We’re in the nascent stages of imagining what we can accomplish with AI, but there appears to be almost unlimited potential if its power is responsibly and thoughtfully harnessed by organizations to benefit employees.
Welcome to the “disrupted, boundaryless age,” one in which the challenges are great, but the opportunities are greater.
Join leaders from Deloitte and Eightfold as we discuss their 2024 Global Human Capital Trends report. In this webinar, we’ll focus on two of Deloitte’s biggest human capital trends — the imagination deficit and boundaryless HR.
Join us to hear about Deloitte’s trends and hear more about how it will impact HR.
Jason Cerrato and Sue Cantrell discussed the evolving nature of work and its challenges for HR leaders, and explored the need to rethink HR’s role in the modern workplace. They emphasized the importance of bridging the gap between knowing and doing to drive both business and human outcomes, and highlighted the role of talent intelligence and skills-based organizations in understanding how skills are changing. Sue Cantrell also discussed the transformative impact of emerging technologies, particularly generative AI, on the workforce, and the need for organizations to adapt by embracing micro cultures and rethinking traditional approaches to HR. Jason highlighted the potential drawbacks of relying solely on technology for career guidance and emphasized the need for ongoing discussions and coaching.
Jason Cerrato 0:09
So great to be here. And thank you everyone for joining us. I’ve been really looking forward to this session. As mentioned, my name is Jason Cerrato. I’m the Vice President of market strategy for Eightfold. I’ve been in the HR and HR tech space for over 20 years in a variety of roles. I’ve been a former talent executive, I’ve been a former industry analyst. I’ve been a former eightfold customer and now have joined the eightfold team leading market strategy. So I love the topic of talent, technology and the future of work. So I’ve really been looking forward to this session and I’m so excited to talk about the 2024 Deloitte human capital Trends report with the sukin trail. As I’ve been reading through this year’s report, there are so many intriguing topics that are very much aligned with what we are working on here at Eightfold. And as I’ve been traveling around the country, taking part in conferences and executive roundtables, I think there are a ton of findings in the research that are top of mind for HR leaders and the attendees joining us for today. So without further ado, I’d like to introduce Sue Cantrell from Deloitte and welcome, Sue.
Sue Cantrell 1:17
Thanks so much, Jason, thrilled to be here. And yes, a quick introduction to myself, I lead thought leadership, which is what we call eminence at Deloitte. So I have 25 years of experience in workforce and talent consulting, I was actually one of the primary lead authors on this year’s human capital Trends report produced by Deloitte and has a long history, we’ve been doing it for a number of years, it’s one of the longest longitudinal research studies in our space of talent and workforce, human capital area. So thrilled to talk to you about this year’s report and some of our research findings.
Jason Cerrato 2:01
I have several of the previous years saved on my desktop and refer to them often throughout the year. So excited to look at this year’s report. So
Sue Cantrell 2:09
good to hear Jason. So this year’s report, we call thriving beyond boundaries, human performance, and a boundary list world and we hope this will kind of come to life for you as we walk through the content today, and I’m going to start with this idea of boundary lists. We actually introduced this concept last year. And when we think about it, the world of work is becoming increasingly bounded, this right work is no longer defined solely by jobs, the workplace is no longer a specific place. Many workers are no longer traditional employees. And this has just accelerated over the past year, as Gen AI has really come on to the scene and in an incredible way. So as we dug into the research into how work is becoming boundaryless, it became clear through the research that the human element is increasingly important. And this threat of human performance kind of runs throughout all of our trends this year. But the issue is that the old thinking and kind of traditional mindsets, and what we call proxies are getting in the way of unlocking human performance and proxy service, kind of imperfect placeholders for which should truly be measured. They were put in place for a simpler world, right. So when you think about it, we have some proxies here on our page, the notion of the employee, you know, that used to capture the singular notion of full time staff who are workers were but today we have a full ecosystem of workers that create value for our organization, contractors, workers from our partners, even AI as a worker, right, the job, we tend to think of that as equated with work, it documents a set of repeatable functional tasks. But it really doesn’t account for all the dynamism of work today. And sometimes, based on our research, work is often performed outside of traditional job boundaries, as we see eightfold is enabling as an example, this notion of culture there on the left, you know, we tend to think of culture as a monolithic one size fits all corporate culture as the way organizations should operate. But increasingly, in this world where agility is valued more than stability, organizations are made up of an abundance of micro cultures. It’s one of our trends. And we see that as a positive thing. Employee engagement, right? That is typically used to evaluate the relationship between organizations and workers. But maybe what we should be measuring is trust. Because when we think about engagement, it measures how much Discretionary Effort workers are willing to expend for their organization’s benefit. But whether or not it helps workers is a little bit less clear. Productivity, right? We measure worker activity. Have a revenue per employee activity, how many hours you’re working, but that doesn’t fully account for outcomes, right the business outcomes and the human outcomes that you want to drive. So we think these proxies of the past are kind of holding us back to creating new value in a boundary list world a little bit about our research that went into our trends. This year, we had 14,000 respondents. This year, we did something a little differently. We surveyed both workers and executives separately to really get at the perceptions and the differences among 95 countries across all different regions and industries. So quite a substantial research study. And again, what we found was that that human factor is the key to making real progress. So one of the most interesting things we found in our study is what we call the knowing versus doing gap. So what we found is to make progress and knowing isn’t the barrier, right. So here on the slide, you can see 74% of respondents said they knew this year’s trends were really important, very critically important. Where they get stuck is in the doing, right, making real actionable, tangible progress to unlocking human performance. So only 10% of respondents said they believe they’re accomplishing great things to address these issues that the trends uncover. So those who were able to bridge this gap between knowing and doing are more likely to produce better business and human outcomes. And really, what we focused on throughout all the trends is how do you make that difference? What do tangibly speaking, to do the trends, and one of them is unlocking those proxies of the past. So I told you in the beginning, human performance kind of runs through with a major theme throughout all of our trends. What do we mean when we say this? The idea here is that typically, in the past, you would see a focus on business outcomes, or human outcomes usually prioritized separately, usually business outcomes more than human outcomes. But the big difference here is that multiplication sign instead of the or so we define it as human outcomes times business outcomes equals human performance, they’re mutually reinforcing cycles, right? So when I say human outcomes, I mean things like better well being opportunities for development and advancement, skill development, and employability, finding meaning and work, equity, all of those things that create value for humans as human beings. Business outcomes are the usual suspects. But what we found is that this is no longer optional to treat them separately. Because both together drive performance, we need to drive business and human outcomes together. And it’s that multiplier effect that propels us. You can see here at the bottom of the slide, that we also did some research that those that bridge the gap between knowing and doing are far more likely to drive both business outcomes and human outcomes. And I’m going to turn it over to Jason and see, I think that this notion of human performance really resonates with what eightfold does, and many of its solutions. Yeah,
Jason Cerrato 8:38
I mean, it’s very intriguing and mirrors a lot of the work that we’re doing, because a lot of organizations are looking at tools like talent intelligence, especially aligned with the conversations around becoming a skills based organization. But what does a skills based organization mean? It means starting to look at this shift from organizing around the job to kind of balancing the view to putting an increased emphasis around the talent. And if you can click forward, so you’ll see, we’ve done a lot of work historically, around organizing with skills mapped to jobs. And yes, you need that for how you organize and you report and how you audit. But increasingly in today’s world, as we start to decouple how work gets done and how work is organized. And especially with the rapid pace of transformation with things like generative AI, work is increasingly transforming. And you need to use tools like AI to understand how skills are changing and evolving. So tools like talent, intelligence, and especially a platform like eightfold are helping organizations map skills to people in the context of work, that then can inform how those skills are updating and being mapped to jobs. And for us, we feel you kind of need both of these tools working together in a complementary nature to see the full picture, right. And if you think about it, when you put job titles and job descriptions together, they’ve always been a reflection or Oh, or a summary of skills, right. But that’s always been somewhat of a lagging measure. And when you’re looking at talent profiles, and the work that people are doing in real time, that is more of a leading measure. But in today’s world, especially with all of the new skills that are emerging, and how our work is changing so rapidly, that lag is getting broader, faster. So the use of AI and skills and talent intelligence is helping organizations keep pace with understanding the world around them in real time, to then kind of embrace this chaos of how do I plan for tomorrow while still operating for today. So when you talk about building the future of work in this increasingly boundary lists world, it very, very much resonated with me and was somewhat music to my ears, because it’s the work that we’re doing every day in helping organizations prepare for how to manage and operate and think differently, because a lot of these constructs and fence posts that we’ve used to organize around, are becoming increasingly less reliable, as the world of work is moving faster, and things are starting to decouple. So that’s why I was looking forward to having the session and talking with you. And when I saw the research get published, I quickly downloaded a copy and started reading through it. Because it resonated with me, because it aligns very much with a lot of the work that we’re doing. If you could advance to the next slide. I also think it speaks to a lot of how our tool is built. So you talked about this mutually beneficial relationship of benefiting the employee and the organization at the same time. And there’s this hot discussion of talent intelligence in the HR space, and in the HR technology world. And what does it mean, and what does it do? And one of the phrases that often comes up is, talent, intelligence is often seen as a win win for the participants in an organization. And that’s because what it helps is it helps this understanding of talent in the context of work. But it also helps for the users, whether it be an applicant, a candidate and employee, a manager and HR partner, but it also helps the organization, the enterprise, the leaders, the talent planners, and the people kind of looking down on the data in the organization. And in our system, the way each folder organizes this is we have three elements of data, we look at the enterprise data, we incorporate market data and public information, but then also user interactions from people operating on the platform. And we take those three elements of learning, and feed that into our deep learning AI engine. And on the other side of that, you have benefits for how this provides intelligence for the individual, whether it be aI matching for an improved candidate experience or career development with career pathing and guidance, or upskilling, or mentor matching, but also organizational intelligence around career pathing or skills based planning or talent marketplaces, or succession planning that gets deeper in the organization and isn’t just for the top 200 or, you know, managers and above. So, this really becomes this dynamic, continuously learning type of approach that is learning in the context of work in real time preparing for the future. So as I was looking over the report and talking about some and learning about some of these trends, it was really exciting to see how this aligns with a lot of what we’re working on. And a lot of what some of the customers using eightfold are benefiting from
Sue Cantrell 14:21
great examples, Jason of both bikes boundaryless in play in real time, and this dynamism of work, right. And that notion of human performance of, you know, individual intelligence, organizational intelligence, working together to create outcomes for both people and for business. Thank you. So I thought I’d do a quick overview of this year’s Deloitte, human capital trends, and then we’re going to zero in on a couple for today. So introducing our trends here. Our first trend is set over to the left. It’s called humans. Sustainability because it’s one of the trends that zeroes in on that human outcomes lens. It really sets the stage for one of our anchor trends for human performance. So what do we mean by human sustainability? Basically, it’s the ability to create value for people that an organization interacts with or touches as human beings. And that’s very different from the value for people as employees or as workers, right. So some examples would be leaving them with greater health and well being as a result of your interactions. You know, something eightfold does very well, leaving them with stronger skills, helping them learn helping them develop, which can lead to better, you know, good jobs, better employability, keeping on top of all of those fast moving skill changes, opportunities for advancement, progress toward equity, increased belonging heightened sense, a heightened sense of purpose and ability to have meaning. So human sustainability really delves into this trend of, we need to put those human outcomes in that multiplier effect, so that we can multiply our business outcomes. And it really shines a light on kind of the s part of ESG, if you will, and makes it really actionable. Our next trend is called Beyond Productivity. And really, this explores the fact that we probably need new metrics beyond traditional productivity metrics. I mean, when you think about it, they’ve been around since the dawn of the Industrial Revolution, right for a mechanized world mass production. And our world, as Jason was talking about, is so much more dynamic and fluid and agile than that today. And we don’t necessarily compete on scalable efficiency anymore, either, right? So what kind of new metrics can we have to measure those business and human outcomes. And as Jason was alluding to what kinds of new sources of data and intelligence can we have, that AI can help us to make this shift of measuring outcomes, rather than those activities, which are typically around productivity. Our next trend, and I am going to dive into this a little bit is called the transparency paradox. And this really highlights the fact that with all of this emerging technology, nearly everything in the world is transparent today. And because of this kind of new advances and transparency, it might not actually build trust, because the common assumption is that the greater transparency, the greater trust is a much more complex relationship now, now that nearly everything can be made transparent. So we’ll delve into that in a little bit. We’re also going to talk about imagination deficit and digital playground today. These are really about how new digital advances like generative AI are exposing an imagination deficit, what we call and how operationalizing human capabilities and providing workers with what we call Safe digital playgrounds, to practice those human capabilities can help solve that deficit. We’ll go into that in a little bit more in depth, workplace, Mike work, place micro cultures. This is delving into what I talked about earlier about that proxy of a single monolithic culture, what we’re finding is that organizations that embrace micro cultures that are still aligned to organization-wide values, that’s important. But there’s a nuance between the, you know, the ways you work that can create better agility, autonomy, better workforce experience. We’re also going to talk a little bit about boundary list HR today. How is HR evolving to support human performance, and we really see it moving from kind of a specialized, often siloed function to a boundary list discipline that’s really co created with the people and business and communities it serves. And then we will talk about leadership implications for the C suite for the board around how you move to action and bridge that knowing versus doing gap. So I really encourage you to read this year’s trends. And today, we’re going to focus on just a few of these four of them. And we’re also going to talk a little bit about how you know Jason is seeing these come to life in Eightfold solutions. Before we go into the trends I wanted to talk a little bit about Gen AI. So we made a conscious decision that Gen AI is so important. You can see its impact here. It is a deep impact across so many different domains that we really threaded this notion of how Gen AI is changing things throughout all of our trends, rather than zeroing it on a specific trend, it should come as no surprise to you on this slide, you see, nearly everyone is exploring it now, many are increasing their AI investments. And what’s the impact? Well, of course, we know massive transformation of the work we do across all types of workers, right? It’s, you know, knowledge workers in particular, many of our tasks will be able to be automated by generative AI and its tasks, not jobs, big distinction there. You know, generative AI can help us do the work we do better and faster, and with the ability to improve human performance. So some studies have shown that Gen AI improves a highly skilled worker’s performance by up to 40% compared to those who don’t use it. But we need to think about how we’re measuring performance. Is it speed? Is it moving the dial on those outcomes we’re talking about? Obviously, skills are rapidly changing. As a result, we’ll talk about the need for human capabilities. When we speak of the imagination deficit, there are lots of risks involved. Can we trust it? Is it hallucinating, has risks of inequalities. And then early career development, you know, workers who are less skilled stand to gain a lot from generative AI and help them to quickly develop skills. But some research on the other hand is showing that AI is eliminating some of those entry level roles. So we need that kind of early career development. Different way of doing it, Jason, any comments on what you’re seeing with gender,
Jason Cerrato 21:37
That last one is one that I’m extremely interested in. We’ve heard about disruption in the LMS and training market in terms of technology and the importance in organizations trying to understand new ways to approach this. And I think part of this is because a lot of the on the job training that organizations used to rely on those, those positions are getting fewer and far between, but also a lot of the tasks that people used to be able to do to kind of learn in the moment on the job, or the tasks that are increasingly being automated, right? So we need to get creative, and figure out new ways to coach and train and teach people to ramp them up into what those new roles of the future are. Because in many cases, the entry point for where people will be joining the workforce is much more advanced than it may have been before.
Sue Cantrell 22:28
absolutely could not agree more. Okay, I’m speaking about generative AI. Our first trend is what we’re calling the transparency paradox. And when you think about this, you know generative AI large language models, they can analyze vast amounts of text data, right, like employee emails, surveys, social media, and they can uncover hidden patterns and sentiment trends beyond, you know, traditional statistical methods can detect and Gen AI can draw from internal and external data sources to create personalized learning and development plans, for example, basically, it’s not just Gen AI, but all different kinds of technology is smart sensors in the environment, the ability to track people’s, you know, digital work as they work. It’s making the ability for nearly everything to become transparent, right. So what this is causing is what we’re calling a transparency paradox. And really, the thinking here is that increasingly, or the common assumption is that transparency is commonly thought to drive trust, right, so you can see here on the right 86% of leaders say that the more transparent the organization is the greater workforce trust. But the issue here is that that assumption no longer holds true in a world when new technology developments can make so much transparent, right? So you can see here on the left, that there’s an average of 400 sources organizations use to collect data today, and Gen AI can help us synthesize and make sense of that data. Transparency has changed, right? So today, we can see how and where workers are working. We can see organizational experiences through social media posts, we can analyze worker data from collaboration platforms, or email. So many leaders are finding this type of transparency is alluring. But it can be both a goldmine opening all kinds of insights, but also a landmine in that the flip side of transparency is privacy. Right? So we need to be able to get this balance between transparency and privacy. Right. And so in our report, we really talk through what are some of the principles that You should use to think through when something should be made transparent versus when something should be made private. What do you share? So we’ve talked about being able to look at what will be made transparent, you know, leadership priorities and goals. That’s traditionally been what we think of transparency. Absolutely, that will drive workforce trust, we have lots of research to back that up. But, you know, research shows that details about creative processes might not drive the trust that you want. Why is it being made transparent, this is particularly important. If it’s to create better outcomes for workers, then that’s probably a go. But if it is used for surveillance, or has any kind of punitive consequences, like used in performance management, or the like, then we tend to not want to make everything transparent. A good example of this is on the right. There’s a British multinational retail distribution center. And they basically had cameras in the distribution center. And then they had aI track the movement of workers on the floor, in relationship with equipment, and it identified unsafe events. And that resulted in 80% reduction in safety incidents in the first three months. That was done with the why of creating better outcomes for workers. And it had nothing to do with surveillance, you know, we have all kinds of principles for responsibility, like opt in, let people decide if they want their data to be transparent. Some data is more sensitive than others. Right? So data on people’s emotions is much more sensitive than data on people’s skills as an example. So anything you want to comment on? Jason?
Jason Cerrato 26:47
Yeah, this is good. This has been a hot topic of discussion. And a lot of the roundtables and conferences I’ve been attending. And part of the concern is what happens when people have so much information at their fingertips. And let’s take what could be somewhat said, for example, closer to home, in the talent space, right? So personalized career guidance, right? What happens when people can see where they can go in an organization, and now that they can see where they can go? What happens when they’re just not getting there? Right. And this is of concern for some talent leaders and some managers. And, you know, part of this is, you know, the technology doesn’t replace the human element of the management discussions, it doesn’t replace the element of human performance. And this is what’s so important around training and leadership coaching, right? There’s the value of the visualization of the possibility through data. But on the other side, there still is execution in real life, right. And there’s meant to be discussions that still need to be occurring along the way. So this is the balance of the capability of technology, but then the role of people and you know, leadership, and the organization and culture, working together. So when you talk about human performance and business outcomes, and creating this culture of working together, and part of this, you know, aligns with this concept of the transparency paradox, right? What happens when you have so much information? How could it potentially be turned into a negative? You need to train managers and have conversations and be able to have discussions where you can turn it into a positive?
Sue Cantrell 28:27
Absolutely, absolutely, that that human element is so important in making decisions, right? It can’t just be the data or the AI? Thank you, Jason. I’m speaking about AI. Again, imagination deficit. Basically, here, we’re talking about how new digital advances like generative AI are exposing the need for and the lack of things like imagination, curiosity, empathy, what we call human capabilities. So when you think about it, for example, with generative AI, we need to be able to ask the right questions, right? That requires imagination, right. And as Jason alluded to earlier, when so much of our work, some of our easier tasks are automated, what’s left over, right? AI is becoming increasingly better at replicating the functional and technical aspects of work. So much of the differentiation going forward is going to come from what humans do or evolve to do, not just the technology, right, and that’s putting this premium on imagination, curiosity, empathy, human capabilities. And you know, and we also need to be able to have imagination to reimagine our work in the future due to new technical advances. It’s changing rapidly, right? So we asked workers and 76% of workers say it’s important for their organization to help them imagine how their job might change in the future as a result, for example of new technologies and using generative AI, but only 43% of organizations are helping workers imagine how their jobs may change. So we need to cultivate that ability for workers to kind of create what is going to be my new role, what is going to be the new work, we know, rather than a top down kind of work that is too dynamic today. And we need to do this together. And for workers to be able to do that. They need imagination. So 70% 71% of organizations said their organization’s plans for generative AI include using it to advance those human capabilities, which I found to be really interesting, right? When you think about it, generative AI can improve creativity, if used the right way, right. So that will help close some of the gap. What we need to do is operationalize human capabilities. And our workforce functions haven’t necessarily quite figured that out yet. One of the problems is being able to measure human capabilities, right? So only 48% of organizations that we surveyed are confident that they have verified and valid information on their workers human capabilities, it’s harder to measure that and document it than our technical or hard skills, right. And then, somewhat alarming is only 10% of organizations say their current workforce possesses those high priority human capabilities that are needed. So there’s a real gap here, that we need to broach that knowing doing versus doing gaps. So we have an example here of one organization that’s trying to do this IKEA, it I mean, IDEO intentionally tries to hire for, you know, human capabilities. So it practices what it calls hiring T shaped employees, people with human capabilities, like creativity, and that’s the vertical stroke of the T. And then also a willingness to collaborate across disciplines. That’s a horizontal stroke of the T. So T shaped candidates are more likely to ask questions not directly related to the role that they’re interviewing for, they tend to talk about how past successes have involved collaboration rather than focusing exclusively on themselves. So it’s just one example of how one organization is trying to, you know, really operationalize those human capabilities in, in, in in its hiring practice. So what do we do about this? Yeah, go ahead, Jason. Well,
Jason Cerrato 32:36
so just going back to that comment around kind of T shaped candidates and T shaped opportunities. One of the debates that’s been going on for the last few years for a while now is, you know, with the impact of AI and generative AI and what jobs will be replaced, but also what jobs will be created. And one of the things about skills and a skills based approach and talent, intelligence and understanding kind of skills in the context of work is one of the capabilities is that increasingly, the jobs that will be created will be jobs that didn’t exist before that sit between functions. Yeah. That increasingly will be specialized hybrid roles. That may be a combination of operations, finance, and legal or engineering and legal and, you know, some other function. And this ability to understand how skills overlap or how skills are adjacent, but also to have this kind of ability for this T shaped careers and T shaped thinking will be the jobs of the future. So part of this is we did a research study back when I was an industry analyst. And we were looking at the competitive nature of talent acquisition and the rise of skills. And one of the things that we looked at was, skills are increasingly being added to job descriptions. And one of the things that we saw was year over year, there was a significant increase in the number of skills being listed in job descriptions. But as we were tracking the skills that were being added, they often were the skills that were declining, and not the skills that were emerging, because people were looking at how the work had been done, and not able to accurately predict or plan for how the work was going to be done in the future. Right. So they were hiring for, well, how have we done this and they were listening skills. And when you looked at the skills, they were skills that were not likely to be needed two or three years down the road. Right. So part of this is we’re partnering with organizations that are using skills intelligence to start to foster and develop the kinds of portfolios and audiences of talent to say we’re not sure exactly what the roles of the future are yet. But we know we want to pay attention to and develop and nurture people with these skills. And as we start to understand who these people are, and what skills we want to pay attention to, that are emerging in our organizations, we can now you know, keep an eye on them as as these roles start to surface, right, because, you know, the world of work is changing so fast, and organizations are pivoting into new industries and new technologies are being created. This is some of the impact of what AI is surfacing, but also how, you know, the nature of work is changing. Absolutely
Sue Cantrell 35:43
what you know, we call these enduring human capabilities like imagination, and the ability to quickly learn because those are what’s going to endure, right. But the specific technical skills are going to be changing all the time. And so we need to be able to have those kind of foundational human capabilities, to be able to, to be able to be much more adaptive, love, that notion of kind of hybrid roles sitting between functions, we’re seeing that as well, it relates to our trend we’re going to talk about and boundaryless HR and a little bit. So to close off on this imagination deficit, just a couple action points, you know, a Jason and I were both talking about kind of how you operationalize this as part of your strategy, talent, intelligence can help with this, you know, highlight for workers, teams, and managers, just the need to prioritize them, you know, reward for them, measuring them can help provide opportunities and venues for workers to explore, experiment, disrupt, co create, that, you know, helps helps them practice imagination, we have one quick example of IKEA here on the right, which basically, they, you know, like many organizations, you know, put AI in their call center to help be able to answer calls. But what they did then was they shifted those call center roles, to focus on creativity, and human connection, what they did was they turned them into interior design advisors, right, so much more complex value added service, probably likely one of those hybrid roles you were talking about Jason is my guess, you know, and then they they provided upskilling, to improve those kinds of human capabilities and technical skills needed for it. And that led to an increase in sales. And, that was the business outcome. But it also developed, you know, the skills and meaning for their workers, which was human outcomes.
Jason Cerrato 37:50
You know, and as you as you and I were meeting to prepare for this, we were talking, I love many of you out there may have seen there’s a video that’s been around for a couple of years now that shows how software, aid hardware, and all the things that used to be on your desk that are now on your phone, right, your calendar disappeared, your calculator disappeared, your planner disappeared, it’s now all an app on your phone. Well, what’s happening now is AI is eating software. Right? So if all of this is coming off your plate, and it’s no longer something that you have to do as part of your work, you know, the way we communicate and interact are amplified. Right? If the administration and the transactions are removed, via AI, it amplifies the importance of the human element. So that’s where imagination and creativity come into play. And also, you know, if we are now increasingly all becoming prompt engineers, for our own AI, virtual assistants, we need to be creative communicators for how we diagnose direct and define scenario scenarios and problems. Right. So for you know, we’ve always been talking about soft skills. Will increasingly soft skills become power skills, right? So is this imagination deficit something that’s a muscle people have to build?
Sue Cantrell 39:09
Absolutely. It’s the muscle. Yep. And one way to build it is what we call a digital playground, which is kind of a fun term. Basically, what we mean by this is like a safe place that is digitally enabled to let workers experiment and play and try new things. And learn how to ask those questions of generative AI. So you think about things like being able to have generative AI sandboxes for example, let’s let workers experiment figure it out. Try, you know, in a low stakes environment, it includes things like digital twins, so we know that we’ve had digital twins in physical spaces for a long time. And then we can kind of play and optimize a scenario model. If we change this, then what will happen, but we’re seeing the emergence of digital twins of the workforce as well, where we have an understanding of some of the workforce elements. And then we can play an experiment scenario model. With digital twins of the workforce, it includes virtual reality, it includes advanced analytics, basically, it’s a safe space for workers to practice those human capabilities, practice the use of new technologies, in a safe, low risk environment. So one of the reasons why we advocate this is because as we know, you know, Jason alluded to this earlier, there’s a lot of fear and some anxiety about, you know, AI, taking over some of our tasks, changing our roles. You know, 75% of organizations intend to accelerate their use of AI over the next five years. But we need to be able to help people, you know, learn how to adapt, right, and so it’s, it’s a time of disruption, it’s a time of possibility. And so we need to be able to help workers have that imagination to figure out how to adapt and use AI using these new digital tools. It’s a way of helping close that gap here that’s on the slide of the fact that only 13% of workers have been offered AI related skills training in the past year, right, there’s a big disconnect. We’re, we’re moving into AI, we’re not offering training, let’s give them a chance to just get in there and try it. The best learning sometimes is by doing. So we suggest digital playgrounds as a way to do this. So one of the some of the actions we suggest for digital playgrounds, democratize access to new digital technologies, to let people play, encourage play, let them play around with it. I mean, the best examples are generative AI sandboxes. I don’t know about you, Jason. But I’ve been playing. I have some learning curves to go out. But you can’t do it unless you’re actually trying to figure it out and learn by doing, connecting, and playing to work. Think about what problem sets are relevant to the organization and where engagement with the playground can be designed into daily work. You know, use digital playgrounds to co create, what are your new roles going to be? What are your new tasks going to be, you know, figure out use them as a way to co create with workers, what work will be in the future. One of the examples we have here on the right is of a digital twin. The Vancouver Airport Authority basically created a real time live, interactive representation of its airport. And they did this with the express notion of being able to have people experiment in it. So it’s a mix of virtual space with data collected real time from sensors from the internet of things. And then data is used to inform daily decision making and collaboration. So it has multiple uses, for example, it supports worker training, right. And it supports testing of new methods. It has data about passenger demand that helps staff forecast wait times and identify potential processing issues. And that allows workers to better provide service to passengers. So it has all these uses. Its democratized workers can get in there and play with it.
Jason Cerrato 43:38
In my, in my human resource development days, which were pre digital and pre AI, this was referred to as trying to create learning laboratories, digital playgrounds sound much cooler. And thinking about, you know, this kind of job centric to talent centric approach. You know, we’ve been thinking about employee experience, you know, for the longest time, and what I’ve been saying is using talent, intelligence and skills, we’re trying to get an understanding of talent through a deeper lens. And from an employee experience perspective, we’ve often been focused on experience at work, right doing employee engagement surveys and trying to get at sentiment. And now from a skills perspective, we’re trying to look at experience from work, right? Am I developing skills that are meaningful to me? Does the organization know what skills I have to offer? Do I understand how my skills aligned to where the business is heading? And how can I contribute? And then there’s also a key component: what is my experience with work? Right? What digital tools do I have to work with? Do they allow me to do my job efficiently? Or am I toggling back and forth? And does this create inefficiency? So all of this is creating a whole new world in which we’re gonna get our jobs done going forward?
Sue Cantrell 44:50
Yeah, yeah. And especially with generative AI when you think about it, it’s the first really democratized AI we’ve had right that we put it in the hands of workers. Um, Our next trend is called boundaryless HR. And the idea here is that, you know, in order to move the dial on human performance, business and human outcomes, we kind of need to rethink what HR or people expertise is. And the notion is that we need to move from kind of a specialized, oftentimes siloed function to what we’re calling a boundaryless. Discipline. And discipline is very different. It’s the people’s expertise, no matter where it might sit, it might sit outside of HR, certainly HR has it as well, that’s co-created and integrated with the people, business and community it serves. So when you think about it, HR as a function has made a lot of progress in the last five years, around integrating within the HR function, right, we have the product operating model, we have more integrated centers of excellence. You know, there’s all kinds of operating models, basically, with the intent of better integration internally within HR. But the next phase, we think, is to become better integrated with the rest of the business, with our workers, with even outside of our business with end customers potentially, when you think about it, there’s kind of four boundaries. This is why we call boundary lists HR, that start to dissolve with a boundary list HR approach, first, the boundaries between HR and other disciplines. So you know, digital transformation, with the advent of Gen AI, HR has got to work closely with business leaders and workers to redesign work and roles, right? All kinds of examples, responsible use of workforce data, and AI HR has to work with it with risk with ethics. ESG, HR has to work with corporate responsibility, DEI finance, operations, marketing, public affairs, right, the boundaries between those disciplines are coming down second boundary areas between HR and workers and leaders and managers. Rather than owning the discipline of people, HR co creates that discipline and cultivates it across all roles in the organization. Third boundary is those boundaries that equate the notion of jobs to work and employees to workers, right. HR has traditionally managed employment, you see this here on the left side, the third one down. Instead, we need HR to orchestrate work. And I mean, this was the slide that Jason was showing earlier, right? It’s not about just jobs, it’s about orchestrating skills and matching them to work. And some of those skills could come from outside of the organization, they might be extended workers, workers from your partners, right. So that’s a big shift. And then the fourth boundary we talked about is the boundaries between HR and external organizations, you know, do we need to bring think about how I’m bringing in the end customer perspective, outside parties, like educational institutions, partners, you know, government organizations, trying to have a voice in terms of regulations, and the like. So they’re basically five big shifts that we see driving the need for a boundary list approach. Being able to unlock human performance is going to absolutely require a boundary list HR approach. When you think about it, the rubber hits the road with the manager. The manager needs that people expertise, to be able to unlock business and human outcomes, elevating human sustainability to be able to focus on those human outcomes. It’s not just an HR responsibility, I spoke about orchestrating work, being able to shift from aligning HR practices to the business strategy, which is like HR business partner, you know, as a strategic partner, to really driving business transformation, and shared outcomes. People’s expertise is so important today in terms of competitive advantage, that we need to be joined at the hip with strategy. And then finally, from HR kind of managing worker compliance to managing and mitigating workforce risk. So on the right, you see, only 15% of executives strongly agree that the organization values the work performed by HR, probably not a surprise, we think being able to shift to a boundaryless HR approach will help unlock that. So of course, the founder of this HR company has AI at the center. 52% of HR executives said that generative AI would be disruptive to their role this year. You know, here’s some examples right? On the left, beyond just doing things faster, like creating first drafts of job postings, generative AI can give HR professionals greater insights. But most importantly, I think it can dissolve those boundaries between HR and workers and leaders. In some ways it can put people’s tools and decisions in their hands. So a couple of examples on the right. IBM, for example, uses AI tools to help managers make better decisions and spot issues like attrition risks, so it’s giving the tools to the managers, right. It even helps suggest, pay and identify pay gaps. Google Cloud Manager is these people dashboards provided by HR to share insights on organizational health and performance. And they plan to embed AI. In the future, the model changes to things like team structures or roles. And basically, here just wanted to highlight that AI is doing more than just automating and augmenting today, but generative AI, right, that’s what we’ve heard. See the automating the tasks we currently do augmenting is supporting HR professionals to improve their effectiveness work, work outcomes and workforce experience. But it’s also going to offer new opportunities for HR to do new things in the future in two ways. One is what we call extend where AI performs activities humans are unable to perform or scale due to that inverse relationship between manual work effort and return on investment. So things like we can now deliver personalized onboarding experiences down to the individual level, right? We couldn’t do that before. Also create. So humans need to develop new skills and take on responsibilities to design, build, test, deploy, monitor and maintain AI solutions. And maybe HR is going to be involved in that right? Are we going to need to monitor AI outputs to, you know, identify and resolve unintended issues? Are we going to conduct prompt engineering and fine-tuned AI solutions to improve their solutions? And lastly, I just wanted to do a couple actions on taking a boundary list approach. I talked about how important it is for managers to become people leaders and have that people expertise, combining business data with workforce and HR data and having shared metrics across functional areas. You know, creating cross functional teams, or even cross functional integrator roles, we see that with like, chief experience officer, which is workforce and customer experience, as an example, co create with your workers put those tools in the hands of your workers pursue collaboration and partnerships with external entities. And I’ll just give you a brief example of Johnson and Johnson’s HR decision science team. They’re integrating all of this finance, operational customer data and workforce data to make better end to end workforce decisions. And they’re bringing cross functional teams together. They have not only HR folks, but people from all across the organization and their decision science team. So that concludes our trends. And I’ll hand it back over to Monica, to see if we have any q&a or to close us out.
Sue Cantrell 53:26
Yes, Jason, thank you so much for your enlightening presentation, where as we begin to take questions from our listeners, of course, you can use your q&a section to the ask questions of Sue and Jason, the first question is, what is needed to embrace the mindset shift from how we used to think and do things to where we should be now, given the way work is changing?
Sue Cantrell 53:51
I’ll start with that. And then maybe Jason, you can chime in that the mindset shift is probably one of the most important issues. To address I think it’s one of the biggest barriers, I think we need to be able to open ourselves to, to, to looking at things in a different light. I mean, we talked about those proxies, being able to see more meaningful constructs. So, you know, not just the job, but skills, right, and then to be able to measure them. I think it’s really important to make it tangible, rather than just a mindset shift.
Jason Cerrato 54:32
I think a big part of it is trying to determine what outcomes you’re trying to drive and what problems you’re ultimately trying to solve. But the other part about it is it needs to be a systemic approach, right? It’s not just a tool, right? You have to address culture, and you have to address policies and you have to address processes. It’s all on the table. Right? So for example, I was having a conversation a week or so ago, where the main focus was returned to the office. And I was saying, if you think this is just about returning to the office , that is the tip of the iceberg, everything we talked about today is happening, whether you work in the office or you work remotely, the world of work is changing, right? So it’s it’s about policies and culture and technology, whether you’re all sitting together in the same building or not the world of work and the way we’re going to work together, and the tools we’re going to work to get it done, are drastically different than how we did this just a few years ago. And we need to kind of rethink how we think, operate, manage and measure differently going forward.
Sue Cantrell 55:42
What do you think are some of the pain points that might be addressed? If we embrace this mindset shift?
Sue Cantrell 55:56
I think some of the pain points are, are, I think probably the most important pain point is not knowing where you’re going. You know, you need to be able to have this sense of what outcomes you’re trying to drive, echoing part of what Jason said, to be able to, to then move in that direction. And then I think one of the pain points we’ve seen going back to that measurement piece, if you don’t have the measures to help guide you to where you want to go, which is why we wrote that Beyond Productivity trend. It’s really hard to guide yourself there. And luckily, new advances in technology are helping us better measure things so that we can move the dial on those outcomes we want to achieve.
Jason Cerrato 56:45
Yeah, I think it’s okay to not entirely know where you’re going so long as you’re able to change direction quickly. Yeah, right. And business agility requires talent agility, and a lot of the conversations around talent agility ultimately lead towards a conversation around skills, right, because you need to understand what talent you have and what skills they possess, to try to figure out what the work is going to be. Because ultimately, if you’re going in a different direction, the work may be very different from the work they’re doing today. So part of how this may help alleviate some of the pain is you may be able to change direction very quickly and avoid going down the wrong path for too long and get caught flat footed or get caught with some sunken costs or some bad decisions.
Sue Cantrell 57:38
Absolutely. And thank you so much for sharing those reflections because the future of work truly is talent centric. So it’s important that we all think differently, and understand talent intelligence to help us multiply human and business outcomes. Just a reminder to our HCI members. Today’s webcast has been approved for HRCI and SHRM credit, as well as for HCI recertification. Your credits for attending this webcast will soon show up in your HCI profile under the transcript tab. While you’re there, don’t forget to check out hci.org for even more insights, as well as information on our certifications, virtual conferences, premium membership and more. I’d like to say one more thank you to our presenters today and to the good people at Eightfold. And I’d also like to thank our webcast viewer. Thanks for spending an hour with us. We’ll see you next time.
