understanding the work and how the manager and the team are collaborating, you really look to understand, at quite a level of detail, the individual manager, the team they're managing and the organisational context as well. Is there anything else that you'd like to add around that?
[0:15:37] Parker Mitchell: Well, I think the experience of personalisation is around your individual world. So, we're lucky enough to have Geoffrey Hinton, the Nobel Laureate, who's also spanned UK and North America quite a lot. I think he did a couple of his degrees in King's College, Cambridge, and in Edinburgh, if I remember correctly. He talks about one of the promises of AI is personalisation. It's personalised medicine, it's personalised education and tutors. And through our conversations, he said, "Wow, it's personalised coaching at work". If you think about what tutoring is, there's a degree of expertise that matters, but it's really understanding where it is that you are having challenges, is it a motivational challenge? You want to be able to increase the challenge step by step by step to maintain a sense of progression with a student, not get too far ahead, but also not have them be bored. And so, in health, it's similar. It's, what is the behaviour change that is going to help you be a healthier individual in the long run, and that might be different than your work colleague down the hall. And so, on the AI coaching side of things, it's very much understanding that personal reality and building out from that. And if you wanted a personal doctor, you'd want them to know everything about the expertise of medicine, but you'd want them to know everything about you and then be able to combine those.
That's the same thing with AI coaching. We wanted to know everything about what are the coaching best practices? What are the company best practices? What do we know about your job that makes your job hard? But then what do we know about you? And then, the combination of those two is what makes it feel magical.
[0:17:24] David Green: What if everyone at your company had a world-class coach in their pocket? Meet Nadia, the most widely deployed AI coach in the Fortune 500, built by Valence. Nadia is the only AI coach that's fully customisable for any talent priority, from performance reviews and KPI alignment to frontline manager support and relieving HRBP capacity. Global leaders like Nestlé, Delta, General Mills, Prudential and more are transforming talent development at scale with Nadia. Discover how you can give every employee a coach who understands them, their team, and the whole organisation by visiting valence.co/insight222.
How do you think about trust and privacy when you're collecting the kind of data that you've been talking about? Because again, obviously, if you're personalising something for the individual manager, that's great, because it gives them hopefully better outcomes. But obviously, a lot of the data you're collecting is potentially sensitive as well.
[0:18:42] Parker Mitchell: We built from day one, Nadia in Valence, on this idea that your personal information is utterly sacrosanct. It is entirely yours, and you need to know that it is confidential and private, or you won't talk about the real challenges. We talk to users about what they talked to Nadia about, we have interviews with them. So, we ask them, "What do you like? What do you not like?" And a lot of them talk about the safe space and say, "Hey, I had a challenge with my manager", or even this question of, "I didn't feel ready for the promotion". They talk about that with Nadia. They are not going go, and they've said this to us, I'm not going to go into my company version of Copilot and say, "I'm not sure if the CEO's strategy makes sense. How do I motivate my team?" Or, "My manager takes credit for my work. How should I navigate that situation?" So, just the knowledge that there is this private, safe space is crucial.
When we talk to CHROs, the ones that are more forward-thinking and sort of explored AI trends across their company, they're saying, "If I don't offer this to my employees, they're going to personal ChatGPT to ask these questions and potentially, they're not supposed to, but who knows what's actually happening on your own computer on your own device? Are they talking to ChatGPT about these issues for the company? We'd rather have them have the safe space". So, all that to say is, privacy and confidentiality is crucial. All the data is, you know, company data is uniquely for a company, individual data is uniquely for an individual. It's not being used to train any models or anything like that, it's never exposed to other people, it's really kept in that sort of cone of security and cone of privacy. So, that's the short but unequivocal answer, is trust is paramount. And I think it's just going to get more so as AI disrupts more in the workforce.
[0:20:34] David Green: We covered a little bit of this, Parker, but again, let's talk about this in a bit more detail. So, what changes in an organisation when everyone has access to an AI coach?
[0:20:45] Parker Mitchell: So, it's an interesting sort of phenomenon. So, if I begin to use my coach to help me think about maybe, I'm early on as a manager, I've got imposter syndrome, I'm not sure how to do goal setting. So, the coach is getting to know me and is helping me in the flow of work. And the first maybe five conversations that I have, I am reaching out to my coach. It might be in Microsoft Teams, it might be embedded in different places, it might be on my phone, but I'm asking the coach for questions. Nadia is beginning to form, she's creating a profile of you. So, she's saying, "What is the type of work that you're doing?" She's got hypothesis constantly, so she's thinking in the background. Probably 95% of our API calls happen outside of the conversation as Nadia tries to plan and think about how to help you. And so, she might, again, start on a Monday morning and say, "Hey, here's a couple of things coming up. They're conversations that we've talked about. You wanted to practise this idea of listening first in your meetings. You're a new leader, you're used to having the loudest voice, maybe you've gotten feedback. You uploaded a 360, you've gotten feedback that you should listen more. Here's a couple of chances to practise that". And so, the conversation shifts from, "Hey, I'm going to you to ask a question", to, "We're in a dialogue where Nadia will reach out to you". So, that's sort of a first change of phase almost as people begin to use Nadia in that way, or partner almost with Nadia in that way.
The second thing is when you have 10,000 people or 50,000 people who are using Nadia, what CHROs and talent leaders are saying is, "Hey, maybe these performance processes, these talent moments, the goal-setting exercise, the quarterly check-in, the development goal-setting and personal learning plans that we have for each person, or the end-of-year performance reviews, those are awkward, they feel like they're a little too structured, they're a little too linear, they're hard to bring to life. Maybe Nadia could help people, not just do the performance review, which is the first case, but make sure that you as a manager are having check-ins with people on a regular basis, that you're sharing with Nadia, "Hey, David's really good at X. Oh, David didn't do as well in this meeting and didn't ask for feedback", gathering those in-the-moment pieces, notes basically we call them, coaching notes, that you just share with Nadia, that she can then blend into initial drafts of, "Hey, here might be a development area for David, here's where he's doing it well". So, this idea is, if Nadia knows about you and knows about all your talent moments, you can put the two together in a much more seamless way and take away some of the -- I think honestly, a lot of managers, performance review season is not exactly met with big smiles. But if Nadia is helping you with it, it can make it easier, make it faster, but I think more importantly, make it better as well.
[0:23:49] David Green: You're working with some really impressive organisations at Valence with Nadia. Where are you seeing some of the biggest impacts so far? Is it performance, alignment for strategy, change management skills, other areas?
[0:24:00] Parker Mitchell: I think it's around the bringing to life company strategy, but at a very, very individual way. So, you are based in the UK. If you go to one of the popular coffee shops, it's the largest coffee shop in the United Kingdom, Nadia, there was a pilot there to help store managers, branch managers of this coffee shop, think about how to manage their store. And so, there was a set of information that Nadia had learned about the company policies, but handling challenging customers, strategies for team motivation, for upselling at the till, all those types of questions, Nadia was being trained on that. And I remember learning about how hard it is to be a frontline manager. I mean, these stores that every sector, every pea of extra upsell is being measured and they're being compared against a bucket of 50 other locations, and every week it's published. I was going, "Wow, this is the degree of which operations are sort of tightly, tightly assessed and you know how you're performing". It's really precise.
But what that meant is they very quickly realised, the companies, that the stores that were being coached by Nadia were outperforming the stores that weren't. And they saw a 20-percentile jump in NPS scores, if I recall correctly, from customer NPS as well as upsell. And so, they've now rolled out Nadia to all their store managers for the holiday season, where she also understands all the holiday promotions, and that there's quite a bit of complexity in managing that. And obviously, holiday is the time where you make all your extra money, and it's really challenging because everyone's busy, stressful customer experiences. And so, Nadia is helping 1,000-plus store managers try to manage this holiday season in a better way. Honestly, I wouldn't have predicted this two years ago. I thought AI coaching was going to be more, "Hey, this is an extension of what a human coach is". But because we can train Nadia in all those different things and she can understand that context, she can really make a store manager's life easier and improve the performance of the store. So, that's just one example of an impact that I wouldn't have expected.
[0:26:18] David Green: I want to take a short break from this episode to introduce the Insight222 People Analytics Programme, designed for senior leaders to connect, grow, and lead in the evolving world of people analytics. The programme brings together top HR professionals with extensive experience from global companies, offering a unique platform to expand your influence, gain invaluable industry insight and tackle real-world business challenges. As a member, you'll gain access to over 40 in-person and virtual events a year, advisory sessions with seasoned practitioners, as well as insights, ideas and learning to stay up-to-date with best practices and new thinking. Every connection made brings new possibilities to elevate your impact and drive meaningful change. To learn more, head over to insight222.com/program and join our group of global leaders.
Let's talk more about performance reviews. As you alluded to, Parker, we're recording this towards the end of the year, so many organisations are going through that cycle around this time. Now, performance has had a lot of tweaks over the years. It's still one of the most unloved processes at work, I think it's very fair to say. So, from your point of view, why do performance reviews remain so broken?
[0:27:54] Parker Mitchell: I just don't think it's how humans think about interacting with other humans. I don't think about putting someone in a bucket or on a scale. I think Likert scales, don't get me started on the degree to which scientists, people analytics are like, "Likert scale, the difference between a 6.3 and a 6.6". Humans are like, by the time you get to question 12 of some survey, you're like, "Yeah, I'm just clicking through things as quickly as I can and directionally correct". So, I think we just don't think in those linear terms about people. We have human relations with them, so there's likeability impacts. There's just so many different things that fit into it. And ultimately, what we're trying to do is say, I think performance reviews are not about how do you help each individual person get better in the day to day, but they're about who is going to get a promotion or a bonus, and who is going to get potentially a performance improvement plan, or where are we officially going to situate people. And so, I think that process is difficult.
What we're trying to do with Nadia, it's twofold. It's one, if you're just starting from scratch, make that process a little easier. So, don't just start with a blank slate, be able to translate your stream-of-consciousness thoughts into some structured output, so she's not just saying, "Write a performance review", but, "I'm going to ask you a few questions. What's an example of this? What's a moment where this happened?" Not, "Here's the answer", but like, "Here's some of the information that will feed into an answer". And if you don't have as good an example, she'll push you on that. So, she's not just translating your thoughts, but she has a best practice set of steps that she wants you to go through. But I think the bigger impact is then, in January, February, she'll help you set goals with that same team that you have. And then, she'll identify check-in moments and coach you on how to coach each individual person.
What that's leading to is, I don't know if you're seeing customer obsession is a really important thing for us this year, she'll be trying to encourage you to integrate one little experiment on customer obsession, let's say every quarter, with your whole team and with each individual in it. And so, what you're seeing over the course of the year, because you're getting those nudges in the day to day, you're actually seeing customer obsession increase. And by the time you get to the end of the year, Nadia has got a lot of information to work with you on to make the performance review of each individual person much smoother, much easier. So, it's that holistic weaving together of this moment that happens one out of 52 weeks of the year into the other 52 weeks. That's, I think, what's really important.
[0:30:46] David Green: Yeah, because I guess if you're a leader or whether you're on the receiving end of a performance management review, there shouldn't really be any surprises, should there? And it sounds like from what you're saying, Nadia can help remove that surprise element about it by making it far more proactive. And if a conversation is needed, positive or negative, that conversation is happening at the right time and there's a chance to course-correct before you spend that one week a year when you do all those performance reviews.
[0:31:19] Parker Mitchell: I mean, let's not forget human nature being what it is, we'll never get to perfection. I think a classic thing is, let's say that I have an idea, a piece of feedback that I could give you, that is a risky thing for me to do. You could respond well, and that will be beneficial to you as an individual, be beneficial to me as your manager. Or, it could demotivate you and you could say, "Hey, I don't like Parker, I didn't agree with that feedback, but I know I have to just pretend to. But maybe I'm going to look for a transfer to another team, or maybe I'm going to look for another job". And so, it's risky for me to try to course-correct and help you. And so, what Nadia is really good at doing is saying, "Okay, let me unpack the assumptions that you might have about why this is risky. And then let's find one small, safe step". And it's that application. The expertise that we've really tried to bake into her is for every issue that you're facing, there should be one small step that you can learn a base of more information, de-risk it in some way. And if you can begin with those small steps, and they'll be different for each individual, that's when you can get up to saying, "Okay, we have an open relationship where I can give you feedback and where you can give me feedback". That might be 6 or 12 months down the line. Performance reviews tries to take that and force this giant step into the one week of the year, and that's why people feel so nervous about it.
[0:32:50] David Green: So, Parker, I mean you've alluded to it again a little bit around this, trying to get it from being a once-a-year thing. If you were redesigning performance from scratch, what would you want people to experience instead, I guess, whether they're the manager giving the performance reviews or the people receiving the performance reviews?
[0:33:09] Parker Mitchell: I mean, I think given the technology that we have available to us today, I would focus more on what do we think are the moments throughout a year that our top managers say, "This is an example that we think will drive higher performance for the business". And it will be different if you're in sales, if you're in logistics, if you're in a customer-facing role, if you're in hospitality. And so, it really depends on what the manager, what the leader of that function is saying. One of the advisory board members that you mentioned, well, you mentioned our advisory board, Tim Hourigan from the Home Depot is just retired as CHRO, had kicked off a Nadia pilot, thinks it has a possibility to transform a workforce in the many hundreds of thousands. He deeply understands what it's like to be a new associate at Home Depot, what it's like to be promoted to a shift leader, what it's like to be promoted to associate store manager or store manager. And so, when you take some of that knowledge and bake that in and say, "Okay, here is what the best practices are". In this case, I'm stretching, I'm not an expert on Home Depot, but when you're dealing with contractors versus a do-it-yourself person, when you're dealing with someone who has a home emergency because something went wrong versus someone who's got a project they're looking at, if you can understand the things that drive the long-term performance around loyalty, around customer experience, not just day-to-day upselling, if you can bake that in, that's where you're going to start to see the improvements in performance. And that's in the one-to-one.
But as teams collaborate to do that, how do you acknowledge that an associate on the floor has just had a really challenging moment at home? There's changes. Home Depot is well known to be targeted, not targeted, but experiencing some of the immigration changes. That's going to change the experience of associates potentially, or people in the stakeholder group. How do you acknowledge that in a way that's respectful? Being able to bake those in in the day to day, that's what leaders and individual employees are looking for, not how do I arbitrarily measure performance in a framework once every 12 months. So, I'd really focus on that day-to-day side, baking in that expertise.
[0:35:37] David Green: Very good. And you've mentioned a couple of them, Parker, already, you're working with a lot of large organisations in different sectors. I love the example you gave about the large coffee company based in the UK. Are there one or two behaviours that you consistently see from Chief People Officers or executive teams in the organisations that move fastest when it comes to AI adoption?
[0:36:00] Parker Mitchell: So, I think it starts from the top. I think CHROs that experiment with AI on their own -- there's a writer on AI who I have the greatest respect for, Ethan Mollick, I imagine someone whose work you've seen. He talks about three sleepless nights. He says, "You have to have had AI not just generate a poem in a Shakespearean sonnet, but you have to have experienced what it's like to have AI do your work in some ways better than you, or some small part of it. You have to see the potential". Really, I'm Canadian, so there's the hockey expression, "You have to skate to where the puck will be, not to where the puck is". And so, one characteristic is because they've experimented with it, they're seeing, "Oh, this is where AI could be". They're thinking about AI and the powers of agentic AI and the guardrails, and all the things that will be there in 6, 12, 18 months. So, one is they're sort of future-oriented.
Two is, not just they're willing to, they put the effort into helping their companies experiment with AI. One of the things that we just say over and over again is, "Just put AI into the hands of your employees". You don't exactly know which is going to be the most powerful. You honestly can't say in three years what the best solution is going to be. But you have to have different options. You have to say, "Hey, we're going to pick four or five different partners", they're going to try different things. One might be an incumbent, one might be a new startup, one might be someone trying to bolt AI onto their existing solution. But put it into your employees' hands and get them to give you feedback. Everyone talks about the big game in AI, but it has to be delivered through experiences. If you're a big company, the DNA of big companies is to prevent these experiments from happening. CHROs have to say to their AI councils and their Chief Legal Officers and others, "We don't exactly know what the answer is going to be, but we've got 500 people or 1,000 people or 2,000 people in the sandbox. We're going to let them play around with this tool for maybe it's six weeks, maybe it's three months. We're going to have a defined experiment", and they're able to push that through, because that gives you so much more signal.
If you come back and you say, "These 1,000 employees have said, 'This solution saves me time. It's answered this question in this way. It's helped me see a new insight about myself'", if you get that information back, suddenly then you have the ammunition to go, "Hey, this is a good bet. Let's take this bet a little bit more", versus, "I'm running an RFP and I've check-marked seven boxes and this one scored a 76 on 100 and this one was a 79 on 100. We should go with this one instead of that one". That's not how you evaluate AI. There was a couple of different answers in there, but I think that understanding the future orientation and the willingness to experiment are a few of the key things.
[0:39:04] David Green: That's really good. And it's funny you mentioned Ethan Mollick. I mean, anyone that's listening to this who's even vaguely interested in AI, and you really should be more than vaguely interested in AI, his One Useful Thing blog, I think is really, really good, because he talks in everyday language. You don't have to be a technical expert to understand what Ethan's talking about. And I've heard him say this a few times, and I saw that you'd had a conversation with him at Valence as well, Parker, about him talking HR being the new R&D, and that kind of plays to the experimentation piece that you were talking about there.
[0:39:39] Parker Mitchell: And I just want to touch on that HR is going to be the new R&D, which I very much agree with. So, I think if I am in the CHRO's shoes and I think fast-forward five years from now, what am I going to look back on and say, "What was the thing I needed to get right?" And I think their legacy will be based on how successful they were at helping transition a workforce from the human-only world to the human-plus-AI world. In a world where there will be job disruptions, every job's going to change, trust is going to wax and wane, leaders that get the trust right, I think, are going to make that transition in a more successful way. If you think of it as like, "That's one of the key things I need to get right", and HR is the R&D of how to do that, you think about ROI in a very different way. No one looked at Elon Musk's early days at SpaceX, at the rockets being built and exploding and being built and exploding, no one was saying, "The ROI so far is minus-infinity percent". But there was this belief that if we get these building blocks, this will be possible.
So, you break down the phases of experimentation and you say, "If we get these building blocks, then we think the ROI is going to be extraordinary". You have to be disciplined about the building blocks, you can't use this to be wishy-washy about things, but the building blocks are going to lead to a much more transformative ROI than, "Oh, look, I was able to save $20 here or $500 there on different sets of interactions". And so, I think that the mentality of measuring the progress of experimentation in R&D is a crucial new skill for CHROs to bring to the table.
[0:41:31] David Green: And it's quite an interesting inflection point for HR, isn't it? Because traditionally, it's been a support function, it's been definitely focused on compliance and managing risk. And obviously, experimentation by its very nature means that you're not going to get everything right. But as you said, the opportunity to help the workforce successfully transform because of AI, and also redesign work, redefine what work is, and as you said to the human AI partnership, it's a massive task, but it's also a really big opportunity, I think, for HR leaders.
[0:42:10] Parker Mitchell: And I've talked about, and one of our advisors has expressed this concept, Lucien, from formerly Prudential, CHRO of Prudential, the Chief Work Officer. And so, HR is going to be the intersection of work and people and how do you get work done. And so, I really do think there's, bifurcation is too strong of a word, but there is a big part of HR that is sort of avoiding downside. You didn't want to get grievances if you were unionised, you wanted to obviously avoid any chance of a lawsuit, how do you handle employee relations, all the different statutory rates. You needed to build a system that was really rock solid at avoiding downside. But this generally came at the cost of capturing upside of how do you help managers learn across their function across the whole business? How do you align people around the CEO and the leadership team's new expectations? So, I think there's an opportunity now to really leverage AI to build the second part of the HR function that I think has unfortunately been underinvested in. The CHROs that make that transition, dedicate a team to this, and not get drawn too much into the downside avoidance, but say, "Hey, we're going to capture some of this upside", they're going to reap the benefits of it.
[0:43:33] David Green: So, what are the early indicators that you look for at Valence to help tell you that an AI coaching initiative is actually working? So, getting back to that experimentation piece, I guess, when a company first implements AI coaching, that's an experiment in many respects. What are some of the early indicators that tell you when it's actually working?
[0:43:53] Parker Mitchell: So, we've worked with Prasad to understand how Google measured the growth of new initiatives, and he talked about four phases, with ROI being the final phase. Step one is, what are the adoption measures? And so, are individual employees engaging with and using the new technology? That in and of itself is a very positive step forward, especially in HR. We've probably had dozens of people return to us after the first implementation and say, "This is by far the most popular tool that we have offered to our employees". I believe one of the managers at Delta talked about that. I know one major agricultural company, their Head of L&D said that she literally held up her phone and could read out the messages of just, "Oh my gosh, this is so useful". Just people being told, "We're investing in you. Again, this isn't about AI being done to you, this is about AI being done for you". That is very, very powerful. So, we look, number one, at adoption.
Number two is, what do people self-report in surveys of the benefits that they see? And this is very important because coaching is private. So, we can't even go in and see the conversations. We can see aggregate topics and data, and things like that. But you first have to go and ask your employees, like, "How are you using it? How is it helpful for you?" And think about what are the use cases that you would expect to see early on. As you build more context, you're going to build more expertise.
Third is proxy indicators. And so, proxy indicators of performance would be things like improvements in manager effectiveness scores in employee engagement surveys. So, we have one of our early customers, a large financial services company, Global, they had about a 25-percentile jump in the managers who were using Nadia for coaching compared to their control group. And so, that was enough for them to say, they'd already determined on the people analytics side that if you increase manager effectiveness, that that is the mission of their talent group. And they were able to do so by the second highest amount. The highest was in-person training, which is obviously very, very expensive. AI coaching is much more affordable. So, that was enough for them to say, "We will now offer this to our entire employee base". So, that's a proxy indicator.
Then, four is actual performance drivers. That's slightly easier in the operational world where those are measured. It's slightly harder in the knowledge work world, but you can begin at scale to say, "Are we reducing turnover? Are we increasing the effectiveness of new managers 12 months into the job?" and things like that. Those are the four stages that we're looking at.
[0:46:53] David Green: So, for those that are listening and think, "Oh, I like the sound of that, I like the sound of Valence", but they may be a little bit wary of another shiny object, where should they realistically start with AI coaching? What are the first few questions that they should be asking themselves and potential partners like Valence? And then, maybe if you've got an example, I'd appreciate if you may not be able to name the organisation, how would you embark on a pilot maybe with a new customer?
[0:47:19] Parker Mitchell: So, I'll start with the pilot because, as I said, I'm a real believer in putting whatever the technology is in people's hands. Because when we first started, we talked about Nadia being an AI coach. The question was, would people talk to AI? Is an AI coach a thing? Now everyone and their sister has an AI coach. LinkedIn Learning has an AI coach; I'm sure every HRIS will have an AI coach; service delivery agents will have AI coaches. It's a term that is almost lost, it's sort of the concept. We have an expression of, "Not every AI coach is created equal. Our AI team is led by a Turing Fellow, a full professor on leave from the University of Edinburgh, co-published 250 papers, him and his team. They have thought more about how you build these intelligent assistants than probably anyone in the world. And so, I could share that. Those are impressive credentials. But ultimately, it only matters if the experience of the AI coaches is powerful for employees. So, we're very much believers of find a way to put it in people's hands.
Now, when we talk about what the pilot is like, we will often work with a company to say, "Let's invest, let's make this an actual six-month pilot, put 2,500 people or 1,500 people or something in it. We're going to give a lot of information about what are the keys to success at your company. We're going to bake that knowledge in, in customisations and configurations. We're going to help Nadia understand what your people processes are. Pick one that's really important, and then really launch that experience". And that gives people sort of a realistic understanding of an AI coach that understands all these pieces of context, what's that like? So, that's how we would design a pilot. We can do lighter weight ones as well, but often CHROs, they just talk to other CHROs, and there's enough of them out there that will say, "Here's why you should go with Nadia. Here's what we've done. Here's how it's transformed our talent processes". That's often the way to do it.
But technology changes. So, I think everyone should do this, a pilot or a side-by-side if they say, "Hey, maybe Microsoft Copilot could do this well". Do a side-by-side. That's a very simple thing to do. Then, going back to getting to know what are the big things that we try to do is just have our customers tell their stories. We have an event coming up in February in New York, our AI Summit. We have a dozen or more already customers who are going to be sharing more about their stories. We have a monthly webinar series that's just use cases being talked about. We think that the place that has the most credibility that people listen to is their peers. And so, talk to their peers about what's working and make sure you hear a few different opinions about a few different things and do your homework, for lack of a better term. There's a lot out there. Some of it's shiny objects, some of it really works in implementation.
[0:50:22] David Green: Yeah, exactly. Hearing from other customers is surely the best way of working out whether to take the leap or not. So, this is a question we're asking everyone on this series, which Valence is kindly sponsoring, how can Chief People Officers influence leaders, executive leaders, CEOs maybe, to use AI to augment rather than replace talent?
[0:50:44] Parker Mitchell: I think it's a crucial question. Well, getting the answer to that right is as crucial. I probably talk to 15 CHROs a month of Fortune 500. And there's a new theme emerging where a CEO will come back from a gathering with other CEOs and their use cases are 90% around replacement, around can we do more with less? And often, it's the 'less' focus of things. And so, I think the crucial question is for an HR leader to say, the pulse of the workforce, the trust that people feel, their willingness to try new tools is going to be predicated on their belief that they will have this job or a job with our company in 12, 24, 36 months. And so, I think talking honestly with CEOs and the C-suite and saying, "How are we going to articulate this? Are there principles that are going to guide us as we think about how AI is going to influence work? And how do we articulate them? And then, how do we live those values? I think that it might sound a little bit naïve, but I think getting the answer to that right, to be able to weave that into the narrative and the decision-making is crucial.
Then, I think for the individual leaders, it is, how do you build this culture of experimentation where you know the first time you do it, it's not going to work? So, it's like having an intern, but the intern actually absorbs everything really, really quickly and really well. You still have to explain a few things to it, you still have to tell it how it did something wrong. You wouldn't expect an intern to get it right, right away. But if you do that, five, ten times, suddenly then the intern's moved into a third-year employee. And if you do that a few more times, it might be able to do some things like a fifth-year employee. And so, that ability to invest in the sequencing of guiding AI to make it a more powerful tool for you, I think that's a crucial part of the story as well.
[0:53:00] David Green: I agree. And hopefully, we can talk about rather than doing more with less, maybe we can do even more with the same, and talk about growth and innovation rather than cost. And hopefully, that's where the conversation will start to shift to. Just before we wrap, Parker, I know that you've recently got Series B funding at Valence. So, I'd love to hear what's next, what's next for Valence, what's next for Nadia?
[0:53:29] Parker Mitchell: I mean, we think that in five years, everyone's going to have this AI coach, and this AI coach is going to know them. It's going to be almost like a companion, a sidekick at work. It's going to be focused on helping them do the best job they can. It's going to bring back this idea of apprenticeship learning, of weaving in experiences into their day to day. So, I think that'll be the most transformative and the most democratising of the technologies we've experienced at work. And we are extremely excited to make the investments to get there. I think it is probably more, if I'm honest, about the AI side than the coaching side. It's not hard to bake in coaching expertise. It's hard to bake in all the other context and get the flavours of that right and turn some dials up and down. Eventually, you've got almost infinite context. How do you make sense of that? And so, we've got a world-class AI team, and we're very excited to sort of bring this incredible version of a personalised AI coach to tens of millions of workers around the world.
[0:54:31] David Green: Well, it's been wonderful to speak to you today, Parker. I've really enjoyed learning more about Valence, about Nadia, about where this could all go in the future. I think you're on the tip of something very exciting, I think, there. How can listeners follow you, find out more about Valence? Maybe, you mentioned the monthly webinar. How can they access that, if they don't already?
[0:54:52] Parker Mitchell: Valence.co is our website. We've got all the information there. That's probably the easiest way to learn more about the case studies, the customer stories, the use cases, all the different events that we have. That's the simplest way to stay in touch.
[0:55:08] David Green: Fantastic. Well, we'll put that in the show notes as well so people can get access there. And, Parker, thank you very much. Really enjoyed the conversation. Thanks for being a guest on the show.
[0:55:18] Parker Mitchell: I really appreciate it. This is a topic that's near and dear to my heart. So, thanks, David.
[0:55:24] David Green: Thank you again, Parker, for joining me today. It really was a fascinating conversation. AI coaching is really opening up new possibilities for how organisations support people in their day-to-day work, and I appreciate you sharing your insights with us. If you're listening and something sparked a thought or question, I'd love to hear it. You can join the discussion on LinkedIn, just find my post about this episode, either on my profile or over on the myHRfuture page, and share your thoughts there. I always enjoy hearing what listeners take away from these conversations. And if you found today's conversation valuable, be sure to subscribe, rate, and share the episode with a colleague or friend. It really helps us keep bringing these kinds of thoughtful, forward-thinking conversations to HR leaders and professionals around the world. To stay connected with us at Insight222, follow us on LinkedIn, visit insight222.com, and sign up for our bi-weekly newsletter at myHRfuture.com for the latest research tools and trends shaping the future of HR and people analytics.
That's all for now. Thank you for tuning in and we'll be back next week with another episode of the Digital HR Leaders podcast. Until then, take care and stay well.