Episode 282: How People Intelligence Is Helping Shape Cisco’s AI Workforce Transformation (with Kelly Jones)
Your AI adoption numbers might be climbing. But what do they tell you about your people?
Kelly Jones, Chief People Officer at Cisco, and her team set out to answer that question, and the findings are reshaping how Cisco thinks about engagement, performance, leadership, and the future of HR itself.
In this conversation, David and Kelly discuss:
What prompted Cisco's People Intelligence team to ask a bigger question about AI than most organisations are asking
The connection between AI use, employee engagement, and career growth at Cisco
Why leaders who use AI themselves are so critical to driving adoption across their teams
The confidence gap Cisco is seeing between director-level leaders and mid-level employees, and what to do about it
How this transformation is reshaping the HR function itself, and the skills needed to build HR for an "intelligence era"
The wellbeing cost of change at this pace, and where to start if you don't know where to begin
This episode is sponsored by HiBob.
HiBob is the people platform built for the AI era, helping organizations replace fragmented HR systems with a unified foundation for workforce management. That's why Brandon Hall Group says unified workforce platforms are becoming the foundation for organizations looking to scale AI with confidence.
The report also includes a practical business case template with ROI modeling and executive evaluation criteria to help build your transformation strategy.
Download the Brandon Hall Group HCMS Platforms Report
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This episode of the Digital HR Leaders podcast is brought to you by HiBob.
[0:00:09] David Green: If you've been following the podcast for a while, you'll know I'm fascinated by what sits beneath the headline numbers on AI and workforce transformation, because adoption tells us something, but it doesn't tell us what AI is actually doing to our people; how is it changing employee engagement and performance; what does it mean for career growth and skills; what happens to wellbeing when the pace of change keeps accelerating; and how do leaders need to show up differently? My guest today has been digging into exactly these questions. Kelly Jones is Chief People Officer at Cisco, and over the past year, her People Intelligence team has undertaken an extensive study of Cisco's AI workforce transformation, combining employee surveys, interviews, and focus groups with data on AI usage, performance, skills, hiring, and employee experience. And the findings are fascinating. AI users at Cisco are more engaged, they stay longer. More than 70% say AI is helping them save time and become more productive. And those recommended for promotion use AI 50% more often than those who aren't. But the research also surfaces some important tensions. Leaders are critical to adoption, yet some senior leaders have lower confidence using AI than employees below them. And transformation at this speed brings very real implications for trust, collaboration and wellbeing.
So, in today's conversation, Kelly and I unpack what Cisco is learning about engagement, performance, career growth, and leadership. We also explore how these changes are reshaping HR itself, and the capabilities the function will need for what Kelly calls the intelligence era. There's a lot to get into, so let's get the conversation started.
So, you're Chief People Officer at Cisco, one of the most recognised and respected tech companies in the world. What drew you to the people and HR space, and what's kept you here?
[02:16] Kelly Jones: You know, it's interesting, I would love to say that I knew from a ripe, young age that this is what I was going to do, but I didn't. I actually thought that I was going to be an attorney. When I was growing up, my goal was I was going to go to law school. You find that a lot on HR teams, people who are the post-lawyer profession. But what happened to me in the early '90s, when there was kind of the rise of IT consulting firms, I ended up working at a company as a recruiter. My very first job was as a sourcer for an IT consulting firm. And I just loved it so much, because I felt like the work I was doing was actually impacting people's lives and by default, the lives of their families. I'm actually still in touch with some of those people that I placed in jobs. And then, I just realised it was where my life's work needed to be, because there's this purpose-centred thing. And for me, I've always known that growing up, I wasn't the best person on the sports team, but I was the best person to encourage others on the sports team. So, I think there's something about helping people be at their best that is at the core of my ethos. And falling into a career on a people team or an HR team is just really a blend of luck. So, I'd love to say it was a plan; it was more a little bit of luck and timing.
[03:27] David Green: And when I think of Cisco, Kelly, I think of a global company, obviously at the forefront of technology, fast-paced, constantly evolving as technology develops so quickly. And I imagine that makes the peopling agenda at times particularly complex to navigate. How do you think about that role, and how do you think about the role of the Chief People Officer in that context? And maybe, what are the big priorities for you at the moment?
[03:53] Kelly Jones: You know, it's really interesting. Where we are right now, I think for those of us that have done this work a while, this might resonate, but I feel like HR and people teams have been kind of defined by this role as a service provider. We are a service provider to the business, we're a service organisation. And while that is vital, I think it's kind of reactive. It's this information asymmetry that you see. And if you think about traditional finance and strategy teams, they've always operated with this level of predictive data and analytical infrastructure, that HR was just too bogged down in manual transactions to kind of play at that level. And so, where I think we are now, when you think about the role as a Chief People Officer and really, as HR teams, how they evolved, agentic AI is going to change all that. We're sitting in this really fun inflection point where we can, as a function, actually reimagine what we are here for, which I think is very exciting. And we've done a lot to integrate agentic into our case management systems, we've had good results.
But the thing about it that is exciting is it's not efficiency, it's capacity. And so, I think our role as HR right now is to think about how do we unlock human capacity, directing work towards human judgment. And I think, in terms of number one priorities to your question, for me, It's navigating that with the employee experience, you know, how do we go through this AI workforce having our employee experience at the centre? Because it's not enough to roll out technology, and my IT friends might be angry at me for saying this, but that's the easy part. It's really this cultural transformation that we, as people teams, have to lead our organisation through. That means designing around user needs as much as you design around workflows, and building these hyper-personalised experiences with this human-first mindset, and really bringing the entire organisation along very intentionally. And so, I see our role changing. We have to invest in kind of what makes us irreplaceable. AI kind of calls for this skills and capability view of the workforce. And what it's going to allow us to do, that we haven't done as much before, is enable this mobility, development, and these talent strategies that are dynamic enough to keep pace with the change that we're going to keep navigating. I'm excited about this future, in case you can't tell.
[06:08] David Green: Immediately prior to our conversation, I read again your article on the Cisco blog, and again, we'll put the link in the show notes for the listeners, which was all about the findings of the research of your People Intelligence team -- and we're going to get onto why you call it People Intelligence later on as well -- your People Intelligence team conducted on Cisco's journey in AI workforce transformation. And what really resonated with me is that rather than just, as you said, not just rolling out AI tools and measuring adoption rates, you actually stepped back and the whole research was around a much bigger question. And I know for the IO psychologists listening to this, I'm going to actually give the research question. So, "When AI becomes integral to how our people work, how does it shape engagement, performance, and growth across Cisco; and what does that mean for our business?" What prompted that?
[06:55] Kelly Jones: Yeah, it's a great question. And I think as we were looking at this, what we realised is we were asking questions, but maybe not the right questions, if that makes sense. Like, what we started looking at is, this is such a pivotal moment, and we were talking about things like AI adoption. And for me, that idea of keeping humans at the centre of any transformation is really the critical thing. And so, we started looking at the fact that we were asking questions about adoption, but we weren't asking the next questions. And that really becomes super-important to us. What is the impact we're seeing on humans? What is the impact that we're seeing on workflows? So, I think it was more a question of you can't navigate any huge human transformation without understanding the impact that it's having to your people. And so, for us, we really just wanted to dig deeper into that. And I would also say that it's something we're going to have to continue to do. It's not a one and done around this, it is something that as we are navigating this, we're going to have to continue to do it as we learn more from where our people are going and where our business is going.
[08:04] David Green: Yeah, and I think that's a great point. Because, I mean again, if we even think back to the pandemic, we wanted to first understand what was the impact on our people who were suddenly having to work remotely? Did they have the right tools to do the job? Were they caregivers, etc? And then, that whole question, as you said, evolved throughout the pandemic and coming out of the pandemic, when suddenly the question was around return to work and flexible working and everything else. And the question evolves, doesn't it? And the question with AI evolves as well, because I guess if you ask people at the start of a big transformation where they haven't got familiar with using the tools, they're going to give you a very much different set of answers than when they're hopefully halfway through that, and as they get to the end as well. And I think it's that impact on humans and workflow, because adoption is great. If we're rolling out tools, we want to understand adoption, but at what cost or what benefit? What's the positive impacts on the business? What's the positive and maybe the negative impacts on employees and workers as well? So, a really good question to ask. So, as I'm sure listeners are telling me, David, just shut up and ask Kelly, what did you find?
[09:14] Kelly Jones: You know, it's interesting, we learned a lot. And to your point about adoption, I just want to kind of put a fine point around that adoption is a lagging indicator. It tells you are people using the tool, and that's important; but it doesn't tell you what's actually happening to the work, to the roles and to the judgment calls that used to live with a person and now may live somewhere else. But we learned a few things. And this was our second, actually, the second study we'd done. And we were really focused on what is the impact on performance, engagement, and on how teams work together. And so, we found that AI usage properly actually creates this really positive cultural loop, it's this circle of goodness. Our high AI users actually report higher enthusiasm for our mission at Cisco, stronger confidence in the company's future, and they feel more challenged and empowered to grow, than some of their peers who aren't using AI. So, there's this really positive impact on engagement, which is really nice. But we're also seeing these super-measurable benefits that are tied to productivity and performance. More than 70% of our employees said that AI helps them save time and improves their productivity, and most importantly enhances the quality of their work.
But a really important data point in this that I just love was the connection between promotional velocity and AI usage. Our employees recommended for promotion used AI 50% more than those who didn't. And so, you get into this virtuous circle of higher engagement, feeling better about the company, performing better, getting recognised for promotion at a higher rate. But I think one of the most important takeaways that we learned was about leadership and skilling, and this concept that leaders have to be a player coach with AI adoption. One of the things I've always said is you can't mandate proper AI usage. If you just go to your company and say, "We're going to measure your AI adoption", what you're going to get is performative AI usage. Leaders play a really critical role in this, because we know employees are twice as likely to use it if their leaders use it. So, it's this concept of bottom-up as much as it is top-down. And I think one of the biggest lessons that we saw in this is employees also want to learn by doing. We had a really strong preference for experimentation over the legislated AI adoption training, and I think we all started with that. We all started with, you know, we're going to legislate AI adoption training.
But what we found is creating these micro learning environments, where people can experiment in a very role-specific way, actually doesn't just increase adoption; it increases collaboration across teams and across roles. Our customer experience organisation is a great example of that. They have these communities of practice built up that are not so much about job titles, but about what you do in the role and the use cases around that. And they're experimenting with each other and creating all of the agents that they're sharing. So, we found a lot of really interesting things.
[12:04] David Green: This episode of the Digital HR Leaders podcast is sponsored by HiBob. Has your organisation outgrown its HR stack? AI is about to make that expensive. The latest Brandon Hall Group report explains why fragmented HR systems are becoming a liability, and why unified workforce platforms are emerging as the foundation for the AI era. Discover how leading organisations are connecting HR, finance and operations to improve execution, reduce complexity, and scale with confidence. Download the report at hibob.com/davidgreen2026, or visit HiBob at HR Tech, booth 1927, or UNLEASH World at booth 101. HiBob, HCM for people-proud companies.
Were there any alarming or worrying insights that you found through this research? Because obviously, sometimes that's not necessarily good, but it helps focus what you do moving forward as well.
[13:20] Kelly Jones: I think to me, the most interesting -- and I'm glad you met Roxanne, by the way, because her and her team are the brain trust of this work we do, this survey that we do. So, she's a lovely person to know and talk to about this, really just a true thought leader. I think one of the biggest things that, I'm going to say alarmed me, is this concept of trust. And what we found was when we had individual adoption in a team, team trust actually erodes. So, if I'm on a team with five other team members and I'm using AI frequently, I'm a high adopter, but the other four people on the team are not, you see the erosion of trust on the team. And our hypothesis around this is, when you're looking across the aisle and someone's using AI a lot, there might be a tendency to say, "But is it right? Are you work-slopping me? Can we trust the data?" And so, the trust for each other drops a little bit.
So, I would say the erosion of team trust with individual adoption was probably the biggest aha for me. Some of these things were on my radar around leadership, you know, "That one feels intuitive", but the trust piece I was not expecting when we think about team dynamics. And I thought it was really interesting. And it changes a little bit how we need leaders to be talking to their teams about this, and how we need people to be thinking about the work.
[14:36] David Green: Yeah, it's a really interesting finding, actually. The way you explain it, it does make sense. You've got to learn together, I guess, and practise together and learn from each other, I guess, as well. And obviously, it highlights the need to build trust and collaboration between teams. So, I'd love to hear what you're doing with that finding, and how you build that trust and collaboration within teams and between teams when it comes to using AI.
[15:11] Kelly Jones: I think the core of this, the core of the trust piece, and I would actually say trust is bigger than even this, because if you think about trying to take your workforce through this transformation, we're in a little bit of an existential threat, if you think about it. People, particularly high performers, and leaders, senior leaders, who have been rewarded for doing their job in a really good way, now we're asking them to unpack that and do their job different. And when AI can do some parts of your job better than you can, it does create this existential crisis. So, trust, if you think about all of us trying to take our workforce through this, what I would call kind of a wormhole on how we think about this, we can't do it without trust. But for me, the trust starts really with responsible adoption. For me, the AI journey, one of the priorities we have is making sure all of our employees understand the ethical side of it, the approved use cases. We have an enormous library of approved use cases, and we really try to focus on ensuring that people understand the ethical side of it, but that we're also thinking about privacy through the lens of privacy by design, you know, how do we have responsible AI use when it comes to our people data, when it comes to all the things we do? Because we're a global company, we operate around the world. Responsible handling of people data is really critical. And we build security into the workflow.
One of the early things we rolled out was a PNC assist programme, which is, by the way, a great place to start. It's essentially like how do you automate, then agentic, your case management systems? And so, we make sure that the agent we have is only pulling from verified internal sources, like policy central and the official knowledge base, which by the way takes a long time to clean up if you're on this journey. But once you do it, you're pulling from only approved places, so you can interact with a high degree of confidence around HR questions. But I also think that this concept of trust, some of it is very basic. When it comes to this, do what you say, say what you do, be clear on what you don't know, and be clear on what you're using data for.
What I've found is the worst thing we can do, when trying to build this type of trust, is to go with a sense of bravado and false confidence around where we think things are going. I think we have to be clear about what we know and what we don't know, and most importantly what are you using your people data for. I find that we need to put that disclaimer in all the time, when we roll out a tool or we make something available, "This is what we are using the data for. This is who gets to see the data. This is what we're not using it for". Because if you think about it, giving people consent to use your data, you're out on a branch of trust on that one. And so, the way you build that is being clear about what you're doing, what you're not doing, and what you're doing with the data.
[17:57] David Green: Yeah, and one of the advantages we perhaps have in HR is we've been handling people data, employee data for years effectively. And obviously, companies like Cisco that set up people analytics, the People Intelligence team years ago, they've already got that sensitivity piece around that. So, I guess we're just magnifying that as we think about AI.
[18:18] Kelly Jones: That's right. Because if you build something -- at Cisco we're building a lot of this internally, so we're going to be able to API all of our systems -- the difference is you're just connecting it in a way that is a lot more powerful. So, people want to know that you're not doing things like, I'm going to make this up by the way, like looking at their badging rate and saying, "This is now going to determine your performance rating". We're just making sure that we're clear on, in this area of hyperconnected data, that we're not connecting things that shouldn't be connected, if that makes sense.
[18:51] David Green: That makes a lot of sense. What I also heard from you a lot there, Kelly, was communication is so important here. We've really got to communicate, and I guess that's where we come in as an important role as a people team, organisationally communicate why we're doing this, what the benefits will be to the organisation, but more importantly, what the benefits will be to individual workers and teams as well. I'm hearing transparency. You're being very transparent with what you're doing and why you're doing it, the approved use cases, etc, that people can use. And I'm also hearing a lot about intentionality here. You're being very intentional about how you communicate and how you help employees to actually use these tools and to thrive with these tools as well. I don't know if there's any words you'd like to say to those points.
[19:37] Kelly Jones: I think intentionality is the perfect word. If you have user-centred design, you have to start with that. And so, we're trying to be incredibly intentional about all of it, intentional about how we are even communicating things like, if you think about the responsibility of HR in the future, one of the things we're going to have to work on is zero-based workflow redesign, which takes you beyond jobs down to the skill, task, activity level. And what we're doing, we need the help from our team members to actually do that. And so, if you imagine there is a sensitivity, and you've seen a lot of press probably out there about how people are trying to get at what people are doing, so they can do this redesign without being intentional about what they're doing with that data and information and without having the trust in their workforce, that can make people a little bit twitchy. Like, "What are you actually doing with this? Am I designing myself out of a job?" rather than explaining, being very intentional about what the things are that we think need human judgement, what don't, and the impact that it's going to have on their role.
I get these questions all the time now from the teams about, "What does it look like in the future?" And so, there is this intentionality about how you navigate this with your team. And thinking of it as a technical transformation and not a people transformation is where I think people get stuck.
[20:53] David Green: Yeah, and that's that whole piece around work to redesign. We could probably have a whole episode on that, Kelly. I mean, I guess I understand why there'll be some trepidation perhaps from workers in some companies about that. But we all know that pretty much all jobs, all roles have some pretty boring elements to it. And these are the elements that potentially AI could help take away. So, again, a really important role, I guess, for your People Intelligence team, as they think about workforce planning and roles of the future, is actually redesigning work at Cisco as well. But hopefully from a positive perspective as well, because actually it makes roles and jobs more enjoyable for people, and it has a better impact on productivity and performance as well.
[21:42] Kelly Jones: Yeah, it's a fundamentally different relationship that we're going to have with the business. And this is what, you know, when I speak to my HR team about it, if you think about going from a service function that takes reactive data and reports back on, "Here's what's happened, here's what might happen in the future", to being an intelligence layer that can actually shift from using data to form a hypothesis before the business even knows they have a question, this is a fundamentally different relationship with numbers, also with strategy. Really, the people and HR function in this new environment have an opportunity to become an intelligence layer that drives strategy. And that, to me, is incredibly exciting, because it's a completely different relationship that we've historically had with our business.
[22:27] David Green: It is. So, we'll probably look at that a little bit more actually in a few moments. But I want to come on to the leader perspective, because obviously a lot of the findings that you had, they relate to leaders. And as I was listening to you, I think we found that leaders need to help they need to take their teams with them around AI workforce transformation, as you'd expect. But there's an important role for role-modelling, I guess, from leaders as well. I mean, it's not enough for leaders to say, "We all need to use AI", they need to lead from the front and do that yourself. I mean, one of the findings that I saw in the research was that leaders need tailored support, and would you say is that a challenge? How are you addressing that challenge and how are you equipping your leaders to do that?
[23:15] Kelly Jones: I actually think post-pandemic, all of our data has pointed towards the fact that the people that are struggling the most are our people leaders, because the role of leadership, I think, has been upended. And it's not enough that they have a strategy, drive a strategy, manage performance. What we are actually looking for, and I think the successful leaders in the future are going to be kind of what I'm calling the integrated leader, those who can combine deep technical fluency with deep emotional intelligence. The way this actually could play out is you have to understand the technology enough. You don't have to be a developer, I don't have to be a software developer, but I have to understand the technology enough to understand the impact to my function and design the future. So, I have to be able to do that. But then, I have to be able to, in the next moment, have a conversation with an employee who might be feeling a way about how AI is changing their work.
So, we need leaders who can take this technical fluency and combine it with this deep emotional intelligence. This is leaders who are empathic, who understand the technology and can kind of work as change agents. So, we're trying to create these intentional pathways with leaders to build some of these skills through coaching and real-time practice. And an example of that is we're working with some of our partners, we have a programme called Leading With Humanity, and it's really focused on how to do hard things in a really human way, because that's the part we can't miss in this, to my point earlier about it's not a technical change, it's a people change. So, we're taking very practical and research-backed information to empower leaders to drive these results and lead their teams. And we're focused on how do you lead with clarity, how do you lead with care, and how do you lead with courage? And we're also trying to create environments where they can do this and feel safe about it. Because I mentioned this earlier that we're asking leaders to show up in a slightly different way, because they've gotten to where they are maybe by being great and knowing the answers to things. And I don't know that that's going to be the future model for leaders. There's this confidence gap that we see where the higher you go, the more kind of daunting this rapid change of pace feels. So, again, it's not about the tech just solely, it's about the vulnerability required to learn something new when you're already at the top of your game.
So, we're moving away from traditional training, we're trying to focus on integration, we're trying to embed the support for leaders into their daily workflow. The Leading With Humanity series is good. Another thing that we've been trying to focus on is we rolled out just-in-time AI coaching for leaders. It's based on a scientific coaching methodology, but is also integrated with our guiding principles and our leadership principles that leaders can, in a very safe space, go in and play and experiment. It's completely confidential. No one sees what they say or when they interact with their leadership coach. And we did this because we actually found data which surprised me, which is people are more comfortable working with an AI coach than a live coach. I think there is this belief that if Cisco provides me with a live coach, that coach is there for me, but that coach is being paid by Cisco. So, ultimately, who are they accountable for? Whereas in an AI coaching methodology, you can be vulnerable, you can talk about the things you don't know, you can model and role-play scenario play, you can ask questions that you might not want to ask your leader or someone else. Because again, we're trying to move from the idea that you're the person that knows everything in the room as a leader, to you're the person that asks the best questions in the room.
So, this is a narrative shift. And when leaders model that and model kind of being the most curious person in the room and show their vulnerability about what they don't know, I think it unlocks this culture where everyone can experiment and learn and grow.
[27:06] David Green: This episode is sponsored by Workvivo by Zoom. Employee listening is at a crossroads. Organisations are collecting more employee feedback than ever, but turning those insights into meaningful action remains a challenge. On 30 September 30, I'll be joining Todd Reeves, Chief People Officer at Zoom, Alexis Fink, former VP People Analytics and Workforce Strategy at Meta, and the team at Workvivo for the Employee Listening Summit. We'll explore how leading organisations are closing the gap between insight and action, the evolving role of people analytics, and what AI means for the future of employee listening. It's free to attend. You can register via the link in the episode description, or by visiting bit.ly/4zw3Cia.
What's been the response from leaders so far with this additional support that they're being given?
[28:25] Kelly Jones: It's early on in the AI coaching, but we've had really high, how would I phrase this, positive response in terms of how often they're using it, do they feel like it's helping them, and their repeaters. Repeaters tell you a lot. You roll out a programme, and the idea of adoption, who uses it, isn't a thing, but who comes back is a thing, and how often that they're using it. So, I think that's been really positive. The harder conversation has been around explaining to leaders the requirement that we're going to need for them in the future. Because if you just look at this very honestly, we have leaders, and every organisation does, who are leaders because they were really strong individual contributors, they did a job really well, they got promoted, they continued to get promoted. They might not be comfortable in my comment earlier about courage and care and selective vulnerability. So, what we're focusing on is, how do we build it, how do you make sure it's a comfortable norm? And by the way, we have many areas of the organisation where they're fantastic, "I will take this, I will run with it". We have others that I think are having a harder time with some of these things, and I hate the word, 'soft skills', by the way. We used to call it soft skills and hard skills. These soft skills are hard skills, they're no longer soft skills. But just to put it in words that people kind of understand, we have some leaders who are having a hard time with that.
So, I think we have to create pathways for all of that; pathways for how you develop this and get comfortable with it, pathways for how you leave a leadership role, if you're never going to get comfortable with it. And I think we have to be confident in doing that. And that is a little bit uncomfortable, but it's kind of an uncomfortable truth when we think about future leaders.
[30:01] David Green: Well, we talked about job redesign and roles evolving with AI, and clearly the role of the leader is evolving as well. Yeah, then maybe what makes a good leader now and in five years' time is going to be different from what made a good leader five, ten years ago. I mean, there's still some skills which I think are consistent, of course, but yeah, it's going to be interesting to watch that evolve, I guess.
[30:24] Kelly Jones: I agree with you. And I actually think we're also going to have, with the level of connected people data, an ability to be much more specific about what great leaders look like when we see it. Because if you think about this and where this can go, we're going to have real time sensing information on where the best teams are, where the best performance is, and what are the characteristics of those leaders that are creating great teams. And this was my comment earlier about if we move from being able to say, "This happened over the last quarter, and here's what we saw", to, "Here is the sensing ecosystem that tells you where these great leaders are, here are their attributes that make those great leaders great, and here's how we create more of those great leaders and call it when we're not going to be able to do it".
[31:06] David Green: And actually, on the leadership point as well, particularly as it relates to AI, one of the findings in your study was that director-level leaders actually show lower confidence than mid-level employees on AI, which I guess is a different kind of challenge for you to address. But at least you've got that insight now, so you can now address it.
[31:27] Kelly Jones: Which is exactly where we started with the AI leadership coach, because we started realising it's really ironic, it's like this bell curve, like the reverse bell curve. Some of the highest adopters have been at Cisco either less than five years or more than 15. And it's that space in the middle, and I wasn't actually expecting to see that. It's that space in the middle where you have the confidence gap that kind of starts to come in. But you're right. If you're armed with knowing where it is, then there is something that you can actually do about it. But I have a theory about this, and I want to be very transparent; it's a theory. I think that what AI is revealing in some cases is where we have human middleware doing work, where we may have a system that is set up to compensate for the fact that you might have disaggregated systems that don't work together super-well. So, we have this AI middleware level. And part of me, and this is Kelly, this is not based on Cisco data, but my Kelly brain hypothesises, "Do you have people in that layer that are functioning as human middleware and might be aware of that?"
So, when you think about what AI is going to do, what full agentic does in the future, it's going to take care of so much of what they are doing that the confidence gap they have might not be just focused on, "Are the AI tools working?" but on, "What is the impact going to be to my job and my work and my role?"
[32:45] David Green: Yeah. And as you said, this was the second study that you've done on this, and obviously this is something you're going to be doing again and again, and you'll get different insights each time. But it really helps inform your approach, I guess, moving forward, which is so, so important. If HR at Cisco and people and communities at Cisco are going to kind of lead the AI transformation within the organisation, it's important that you do these types of studies, isn't it?
[33:12] Kelly Jones: Oh, yes, it absolutely is. And we've always had a pretty strong People Intelligence function. This is something that we invested in years ago. So, we use the work they do to kind of feed into what we design, because we don't design things in a vacuum. What we tried to say, and my philosophy on this is, we design with people, not for them. Because there is this tendency to say, "We're HR, we're here to help, we know all the things. Let us just figure this out for you". But you don't have human-centred design unless you know where the humans are in your change curve and what the humans are thinking. So, we've always had it. But one of the most exciting things to me in the HR future is the elevation of the People Intelligence function, and how that is going to fundamentally change to really drive strategy across all areas of the business. That, to me, is really exciting.
[33:58] David Green: And actually, a couple of ways we think of, we'll develop that a bit in a minute. But it's interesting, one of the things you mentioned about leading with humanity, courage. Now, I think, I had one of your peers on, Katarina Berg, who was at Spotify, now at On, and I've spoken with other people in your role in large organisations as well. And one of the consistent messages I get from Chief People Officers that actually have that ambition to turn what has historically being a support function into a strategic partner, is we need to be a bit more courageous as HR professionals and HR leaders as well. And actually, as you said, not just look in the rearview mirror and talk about what's happened, but we actually need to try to shape what's going to happen. And People Intelligence is absolutely key to helping us to do that, isn't it?
[34:46] Kelly Jones: I completely agree. And I think what's going to be important as we do this is that we don't lead with the message of, "We've transformed the function, we're here", but rather, "Do the work, show up credibly". The trust and the showing up credibly has a little bit to do with, "What did you predict that was right? Like, how have you shown up in this space in the past?" But I think it's more about how we show up and picking what are maybe one or two major problems that if you had better people data, you would have had a better outcome as an organisation, and start there when it comes to people analytics, "How might we have unpacked that in a different way?" and demonstrate it. I'm a big believer in credibility through demonstration. It's less about what we say about what we're doing, and more about what we are actually doing.
[35:29] David Green: Yeah. And actually, I always ask this on the podcast to someone in your role as a Chief People Officer, Kelly, how does the People Intelligence function at Cisco, how does it help you with your conversations with the CEO of Cisco and the board?
[35:44] Kelly Jones: Well, it brings credibility to what it is that we're bringing them. We're not bringing them a, "We think this might be happening". We can actually come with hard data and bring something that helps us secure funding for things, it helps us ensure that we are kind of holding the hole around the human side of the transformation. And I work for a technology company that I think has an incredibly responsible AI focus, we've been that way from the centre. At the same time, I don't think this should be designed by technologists, it has to be designed by people that are also focusing on the human impact. And so, when we come with data to that, it gives us more credibility to be able to do that. It gives us an understanding of where things might look different. Cisco, we've got 86,000 employees, we have really large functions. In some ways, our engineering functions work a little bit differently than our sales function. The human side of this is different. And if you've ever worked with engineers and worked with salespeople, you know what I mean. It might not be the same motivators, it might not be the same kind of data you need to give them to drive the right behaviour. So, People Intelligence allows us to kind of by function, but also understand some of the regional differences.
One of the other big problems I think businesses based in North America can make is assuming everybody functions like the US, and the world doesn't. It's different, depending on where you sit. So, they give us an ability to almost bifurcate this data in a way that allows us to make good decisions that are more pinpoint, based on what it is we're trying to do.
[37:17] David Green: Yeah, very good. And obviously, there's lots of talk at the moment, Kelly, about the HR operating model. We do love to look at the operating model as HR professionals, don't we? How are you finding the kind of workforce transformation and all the changes that are going on with the function? How are you finding these changes impacting the function and how it's seen by the wider organisation? And also, you've talked about the transition into an intelligent function. How's that kind of reshaping how you set HR up at Cisco?
[37:47] Kelly Jones: You know, it's interesting. I think that HR has actually been kind of holding this incorrect mental model about what we're here to do. I think we've historically been very good at designing jobs. If you think about job descriptions, job-levelling, job families, but that's just not the same as designing work. Those are just genuinely different things. And so, what we're talking a lot in the HR function is when you design work, you actually decompose what needs to happen. So, you're looking at the task level, the decision level, the judgment level. And you're asking, "Which of these needs a human presence? What can you automate? What should you just stop completely? What should we not be doing at all?" And one of the things we're talking about, I think across the enterprise, that's an underrated category, we really need to focus on what are the areas where we have an opportunity to ask what we should actually be doing. And for me, when you think about a people team or an HR team, that's where the business value actually is. It's not in the automation. Anybody can go out and put a bunch of automation around their processes, but it's in the intentional redesign of what humans do, and then what you do with that human capacity.
I'm finding that functions are at different stages in terms of what they want to do with their human capacity. But the organisations I think that are going to really win aren't the ones that just automate the most. And this is the conversation I have with a lot of HR leaders about what are the tools, what should we be looking at, what do we map first? How I think about this is the companies that are going to win are the ones that are very deliberate about the what, kind of what are the things they should point human judgment at. And remember that it's cultural, not just technical, because I feel like for each of our functions, if you can't see the work at that level of resolution, you can't redesign it. And so, we're working with each of our functions to redesign workflows. But before we do that, we have to really make sure that we understand it as a deep level. Because if we don't, we're just kind of automating what happened in the past. And I personally think that is an incredibly expensive way to stay in the same place, which I don't think anybody wants.
[39:52] David Green: No, you're right. And then, as we do kind of shift emphasis as a function, if you're building the people function for an intelligence era, what are the signs of different skills that you're maybe looking for in some of those roles that maybe we weren't looking for in the past?
[40:11] Kelly Jones: Yeah, this is a really interesting one. And I think my teams are asking this a lot, and a lot of HR conversation in the blogosphere is around this. And for me, I think it's a couple of things. And we've done some mapping around what does our function look like in a post-agentic era? So, we know some of the specific areas that we need to increase fluency, which includes the People Intelligence side, but also includes some other areas. And some of them are not surprising around AI orchestration in the concept of agent governance. The skill isn't knowing how to build an AI agent, it's kind of knowing when to trust it, when to override it. And this is where my optimism really kicks in around HR becoming kind of the judgement layer, not the processing layer, because it's a much more interesting job for those of us that do this.
But in the People Intelligence space, there's also this concept of organisational diagnostics. We need HR people who can actually read an organisation the way a really exceptional doctor might read a patient. So, rather than just looking at symptoms, they have to look at systems. So, anyone can look and see attrition is high. Having an evolved intelligence layer that is really focused on organisational diagnostics is going to tell you why and what the real intervention is, and probably tell you before you know you have a problem.
Another area that we're talking a lot about is this concept of workforce architecture and work design. When you think about AI changing what the humans are doing day-to-day, this is the zero-based workflow design that I was talking about. This is our opportunity right now to kind of decompose the roles, rebuild the task, figure out where the human judgment is irreplaceable, and I would actually argue this is kind of new territory for us as a profession. Some of the other things I would say, change navigation and influence. We've always been in an influence-without-authority space on people teams. At the same time, we're in a unique opportunity where we're going to have the data to be able to influence things in a much different way. And I'm seeing that the business actually needs us to help with change management. And when I say change management, I don't mean the traditional, "We're rolling out a programme, see, feel, think, do", all of those things, but navigating the change on a much more broad way. We need to do that much more broadly across the organisation.
Then, I think the other one is ethical reasoning and risk judgment. This is one that we're going to need more of this. I wouldn't say that's a role. I think that's a capability everyone needs. Then, probably the one I'm most excited about is this concept of foresight. Foresight and scenario-thinking in an intelligence layer with true automated agentic AI, again, it doesn't just tell you what's coming. It has to tell you what does it mean, how do we build scenarios, watching these leading indicators and kind of advising on decisions that might not play out for two or three years. And this is really interesting and exciting, because HR has got to get comfortable living in the future. And the throughline for all of this is the idea that we stop being a function that manages process well, and we start being the function that helps the organisation make better decisions about what I say is the most important asset that we have. And in many cases, I think it's going to be a completely different skillset than what we have right now on some of the HR teams.
[43:18] David Green: And again, I think listening to you there, Kelly, you've just given the perfect kind of synopsis of how you shift from being a process function to an intelligence function. All those skills and capabilities and mindsets that you talked about, they're fundamental if we're going to achieve that successfully. And then, linked to that, obviously again, as a people function, we've got to bring people with us, both within the function and obviously across the organisation. And I know you have a very well-honed approach to employee listening and employee wellbeing at Cisco. And clearly, it's a really important element of this. It doesn't always perhaps get the airtime it deserves. How are you thinking about that at Cisco, in terms of your employee-listening approach?
[44:02] Kelly Jones: I'm so glad you asked this question and I'm so glad you made that comment about wellbeing, because I think the conversation about wellbeing is happening in the wrong room sometimes. I think that people tend to see it as a thing that people do because they're nice and they think it's yoga and breathwork. It can be. Yoga and breathwork can be a part of it. But one of the things that we know from our employee listening and from all the connected data that we have is that wellbeing and high performance are directly tied. And so, the time that we spend investing in making sure our employees are well -- and I'm the executive sponsor for a programme that we have that is around our wellbeing ambassadors. So, we've got hundreds of Cisco employees around the globe. And it's one of those things where when we do that and we focus on that, we see a direct line to higher engagement, to higher performance. And when you have higher engagement and higher performance, you have higher customer satisfaction.
So, rather than having wellbeing in a conversation over here and performance in a conversation room over here, I think we need to be talking about them in a more connected way, because that's what our data tells us. So, the money we invest in the wellbeing of our employees, we see back in our revenue, it leads to better customer outcomes. And so, for me, I think the trap you can fall into in this is starting to feel like wellbeing is the thing that we do because we're nice. Cisco is a very nice company, but investments in wellbeing are not just about that. It's about making sure employees are well. It's good for the bottom line, it's good for our customers. And we know that because of the connected nature of the data that we get through People Intelligence. And it allows us to make a case for some of these things that we want to do in the wellbeing space, whether it's how we intentionally design a space, which is something we've been doing in our office in London. We have a new office that we launched, I think about eight months ago in London, that was focused on neurodiverse employees and how to build a space where everyone can thrive. But what we find in the wellbeing space is when you build a space like that for a specific population, everyone benefits.
That's how we're using some of our People Intelligence and listening data to ensure that we're making the case for what we want to do, but we're also sharing it with our people and giving them permission to do the things that develop their wellbeing, permission to rest, permission to get engaged in some of these programmes that we do.
[46:10] David Green: It's really interesting. I've had a quite a few guests on the show over the last sort of year, 18 months, both Chief People Officers like you saying exactly the same thing, "Our data tells us that wellbeing and performance are connected. Those that have, or report higher employee wellbeing also perform better, etc, and it has a direct impact on the business"; and I've also had academics on. We had Jan-Emmanuel De Neve, who runs the wellbeing centre at Oxford University, and I think he's involved in the World Happiness Index. And again, exactly the same thing. There's more and more academic and practice studies that tell us that this is the case. So, why is it, and I'm talking generally here, I'm not talking about Cisco, why is it that so many CEOs don't fully understand this connection between wellbeing and performance? Is that down on us a little bit on not telling the story well enough?
[47:05] Kelly Jones: It probably is. And I'm fortunate because I think about our culture and how it's changed since Chuck came into the role, and I think I have a CEO who sees that. But I do have a lot of C-level friends and acquaintances. And I think it's a little bit about how we tell the story, because if we don't show up with the data, it just feels like HR is here with a touchy-feely thing. And showing up with data matters. You have to show up with the data. I also think that the C-level executives I know, if we're just being very honest, don't model the best wellbeing. And so, they live in a world that's a little bit different. CEOs work pretty continuously. There are days off, but there are not really days off. And so, I think when you are at that level and you've been performing at that level for a while, we like for them to model good wellbeing, but the reality is most of them are at work all of the time, 24/7. And so, it might be difficult, and this is a Kelly opinion, it might be difficult for them to bifurcate that a little bit, because their reality, and oftentimes the reality of their direct team, is that. They're living in a constant state of on.
So, when we go and we try to explain that we need to build in this time for rest and ensuring that we have the tools and we're giving our employees permission to rest, they might not be resting themselves. And so, it's a little bit difficult, I think, for them to kind of cognitively connect with that. And that's the conversations I've been having externally with a lot of C-level executives, CIOs, CTOs, even Chief People Officers, where the reality is you want to model the right wellbeing, but you are oftentimes never really off. So, I think there's a disconnection from how it actually plays out in the rest of the company.
[48:53] David Green: Yeah, that's a really good point actually, I think on that, that actually, generally, the higher you get up in an organisation, maybe you're not any less concerned about your wellbeing, but you're always on. I've got two more questions, Kelly. The first one is just for the HR leader or HR professional listening to this who's already embarking on their AI workforce transformation, they're listening to you thinking, "We need to do something like that at our organisation", where would you suggest they begin?
[49:24] Kelly Jones: The first thing I would say is do not start with the technology, it's a trap. It is a trap to start with the technology. Because oftentimes, that's what I hear when I do calls with people sometimes, "What tools, which platforms are working?" Those are real decisions and we have to make them, but they're a downstream of the fundamental question, which is what are the problems you're actually trying to solve for the business? What are the problems you're trying to solve? Because an intelligence layer isn't a technology investment, it's a repositioning of what is your function for? Who are you in the world? And if you haven't answered that question clearly, it's just going to be a bunch of expensive tools that are automating the wrong thing. So, the first thing I would be thinking about is, what are the decisions? What are some of the decisions that the business might make regularly, where having better people intelligence would have changed the outcome? So, start there and kind of work backwards from the decisions, not forward from the capabilities, which by the way, it's tempting. I've sat through many a demo where you see the capabilities and you can go, "Wow, this will be great". You have to work backwards from what it is you're actually trying to do.
The second thing, and I think this one is a little bit uncomfortable, you kind of have to be honest about your team. Because the skillset that might have made some great HR business partners in a service model might not automatically be the skillset that make them effective in an intelligence layer. Now, you're asking people to move from answering questions and supporting to forming a hypothesis; and from maybe executing a process to designing a system. And that's a real gap. And I think if we pretend it isn't there, the transformation is going to fail. And then, I think the last one, and this one I feel really strongly about, you have to redesign the work before you redesign the function. If your HR or people team is still spending 60% of their time on transactional work, you're never going to be able to layer intelligence capability on top of that. The capacity doesn't exist. So, there's this sequencing question, what do you automate? What do you eliminate? What might leaders be able to do much more efficiently in the system that you have? And how do you free up the human bandwidth?
This comes back to something I was saying around credibility. The intelligence layer only works if the business trusts the intelligence. We build that trust through time with a track record about being right about the things that really mattered. You pick two or three high-stake business questions, you bring a level of workforce insight, and then you let that do the talking. The repositioning in this for HR to becoming this intelligence layer is real. But again, I think it's going to happen through proof points, not through a big HR rebrand.
[51:51] David Green: Kelly, we've got to the last question. This is a question we're asking everyone on this series of the podcast. And I think it almost could have been designed for you, because we've talked a little bit about this. How should HR redesign work to unlock business value?
[52:05] Kelly Jones: I think it comes down to decomposing what actually needs to happen in the work, and you've got to start there. And this, by the way, HR is not really set up to do this. This is going to be a real intentional focus around what are the tasks? What are the judgments? What are the decisions? Where is human presence? What should be automated? You really have to start there. You have to start at moving away from the concept that we manage jobs to moving to the concept that we manage work. And those are very different things. But that is also where the real business value is going to exist. It's going to exist in us being able to do that. We have to see the work at that level to be able to redesign it. If we can't see the work at that level, we can't redesign it.
[52:52] David Green: Kelly, it's been absolutely wonderful to talk to you today. Thanks for taking the time to share the work that you're doing at Cisco with our listeners. Before I let you go, can you let our listeners know how they can find out more, either by connecting with you, presumably on LinkedIn, and how they can find out more about the work that you're doing at Cisco?
[53:13] Kelly Jones: Yeah, so there's two things. Feel free to follow me on LinkedIn. I actually share a lot out there on a range of topics, from industry trends to kind of current events. We share a lot about what Cisco is up to, not necessarily to hear myself talk, but to get conversations started, because we don't know everything. We're all in this area where we're experimenting. And so, for me, I use that as a platform a lot to share what we've learned, if others can find some interesting benefit in it, but also to understand what others are doing, and to challenge my thinking a little bit in ways I should be thinking about this. There's some really interesting conversations happening on LinkedIn. But I'd also say you can check out Cisco's AI workforce findings. That's on blogs.cisco.com. That's the full picture of our employee learning and AI adoption, we have both studies out there. We have a lot out there actually around what we're learning with regards to AI. So, those two things, I would say.
[53:59] David Green: Yeah, and thank you for sharing that. In fact, when you shared the findings of this particular study on LinkedIn, that's how I got to contact your team and set up this conversation. So, thanks for doing that.
[54:09] Kelly Jones: Oh, fantastic!
[54:10] David Green: It's so important that companies like Cisco are sharing some of the findings that you're getting, because it helps the rest of the field to move forward as well.
[54:18] Kelly Jones: Well, thank you, David. I so appreciate you having me on. I enjoyed the conversation. Thank you.
[54:24] David Green: Kelly, thank you again so much for coming on the show and for being so transparent about what this important research is really telling us. Turning to our listeners, thank you for tuning in. I'd love to hear your take on this. Head over to LinkedIn, find my post about this episode, and let me know in the comments. I read every single one and honestly, the conversations that happen there often build on the one we have on the show. And if you enjoyed this episode, please do share it with a colleague who gets something out of it. And if you haven't already, hit subscribe so you don't miss what's coming next.
One last thing before we go. For those who would like to keep up with what we're working on at Insight222, follow us on LinkedIn, or head to insight222.com. You can also sign up for our bi-weekly newsletter at myHRfuture.com to get the latest thinking on HR, people analytics, workforce transformation, and everything shaping our field. Right, that's us for today. Thanks for listening. We'll be back next week with another episode of the Digital HR Leaders podcast. Until then, take care and stay well.