AI Is a Team Sport: How Trust Drives the Future of Work

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Nichol Bradford: The leaders who thrive in the AI era aren't just the ones who embrace innovation. They're the ones who ensure it's inclusive, ethical, and deeply human centered. Compassion, belonging, and the ability to embed trust into digital transformation are no longer just ideals. They're essential for creating workplaces where everyone can thrive.

Our guest today is Rosanna Durruthy, Vice President of Belonging Learning and Employee Experience at LinkedIn. As a champion of inclusive innovation, Rosanna has pioneered initiatives like AI Skill Pathways to democratize access to future ready skills, and has been a global voice for ethical AI adoption. Her work focuses on ensuring that AI expands opportunities, fosters belonging, supports talent, and prepares organizations for the future of work.

Together we'll explore how AI and human insight can work hand in hand to create more inclusive workplaces, and we will dive into the role of compassion and trust in designing AI powered employee experiences. Rosanna, welcome to the The AI+HI Project.

Rosanna Durruthy: Nichol, it's a pleasure to get to spend this time with you.

Nichol Bradford: I love spending time with you because the conversations that we have about work and trust and AI and teams, every time I learn a lot from it. And so I'm really happy to share that with our audience.

To that, let's jump right in. I would like to start with AI and inclusion, one of the most exciting areas where human and AI intersects. AI has the potential to break down barriers and create opportunities, but also comes with some challenges. How can we use AI to build more inclusive workplaces? I'd love to share with the audience a little bit more about the AI Skill Pathways. Can you tell us about the initiative and what it does?

Rosanna Durruthy: Sure. So first, let me start a little bit with AI Skill Pathways and then we could dive deeper into how inclusion plays such a critical role in this transformation of the workplace.

AI Skill Pathways has been a fairly groundbreaking initiative for us. LinkedIn Learning and Microsoft partnered to offer more than 150 role and level aligned learning paths and professional certifications. These certifications allow organizations to upskill their talent and validate AI skills at scale.

One of the things that this has been based on is LinkedIn's AI upskilling framework, which effectively provides content that's curated by role and by level to meet learners exactly where they are. When we speak to the industry recognized credentials or the professional certifications that are included here, it's been a wonderful way to not only validate skills, but to signal readiness to assume new responsibility.

So in this era of leading and growing in the age of AI, where career mobility is so important, it's proven to be a really effective way for organizations to scale. One of our clients, a large consultancy services company out of India, has enabled more than 570,000 of their employees to actually have access to begin to create AI readiness. When you think about how you build structured pathways for learning and growth, the biggest challenge is how do you make those skills available and ready?

An important indicator of the impact that we've seen with this is how LinkedIn learning customers are seeing 98% year over year growth in AI skill development. That is greater than what non-customers are seeing, much greater. So organizations in the top quartile of AI literacy are seeing 18% higher revenue already, as compared with the bottom quartile. We are seeing AI skill pathways as a really critical and relevant way to create upskilling and enable the validation of those skills.

Nichol Bradford: Wow. So that's great. Really being able to allow organizations to map out their pathway that's also curated and works for their employees. But then those organizations are seeing an increase in the skill profiles of their talent base, and then we're able to actually connect it to the marketplace and show that organizations that are in the top percentages of employees having AI readiness, it's showing up in their economics and their revenue. Did I get that right?

Rosanna Durruthy: Absolutely. It's connecting the dots precisely. How do you build skills that enable an organization and its talent to be more productive and more successful, and we're already seeing really positive results there.

You also asked about inclusion, and as someone who has spent many years building teams and developing leaders, a lot of the focus that I've seen around inclusive leadership, I think organizations have often translated into the world of diversity and inclusion. But I think we are seeing a real breakthrough moment in that inclusive leadership skills are precisely the kinds of skills in this human plus moment. This moment where AI and HR are coming together and we think about how AI as the technology enables vast transformation in how individuals are able to collaborate with teammates, how they're able to innovate together, how they can build outsized impacts.

But there's a really fundamental part of that equation we cannot overlook. In fact, it's the most important part of the equation any leader can truly control for, and that's how are you creating the kind of psychological safety, the kind of trust that enables your talent to believe in what they're doing, to find purpose in what they're doing, and to feel confidence in continuing to work alongside digital colleagues.

If we think about it, we can't control necessarily for the behaviors of AI, which can be incredibly optimistic and positive. We also can't control for the behaviors of humans. In all cases, humans are dealing with life in flux and in motion. We are still going to have teams of people responsible for caregiving. We're still going to have teams of people dealing with health issues and life issues. We're still going to have the importance of what it is to be human in this moment.

In fact, it's going to be even more important because AI begins to reduce the need to compete with technology, and it increases the ability of working with technology to do what we do best. So leaders who are able to master this capability around trust building, psychological safety, deeper connections with their teams, creating high performing, highly effective team capabilities are actually able to extract more value. The value of human experiences, the value of human perspectives, the value of human intuition and insights alongside artificial intelligence really is the transformation that we should be seeking in our businesses.

Nichol Bradford: One of the things that I've been thinking about, and I'd love to get your thoughts on, is the intersection between belonging and AI usage. We've spoken a little bit about our thesis that the future of the AI workplace is going to become very team centric. Could you speak to teams and belonging and any thoughts that you have on that plus AI?

Rosanna Durruthy: Gosh, Nichol, I've got so many thoughts. The first thing that comes to mind when I think about belonging and AI is that while people often equate belonging just in terms of an emotion or an experience that people have, what's really fundamental is the dual components of belonging.

One, that a space is created for an individual to bring their best self into the environment and contribute. But I think there's another really important capability that belonging unlocks. It's the personal ownership for that space. Belonging in Spanish is called pertenencia, and pertenencia means ownership, to pertain to, to own. I think it's really important both from a linguistic and experience perspective when we think about the importance of belonging.

AI enables access in different ways. That's such an important part of what creates belonging, to feel that I can access from where I am or from what I know or how I may do things. AI enables customization, like role specific coaching is an example, and so depending upon how you learn or how you understand things, the ability to apply differentiated context that can reach an individual and allow them to be more effective in the work being done.

It enables things like recruiting in very different ways. If we think about inclusive job description drafting, if we think about interview preparation, if we think about skills first screening, it really allows more fulsome capabilities that will enable organizations and leaders to find the talent they need for the opportunities they have.

So there's really an opportunity to foster this much deeper sense of belonging by creating this reach and this breadth, but we can't forget that belonging is a byproduct of inclusion. Belonging is a byproduct of inviting people into circumstances where they can contribute and they can impact, and that's about perspectives. That's about welcoming a different perspective so that we don't have echo chambers. That's about how we even think about the LLMs that are being created, not having singular points of view that become the singular weakness by which AI fails.

We need the diversity of perspectives. We need people willingly contributing and trusting that their contribution is a part of this broader skill and knowledge base that AI helps to foster.

Nichol Bradford: I think, because I'm obsessed with teams, I speak to people who have looked at the science of teams for a very long time. So that includes professional athletes and it also includes military. One of the things, another aspect of belonging, in addition to being willing to take risks because of psychological safety or feeling ownership, the third part is that people who are in some of those situations, when they feel like they belong, they're also unwilling to let their team down.

So it's not just the ownership of the piece that they have, but it's like they belong to this team and they're unwilling to let the team down. So it creates a high level of excellence. I think what we're going to see is AI as a team sport. The importance of belonging in AI empowered teams is, I think that's one of the things that people, when we have this conversation next year, people will be really surprised by how important it is to effective teams.

Nichol Bradford: You've spoken about also compassion in AI adoption and now that we're talking more about employee experience, what does an AI powered employee experience look like that is truly human centered and considers compassion?

Rosanna Durruthy: Compassion is, I think, such a differentiator in most environments. It's an important access to belonging, to being seen, to being welcomed, valued, and appreciated. But compassion is also this intuitive capability that humans provide to each other. We're tribal beings, no matter how we look at it. We accomplish nothing alone.

In fact, to your very point, the ability of belonging to unlock this discretionary power and capability that we have, it almost evokes our super human nature because we bring more than just what we know. We bring ourselves to the equation, and that's what differentiates. It's part of the alchemy.

When we look at AI, we are looking at how we're able to really accelerate personalization, how we're able to meet people where they are, as opposed to creating one size fits all kinds of solutions. How it enables us to just be smarter in the moment to think about how we are showing up, whether it's, are we showing up with a sense of bias in how we're applying data and models that we utilize in our work and how do we mitigate those things?

AI has a remarkable way for being able to capture our words and thoughts and play back to us. Are we striking the kind of tone that we want to strike for the audience that we're communicating with? Are we able to reach that audience? So there's this way of differentiating that AI makes us aware of that sometimes we're not aware of by ourselves.

Then certainly I think a really important distinction that AI brings to the equation is speed. Velocity is such an important part of the moment that we're in where companies are dealing with how are they going to evolve. Not only to be competitive and win, but to earn the trust of customers and employees in a way that makes them relevant for the future.

We've seen any number of companies that clearly were considered leaders in their industries 30 years ago when those companies no longer exist. The pace of evolution for companies will be much, much faster. The pace of change will be much, much faster in this moment. AI allows individuals to have the agency and the access to be a part of that change in real time, not just waiting for companies to tap them on the shoulders.

I think that is a remarkable moment to live through as HR professionals and talent leaders, but I think it really also requires us to think about how are we not only enabling the change, but allowing ourselves to be the change to use AI in ways that help us transform our own way of being as HR professionals.

Nichol Bradford: I remember a long time ago listening to a talk by the Dalai Lama and it was really interesting. A lot of times people when they think about compassion, they think that it is only softness. But compassion is also saying, from an AI skill standpoint, this is the direction. This is where the value is going to lie. It's being empowering people to signal their AI readiness and to actually get on the road to being able to continue their development so they can continue to hold value and create value for themselves, for the teams and for the companies that they're at. So I think there's compassion is also honesty and clarity as well as support and tools as well.

Rosanna Durruthy: Well, at LinkedIn we call compassion empathy plus action. We often think of the term empathy and someone who's been influential in how I think about compassion is Jeff Weiner, the former CEO of LinkedIn, and he's done any number of talks and leadership courses on LinkedIn learning regarding compassion and compassionate leadership.

This idea of empathy plus action is really important because while it's important to put yourself in another person's shoes, ultimately being in their shoes alone does not forward or create something new. It allows you, perhaps, in the feeling that that person may have and it may provide some access, although not complete access around the experience, but compassion is actually where the collaboration begins. How can I help others? How can I support others? Not just how can I feel what they're feeling.

So this empowered context around empathy plus action becomes really important when we think about the products that we're creating, the solutions that we're empowering. How are we thinking about human-centered design? How are we thinking about designing with and not just designing for our customers, our employees?

As we think about the challenges this particular audience faces, many of whom I would expect are HR professionals like myself, it really signals this huge moment for us to imagine what will it look like to create differentiated experiences for employees in the future, especially in a world that's changing, in a world that's complex, in a world where we see a new generation emerging of digital natives.

We literally have to be multilingual in the context with which we reach our employees. We have to be multi focused in how we respond to the employee life cycle and what the needs of those employees are, and we have to do much of that in real time because time is often not our friend. When employees have options, whether it's the option to go to another company or what I consider the grander option to stay on the job and check out, the cost is high.

How we enable an environment that's high trust and high performing really requires us to bring that kind of compassionate leadership and compassionate capability to the use of AI to be able to build solutions that help people be the best versions of themselves at work.

Nichol Bradford: Well that's a great lead into the next question because our audience, they are HR leaders and they are simultaneously in the room for preparing the organizations for the AI era. They do learning and development, they are doing skills, and then at the same time, they are being questioned about their own value, that happens for many of them.

Could you speak to that specifically? How do we as HR leaders prepare employees and organizations to thrive? What does it take, what does it actually take to scale AI literacy and build a future ready workforce? What is it about how should they be thinking about the employee experience to be able to do that?

Rosanna Durruthy: I think so much of it really challenges us to question how we've done things in the past and how that might not work in the future. AI is unique in that it's not just a book you open up or a set of protocols or processes that you institute and people follow. AI is highly experiential and that in and of itself is what makes it so transformative.

If we think about traditional forms of learning, whether it's learning in a classroom, or learning by reading a book or attending a university, often that's informational learning. I take in the information and over a period of time, I'm expected to have gathered the knowledge and I will apply it at some point in the future.

But AI has its own challenges. When we think about how employees sometimes fear that AI would replace them, when we have concerns about whether AI fully understands the context that different people from different places and different experiences have. How are we imagining AI as a stalwart that removes the bias from solutions and ideas? We have to overcome some of those obstacles and part of overcoming the obstacles.

How do we create the space? The place, the time for employees to test these skills without feeling that someone's watching them and getting it right is more important than learning how to operate with it, how to play with it, how to explore with it, how to unleash your curiosity with AI and grow comfortable integrating AI in your life, not just your work, but in ways of finding answers, in ways of creating new ways of doing things, and ways of testing your ideas and collaborating to create new ways of doing things.

So it really is in this crossroads between how are we having employees learn these things by teaching them, how are we having employees play with these things? Literally play, testing it out in the exploration. How are we creating collaboration through hackathons where teams come together with ideas? They pressure test their ideas. They build something just from an idea without feeling that it's not a good use of my time. That's not what I'm getting paid for. I won't be able to show the result immediately, and in many ways go back to the basics of curiosity.

This ability to allow yourself to learn something, knowing you don't know what you don't know. AI offers us an opportunity to learn as we go along, to be able to test and explore and in community, how do we share what we're learning? How do we learn from other people's experiences so that we're not becoming these single points of failure and we're not operating in a de facto go it alone mode.

This isn't about what I do by myself. I think to your earlier point around teaming and some of the conversations we have, AI is actually the access to how am I thinking about what I'm doing with others as opposed to just how do I do my job alone inside of my job description?

Nichol Bradford: Well, and earlier you mentioned the speed of change and innovation and then where we just spoke about employees experimenting. What are some of the things that you've done at LinkedIn that other HR leaders can think about doing in their companies around getting people to have hands on with the tools?

Rosanna Durruthy: There have been a number of things that we've actually taken on as a way of encouraging employees to explore everything from hackathons and vibe coding sessions that we've introduced non-technical teams to engage in and experience and to see the joy of how employees who have no technical background actually see the work coming together, their ideas coming to life and sharing that with each other.

We have a monthly day that we call InDay at LinkedIn, which represents an investment day in our employees and InDay is typically a time when people come together. They not only attend workshops and sessions, they do things together in the office. We've done everything from Lego building in the office to sound baths for well-being and mental health to actually coming together and learning how to apply AI in day-to-day utilization and learning new tools.

We've created play dates, play as in P-L-AI, it's people and leader AI dates where groups of teams come together to learn how to utilize new tools and to share how they're building agents and some are doing it for their personal lives. Some are doing it for work-related products, but the idea is to be in the experience of learning as a community and often doing it even inside of teams.

We've been doing it for our very own talent organization, so there are teams who are doing it. We're doing it enterprise wide with time built into the calendar so that employees can attend. We do it on globally friendly hours so that our employees across all regions are able to participate, live and ask questions. We've made it a centerpiece of how we are evolving the experiences together and not expecting our employees to go it alone and figuring it out.

We're creating healthy competitions, but we're also thinking about this in terms of how are we creating an ongoing conversation that allows the learning experience to meet employees where they are, rather than presuming expertise or a lack of expertise. It's kind of like enter as you are. Bring your ideas, bring your thoughts, bring the intentionality of learning to this.

What we see is the adoption is growing and adoption is infectious. When people feel that they can do something and disclose that they're doing it, rather than hiding it. I think many organizations I've heard have employees who are concerned about sharing it with their managers or leaders, or concerned about saying, "Hey, I use AI to conduct research on the competition," or, "I use AI to better understand what my customers are doing."

Encouraging the spirit of transparency is such an important part of how people get pulled into wanting to know more and wanting to do this together.

Nichol Bradford: So what I'm hearing is make it official, make time for it in the calendar for everyone. So if I want to do it, but many people on my team aren't doing it, they're not meeting while I'm learning. So make it official, make it a day so that everyone can have time to do it in the spaces that they're in together, and then also make it easy for that and give them the ability to be in community and share. Because AI adoption is something that can be caught by people doing it together. Is that right?

Rosanna Durruthy: Absolutely, and even make leaders visible to this by having them share their AI adoption stories. I think it emboldens when leaders come with the humility of what they're learning, but also the vulnerability of how they may have failed or what they gained or what they struggled with to be able to demonstrate to their teams that we all have a beginning here, there isn't entering as an expert in the matter.

It's been phenomenal to even see the kinds of collaborations we've seen between our engineering teams, working alongside sales professionals and our go-to-market teams in helping them be able to build agents together and helping them understand how to utilize the tools. It's actually fostered and nurtured healthier relationships and trust across functional teams in the organization. That's a really healthy way of contributing to a culture that's growing together versus a culture that feels fragmented and quite frankly, distrusting of a future that awaits us.

Nichol Bradford: There was just recently a piece of research that came out and basically it was sort of like the number of CFOs and CEOs who actually had substantial hands on AI was very small percentage, so there's a lot of like reading about it, knowing about it, but in reality a lot of senior leadership teams don't actually know how to use it beyond using it like a Google search.

Because of that, the idea of what AI can and cannot do is really sort of informed just by the stories people, the projections that people have about AI as opposed to what it actually can and cannot do. So to have a cadence like you've described, where the senior leadership is a part of it and they're doing it too, and they're saying, "Oh, I built this thing that helps me manage my whole house in the play schedules of my four kids or whatever," that sort of thing.

It's really helpful, one, to show the audience, to show the employees, but two, to ensure that they actually have hands on as they're making decisions about what they think the scale of the company should be in the future. So I think that's really a wonderful way to ensure that from top to bottom, the entire organization understands.

Then the last thing I would say is that I'm using AI every day and what it can do changes nonstop. So the other thing that I like about what you've said, and I think is really informative for other leaders who are listening to this is that it's not a one and done. You don't train your people and then you're done with it. It's like every period you have to keep doing it because the capacity and capabilities of the models is evolving all the time.

Rosanna Durruthy: It's evolving and it's evolving so rapidly, and I think for leaders, an important part of being credible in this moment, both in how a leader leads teams that are human and increasingly will have digital workers associated in those teams, as well as how that leader is able to show up with a kind of compassion for how their teams build the confidence in utilizing AI, build the agility in applying AI, build the depth of skill around how they create with AI and create with each other really requires an up close and personal view.

This is not a delegated assignment, and I think it's one of the great sea changes that we will see in the workplace. Certainly over the last couple of years we've heard about organizations growing flatter. We've heard about how layers of management are being removed because it slows down organizations and creates greater bureaucracy. But we're also beginning to see the team is not just the people you're managing. It's people across other functions who contribute to your functions.

So leaders who don't understand how to utilize the tools are going to have a definitive missing. I'm not going to say there's something wrong, but I'm going to say there will be something missing in their ability to imbue confidence in the teams that they're working with, that there's an understanding of what the co-creation and creative process looks like when you're working with people and AI simultaneously. How are you helping shape the most valuable part of the equation, which is going to be human discernment?

We all know that perhaps one of the most critical skill sets that exists in how we work with AI is prompting. We are beginning to learn that even prompt engineering is changing. It's not a single question. AI has such capacity to digest my run on sentences and questions as I term it in the interest of how are we creating solutions that are contextual. How are we creating solutions that apply to the unique cultures that we are stewards of? How are we applying solutions that sit inside of the processes and the ways in which we do the work in our environments and organizations?

So AI is only as effective as its ability to understand and process how we work in the environments we work in to create the outcomes that we seek as opposed to very generic outcomes that have limited applicability and really create a lot of make work as opposed to valuable work.

Nichol Bradford: Yes. So much so. Okay, so last question. We always end with someone in the audience, they've thought about this conversation. What is the first thing they should do on Monday if they want to improve the employee experience around AI and help their company innovate and transform. What should they do?

Rosanna Durruthy: So if they haven't begun their AI journey, create intentionality around when you're going to start and you start on Monday. Quite frankly, carve out 15 minutes. Whether you're utilizing copilot at work, or you're utilizing ChatGPT, or you're just utilizing it in your personal life because you may still be a little concerned or not feeling safe about utilizing at work. Start building in regular time. A daily habit around AI. 15 to 20 minutes a day can be really transformative. It's not only really fun, you don't have to have a specific topic. It could be a question. It could be about your wellness journey. It could be about mental well-being.

Second, consider that it's not just the consumption of learning. Your AI is only as good as what you put into it. So it's how are you pouring yourself into the process? What questions are you asking? How are you challenging your AI to ensure that you're creating relevant answers that may be applicable? Don't think about applying all of it. Think about how you're going to process it first.

Think about how AI can help you summarize your day-to-day schedule. I now use AI to summarize my email. I get a lot of email every day. It's become a utility for me. Copilot is able to identify emails from not only the most important stakeholders I interact with, but summarizing them so that I know what actions I need to take first before I get to the rest of my work. So it's become, quite frankly, literally my trusted partner in how I create my day at the beginning of the day. So find ways to create your day with AI.

The third thing I would say is ask your teams how are they using AI? Get them into not only a conversation together, but think about how you're going to incorporate their learning journey as a team sport. Whether you have an offsite, where you dedicate an afternoon to your own vibe coding journey, or hackathon as a team where you're willing to bring a very nascent beginner's mind to this so that you can create confidence as well as learning.

Then the last thing I would say is keeping in mind the journey to AI requires all the things that we bring to our practice as HR leaders: responsibility, fairness, transparency, privacy, and security governance. Before we go and create things that we think are applicable for work, let's make sure that we're being responsible in instituting and implementing the processes either that already exist or are being created for our organizations so that we're creating a safe journey for everyone involved.

Nichol Bradford: Wonderful. Wonderful. Well, thank you so much. That's it for this week's episode. A big thank you to Rosanna for sharing your experiences and insights with us. Thank you for joining the conversation everyone, and we will catch you next time.