HRE Moderator 0:00
Smarter, faster, personalized, crafting the future of HR with AI. I have a few housekeeping notes before we begin. If you have any questions or technical concerns, please use the q&a module on your screen. You can resize and minimize the different modules on your screen by using the options in the top right corner of each module. This event is being recorded and can be watched later on demand using the same link. Attendees will receive the recording of today’s event, look for that email within 24 hours post event. We encourage you to put your questions in the q&a module throughout the event for our speakers to address. You can also use the reaction module in the menu at the bottom to relay items you may like or want to express an emotion to. And now I will pass the stage to Jason Cerrrato, Senior Director, Product Marketing at Eightfold AI.

Jason Cerrato 0:56
Thank you so much. It’s great to be here today. And thank you to everyone who’s joining us for our session today. I’m delighted to be here with you and delighted to be joined by Sona Monzo and Greg Vert from Deloitte partner with Deloitte on a lot of these initiatives, so it’s so great to be partnering with them on today’s webinar, I’m going to walk you through the agenda real quick. And then I’ll let Sona and Greg introduce themselves. For today’s agenda. We’re talking about the applications of AI and HR, as well as the future of HR, and then what that means for leading the enterprise. I think this is both a technology and a transformation conversation, which is why it’s so great to go and buy both Sona and Greg. So with that, I’ll let them introduce themselves. We’ll go to Sona first. Welcome Sona.

Sona Manzo 1:44
Thanks, Jason. So happy to be here today. What an interesting topic for all of us to be spending an hour together. So I’ve been involved in this space for over 25 years in the intersection of how HR can serve as business leaders with enterprises to address the needs of the day and be future ready. And a big part of that equation is how we can continue to look at technology as an enabler. So these last few years have certainly been a lot of disruption going on in the marketplace that we’ve seen continue to accelerate. And so I think that’s why this topic is so fascinating for the three of us to join in on today, Greg?

Greg Vert 2:25
Yeah. Thanks, Sona. Hi, everyone. Thank you for joining us and appreciate the time. My name is Greg Vert. I’m a leader in our human capital practice. And like Sona, I’ve spent the last several years helping our clients take advantage of emerging technology, including Intelligent Automation and artificial intelligence to advance the capabilities of the HR functions. So happy to be here today and share some perspective and hear from you all during the q&a and learn a little bit more about how you’re approaching this topic. So thanks again.

Jason Cerrato 2:54
Okay, great. So that’s our team for today’s webinar. And this is our agenda. Along the way, we’re also going to ask a couple of polls, to get a feel for the audience. So stay close to you, your laptop or your computer so you can participate and reply in some of the polls. So let’s go ahead and get started. I think first, just to level the conversation. You know, Sona and Greg both mentioned the word disruption. This was a key call out from a report that was earlier in the year from the World Economic Forum that talked about how close to a quarter of all jobs will be disrupted in their future jobs report. And, you know, as we get further and further into the future, you know, these stats in this picture are becoming somewhat clear. But the key takeaway from this report was, they refer to this as this new era of turbulence. And I think that’s a very, very apt description. And especially for those folks working in HR. The HR function and the HR practice are changing significantly as we adapt to the new ways of work, the way we’re all going to work together and the technology that comes into play, for carrying out this work. So it’s kind of a two sided conversation, both examining how the HR function is changing, and how people will change the way they carry out their job every day. But then also how the HR practice is changing, and all the other roles and other jobs that we support and organizations, the way we manage talent, the way we acquire talent, what those roles and the way that work is done looks like all of this is changing all at once. So we are truly designing the future while still trying to manage the organization going on today. So it’s never been a more challenging, but also exciting time to be in this space. You know, as Greg and John had mentioned, they’ve been in this space for quite some time. I, too, have been in this space for quite some time. But all of this is something we’ve really never seen before and as an HR function. And as transformational leaders. We’re building the future together in real time. So with that, That’s kind of the stage for today’s conversation. And before we get started into the content, we want to get a feel for a little bit of who’s joined us for today’s call. So we’re going to start off with the poll. And here we have our first poll question. How would you describe your sentiment towards AI’s role in HR, when we give you a couple of options to select from, and we’ll give you a few minutes to submit your responses. But while we’re waiting for responses, I’ll toss it over to Greg and say, Greg, what are your thoughts? Or what is the predominant predominating thinking that you’re seeing or hearing when you think about this question?

Greg Vert 5:38
Yeah, I mean, I think we see a range of responses. And that makes sense. It’s natural for people to both be excited and skeptical, at the same time for something that’s disruptive. But at the same time, I think we’ve reached a point where every organization has to take action around this topic. And so you almost have to put your excitement to the side or contain it a little bit, you have to put your skepticism to the side a little bit and really start to chart a path forward in a way that makes sense for your organization and for the workforce that you support. But it really runs the gamut at this point.

Jason Cerrato 6:20
In Sona, before we advanced to see the results, what do you think we’re going to see in the responses?

Sona Manzo 6:26
Well, it’s really interesting. I mean, I think the conversations we’ve been having pretty frequently, almost on a daily basis are leaders asking HR leaders and their business partners looking at how do we enable these disruptions? And how do we leverage AI to do that in new and interesting ways. So I would say, we’re going to see, you know, some sentiment around it being a game changer. But we’re also going to see some people who are cautious because there’s been a lot in the news and in the dialogue about the risks. So how do you balance that risk reward? So I think it’ll be interesting to see what these results look like, Jason.

Jason Cerrato 7:01
Okay, so let’s, hopefully everyone has hit their button that wanted to participate. And we’ll see what the results look like. So here, we have a couple to lead, we have almost 28% of the audience that says they’re excited, and that they see this as a game changer. 40%, almost half are optimistic, and they see the promise that this could deliver, and about a quarter are open to it. But one more piece of evidence. So I think this is pretty consistent with some of the conversations that I see that I’ve been having any immediate reactions to these results.

Greg Vert 7:34
No, but I’m guessing we probably have a little bit of a bias because the people that join this call are probably excited and optimistic about the future. So it’s good to see. And I think that’ll be a good start to our conversation today.

Sona Manzo 7:49
Yeah, and Jason, I would just say, you know, one of the things that I would add to that is if you put your skills based strategy lens on this, that’s where we’re seeing so much excitement, right? How do we look at using skills as a new currency? And how do we use AI? To really provide that talent intelligence to answer those questions. So I think that will be something as we go along, we can talk more in detail about

Jason Cerrato 8:15
Sure. So we’re gonna talk about the pace of change and how this is impacting organizations. So with this, I’ll hand it over to Greg to get the conversation started.

Greg Vert 8:27
Thanks, Jason, Jason. And yeah, the goal here isn’t to do a formal history lesson here, around HR and workplace technology. But we did want to kind of take a look back and just talk about the progression that led to this feeling that we’re now entering the artificial intelligence era. So if you go back 35 plus years, HR technology was primarily administrative data management, databases, really in nature, there was on premise technology, not very user friendly, typically required a lot of training and, and special expertise to be able to use these systems. And they did what they needed to to enable the business. A little bit later from that, we started to see some innovation in point solutions, things that focused on recruiting, learning, time management, payroll, specialized tools that would allow you to do more with your data to enable HR as a function. And then about 15 years ago, there was a mass migration for HR from these older on premise solutions to more modern cloud based platforms. And we’ve been going through that journey for the last 15 years or so. And some organizations move faster than others. But it was really a moment in this timeline where the new replaced the old, wholesale, right we kind of all got a fresh start. Not necessarily from a data perspective, there was a lot of historical data that had to be accounted for. But from a technology perspective, it really provided a clean slate, and it also marked the shift to more and more self service, which is why we see that strategic focus move toward engagement, and giving employees and managers and really your HR professionals in the, in the field, the ability to use technology themselves directly to get their work done, access data run reports, etc. And as a result, about five years ago, and saw estimates, right, but about five years ago, we started to see an increased focus on what we call digital platforms. And these are technologies that are focused on making the user experience better, really in, in, in supplement to those core cloud technologies, who were also investing to make the user experience better at the same time. All of that has sort of led us to the beginning of this artificial intelligence era. And it’s, you know, both technological breakthroughs, the massive cloud computing gave us access to the data that allowed for AI technology to mature at a faster rate. But it also was the shift in that strategic focus from not just providing the right experiences and engaging with your workforce, but really, to trying to empower them. And the way that I interpret that is everything that happened up until the point in time where we are today, required us as humans to learn how technology works. And that barrier got lower and lower over time. But it’s still required training humans, humans were burdened with learning how technology works. Artificial Intelligence is an opportunity for us to switch that around. And now the burden is really with technology to learn how humans work. And it’s going to reduce that barrier for us to fully harness and be empowered to use technology to almost zero. We know there’s more stuff coming in the future, you know, it’d be naive to think that this is the last big disruption that we’ll see from a technology perspective. But it’s important to note that the pace of change and the cycles of these major disruptions have been getting shorter and shorter. So as I mentioned, when we were looking at the polling results, there really is a universal call to action here around AI, because you may only have a couple of years to start to figure it out before the next big thing comes along. So if your strategy is wait and see, you know, probably something we wouldn’t recommend. And, and you know, the other thing that I’ll point out here, when we did the mass migration to the cloud, it was a wholesale replacement. Everything that’s happened since then has been layering on, right, we’re building on the Cloud Foundation. And so whatever that next thing is, assuming that it continues to layer on, you’re gonna want to have a pretty good position around AI, as part of your foundation as part of your technology stack to be able to take advantage of whatever that next thing is. So

Jason Cerrato 12:35
I love the way you phrased that. Yeah, I love the way you phrase that it’s not just the advancement of technology, it’s also kind of shifting the lens at which we’re looking at the work. I think we’re gonna get into that in the upcoming slides a little bit more. But that really also speaks to the need for not only technological advancement, but kind of a transformation of the function and the way we organize around work and the way we organize around some of the tools. So I’m looking forward to hearing some more about that in the upcoming slides. Yeah, and I think maybe some nice summary of some of the reports of your AI findings.

Greg Vert 13:14
Yeah. So some research to kind of back up this idea that we’re now in the age of artificial intelligence, right. So Deloitte has run for the last several years a state of AI enterprise report. So this particular report had well over 2600 responses. So it’s a large, large dataset that we have to work with. And there are a couple big things. One is that 94% of business leaders agree that AI is critical to success over the next five years, which is about as unanimous as it gets from survey survey research. But the other thing that you see on the left hand side here is that the playing field right now is pretty evenly distributed, you have roughly a quarter of organizations that are still in that starting block state, they haven’t deployed much in what they you know, obviously, because they haven’t deployed much they haven’t seen a ton of results. In the top right quadrant, you have roughly 25% of the landscape that has deployed a lot. And they’ve seen significant returns to the AI that they’ve, they’ve, they’ve deployed, and then you’ve got this group in the middle, that sort of a mixed bag where the path seekers have not deployed a lot. But what they’ve deployed has produced the intended results, right? Results from Ai investments are not guaranteed. We’ll talk more about that in a minute. But they’re up there seeing that return. So they just have to figure out how to invest more into scale. And then you have the underachievers and this, these are groups that have deployed a lot. They’ve tried to do a lot. But the results aren’t there, or at least they’re not consistent. So I think this kind of paints a picture that you know, everyone is sort of in different places in their AI journey at the moment. It’s pretty evenly distributed. And when we looked at the data, the underlying data that contributed to the organizations that were in that top right quadrant. The things that they did that were different from the others, really came down to non technical, non technology related activities. It was how they invested in culture and leadership, to embrace AI and to embrace more of an agile mindset, how they used AI as a catalyst to transform operations, how they thought about AI and human talent working together and orchestrating that in a way that delivered results. And I think, you know, very underrated, how they went about selecting the right use cases that were going to accelerate value and create some momentum in their AI journey early on. So those are some of the things that, you know, the more successful organizations that are in the top right quadrant are doing that I think others can learn from, regardless of where you are in that, in that maturity curve. But, you know, Jason said, I’d be curious to get any other thoughts on this research? And hopefully, this kind of continues to help us set the stage for our discussion today.

Jason Cerrato 15:58
So let’s go first.

Sona Manzo 16:00
Yeah, you know, Greg, the point about investing in culture and leadership, I’ll just kind of add on to that, when we look at using AI to start moving towards a skills based organization. It’s exactly one of the key topics to talk about, right? So setting your talent philosophy, so that you have an organizational strategy. And you can have that red thread of how that will be utilized across the talent spectrum. And I think one of the key things is that we’re seeing AI really accelerate the ability to then take that and put it into action. And so as you said, you know, certainly looking at the right use cases, but looking at that foundation, to help you prioritize, and then developing, you know, that connectivity to a skills portfolio and how that connects in with your job architecture that can support that transformation is an area that we’ve seen a lot of interest, again, in kind of leveraging AI and moving more towards that right upper quadrant, I think as transformers through that technology.

Jason Cerrato 17:01
And I’ll just, I’ll just add, I think, you know, Greg, when you showed that kind of timeline slide, and the move to the cloud that happened, you know, over the last decade, there was a lot of focus on the tool. And a lot of those projects and a lot of those initiatives. And I think now, there’s a lot of needed focus on the transformation. Right, as the tools advance as the tools are able to do more, it becomes all these other things that happen around the tool that become increasingly important. So this resonates with a quote from an Eightfold conference we held earlier in the year where there was a talent leader on stage that said that technology was the easy part. It’s all the stuff around the technology around the use cases, the transformation, the culture, right, that really make it sing. So I think this, this speaks to some of the things we’re hearing from those adopters as well. Okay, with that, we’re going to talk about kind of how this is applied in practice. And we’ll start getting into a little bit of the applications of AI in HR. So with that, we’re going to set the stage with another poll question. So our next poll question is to what extent is your organization currently leveraging AI in your HR practices? And we’ll give you a few minutes to go ahead and respond.

Gregerson? I’d love to hear your opinion on this. I think when people are asked this question, to what extent sometimes they’re under reporting, because they don’t even realize all the places where AI may already be? What are your thoughts there?

Sona Manzo 18:31
Oh, that’s a great point. Jason, I think that’s true. I think what we’re seeing is organizations who have been, you know, on this journey to understanding how to identify these use cases, but start the experimentation. And I would say we’ve got a pretty big range of some organizations who have developed a strategy where they have gone through that process, their experience experimenting with the technology, and it’s getting woven into the ways of working. So some parts of the organization don’t even realize the impact of AI that is happening on a transformational basis. But I’d say it’s a pretty big range when we look across the talent spectrum in terms of the way it’s being leveraged today.

Greg Vert 19:14
Yeah, I’m curious to see the results because we’ve tried to do some benchmarking here. Our clients usually ask us for that type of data. And everything’s moving so fast. The amount of time it takes to collect the data, the shelf life of because relatively short before your organization’s invested and made changes and and the goalposts keep moving. So it’s an interesting space. And I love the question because it does require some interpretation. It’s a little subjective, but I’m curious to see what the audience responded with.

Jason Cerrato 19:47
So without further ado, let’s go ahead and see the results. And Greg, walk us through what you see here.

Greg Vert 19:53
Yeah, this is interesting. I do feel like we are exiting an experimentation phase and moving more into a deployment phase with AI in HR. And I think the data here sort of suggests that right, you’ve got about 20% that aren’t using it at all, which is consistent with our quadrants, right. And then, you know, about 38 or 40%, rounding up, that are exploring, but not quite implementing, and then another 27-28% that are using AI and I would say pockets are with specific tasks. And that’s about what I would expect, based on, you know, our experience working with clients. And I think, you know, if we were to come back and do this webinar a year from now, and ask the same group, I would expect to see some pretty significant shifts towards some of the answers on the bottom of the screen.

Sona Manzo 20:42
Yeah, and I would say that, you know, again, if we look at these different segments of the talent lifecycle, you probably see higher adoption in areas like talent acquisition, the implementation of talent, marketplaces, another area where we’ve seen, you know, quite a bit of movement. When we did our skills based or survey and research, we found the use of AI, you know, heavily weighted in some of those areas, but really emerging in other areas like workforce planning and talent planning, and starting to see trends and a lot of interest in that, you know, on the other end of the spectrum, you know, where, where are we in terms of looking at the impact of that on rewards, or looking at the formation of teams, you know, so you’re gonna see a really different level of investment and commitment in different areas of the pipeline. But I think the conversation is leaning more towards how do we set this vision so that we are starting to not be so silent, when you see this result, you’re about limited for specific tasks? or moderately using, I think we’re really starting to see the dialogue change to how do we develop this strategy for our organization, and specifically within HR to start leveraging.

Jason Cerrato 21:53
So I think that’s a great segue into our next slide, which is a little bit of an overview of what you’re seeing from an adoption standpoint at Deloitte. Greg, you want to walk us through this one?

Greg Vert 22:02
Yeah. And so artificial intelligence AI is kind of an umbrella term, right. And underneath that, there’s a lot of different capabilities, a lot of different technologies that really make up what we refer to as AI. And instead of getting lost in all that, right, when we talk to clients, we’re usually thinking we usually start with, what can the technology do for you? What are the ways that you can apply it within the HR function to create results that create a meaningful impact? And so we came up with these four categories, and there’s a little bit of overlap in them. But you know, the first one is how do you use AI to automate operational tasks? And then processes? We call this category Intelligent Automation? Obviously, the benefit of this for?

Jason Cerrato 23:06
Are you Greg frozen? Greg may be frozen Sona, are you still there?

Sona Manzo 23:12
I am here. Yes.

Jason Cerrato 23:14
So let’s wait a moment for him to come back. I think I really like this slide, because it breaks it down. And even if you look at the first word of each section, you know, automate, engage, deliver, and generate. And you think about those applications. Like he said, it’s a broad use of the term AI, but they’re aimed at different outcomes. And I think that’s one of the things we’re currently learning to get our arms around now in this discussion. Any thoughts there?

Sona Manzo 23:40
Yeah, I think that’s so true. And, we’ve seen that the adoption curve of these areas is continuing, like those outcomes are starting to really come through in terms of some of the Intelligent Automation or the cognitive analytics, that insights to tell intelligence, etc. Things like not only the impact, and in terms of the sentiment of the workforce, right, in organizations that are starting to implement this, it’s resulting in more transparency, more agency for employees, through these cognitive analytics to the data driven insights or the time intelligence, if you will, but it’s also having a direct business impact on things like ability to innovate and respond to change. So I think when you start to really combine the way in which we layer in these different types of AI applications to the business outcomes, it is driving a different discussion. And certainly now when we start thinking about generative AI across the spectrum here, the augmented professionals is really an interesting one. It’s one that we as an organization haven’t been investing time with and looking at the way in which that is being applied in different industries, and how we can use that to really start thinking about reimagining the work that’s being done. So AI driven work design is another aspect of that

Jason Cerrato 25:00
Greg, I think you were able to come back. Did I see you,

Greg Vert 25:02
Papa? I apologize for having some issues here in the local office. But yeah, so thank you for picking up and leading us through this. I think the key is that you were really touching on at the end is organizations that are going to thrive in the era of AI are going to be the ones that figure out the right way to architect these different capabilities together to go after the most impactful and value added use cases across the HR function to the ones that are going to really make a difference from a business or workforce perspective.

Jason Cerrato 25:32
And I think the next section of our content today is kind of putting this into context and what this looks like, in the, in the aspect of like, let’s see here for a talent lifecycle.

Greg Vert 25:45
Yeah, I think this is interesting. I’ll talk to this one this station

Jason Cerrato 25:48
speak to.

Sona Manzo 25:53
Now, Jason, might be coming out, Greg, I think you could.

Greg Vert 25:57
Sure, I’ll go ahead and speak to this one. So you know, one of the interesting things, especially in the breakthrough, Recent breakthroughs with generative AI is that we no longer are trying to find use cases that fit the technology, Jason kind of talked to that earlier, we can really look more at the work that HR does, and kind of work backwards to find the right types of AI the right forms of AI that can either automate elements of that work or augment the person that does that work to make them a little bit more efficient, a little bit more effective. And so what you see here are a couple of use cases just kind of a sample throughout the talent lifecycle, although I will say, I’m aware of a client that has either implemented or pursued every one of these use cases, so they’re grounded in reality, right? If we just take a couple from the beginning, how do you use this technology to automate the creation of job descriptions? First, the first draft job descriptions are creating benefits guides using combinations of internal and external data. We see organizations using this to generate pre screening questions that are contextually tailored to a specific job or role. We see generative AI used to synthesize interview notes to help speed up the decision making process, especially when a number of different interviewers have met with a candidate creating job offer letters or contracts. If that’s required, in the geographies where you operate, addressing new hire questions, generative AI really unlocks the ability for chatbots and digital assistants to provide near human-like support. That’s been a challenge up until the recent developments with generative AI, but I think we’re going to really see a big wave of chatbot adoption and kind of finally breaking through the barriers of using that technology to create good experiences, positive experiences. And the list kind of goes on and on. I’d be curious to hear, Jason, from an ethical perspective, what are some of the areas where you’re investing in generative AI and AI within the product?

Jason Cerrato 27:57
Yeah, that’s a great question. You know, earlier in the year, we announced some co pilot functionality. And some main use cases are for automation and some virtual assistant functionality. A couple things we already touched on here, whether it’s the updating and formulating of a job description, catalog, or, you know, a job description library, a key one, are helping recruiters with, you know, candidate summaries to interact with sending information to managers, you know, here’s, here’s your short list of who you’re going to be interviewing. And here’s why they were selected. One of my favorites is the formulation of campaign messaging, as well as using AI to help with generating the audience and formulating some of the content that goes into the campaign. So, you know, we say that some of this capability can be applied to, but again, I think it’s this combination of automation and kind of variety that is ripe, in the TA and TM and HR functions.

Sona Manzo 29:05
Jason, I think that leads us to, you know, a great point to transition to this next slide, because we put this through a little bit of a different lens, right. So, in the last year, seeing, you know, various ways to Gen AI can be making a difference across the lifecycle. This puts it through the lens of digital experience for an individual. And really starting with connectivity in the marketplace. One of the things that we’ve seen really fascinating is this concept of talent, rediscovery, enabled by AI, right. So with a full platform, being able to have insight into talent, that in the past, we had a really difficult time discovering or rediscovering. But with these new capabilities and profile, written enrichment, basically gives insights into the skills and capabilities that individuals have developed over time. So really being able to transform the way we use our talent communities if you will. And so this really is just intended to give the vision of what the experience could be like for an individual who had previously connected within an organization, but gets a reach out based on, you know, their current skills or current interests, gets them to re-engage with the organization. And then you can see all these touch points here kind of in the blue that are AI and capability enabled, to really help improve the experience, right, the use of transparent AI to help a candidate understand why they match a position, I think is a huge game changer. We see an uptick in terms of candidate completions and the quality of candidates because of this, AI matching and transparency. And then we get through, you know, the human touch, you weren’t just doing interviews at the point in time that it’s most effective, but leveraging the technology to really speed our way through identification of the top talent. And again, from the different personal perspectives, recruiters are able to see that transparent AI, as well to help guide those discussions. If we look at this inflection point of onboarding, you know, we usually have really high sentiment, right, people are excited about this new opportunity, they’re joining an organization, we want to keep that sentiment really high. So if we use this concept of, again, transparency, helping an individual come into an organization, they know they can see what their skills are, they can see what path they can take to continue to uplift and enrich those skills, whether that’s through learning experiences served up to them, whether that’s through gig marketplace, and projects, or mentorship, there’s a plethora of opportunities to really leverage the AI technology to do that. And ultimately kind of unlocking, if you will, opportunities that were not exposed in the past, which ultimately transforms you know, the experience of an individual. And, again, like to say, make it easier to stay rather than leave an organization and continue to then find roles that are matched for their career growth and, and become an ambassador. So that’s kind of our vision of putting skills at the center and using AI to power that.

Jason Cerrato 32:10
And I love this visual, you know, just last week, I was on both the East Coast and the West Coast meeting with talent leaders, talking about their journey. And one of the key themes that came up in both of those meetings was the need for personalization and transparency. And I think as you walk through and kind of see this journey and this experience, and those things ring true, as you’ve kind of outlined all of these use cases. Okay, with that, I think we’re on to another poll to get a feel. Before, here’s our next poll question. Where do you think AI HR is?

Sona Manzo 33:03
Jason, I’ll just, I’ll just come in, I’m going to be a little bit of a disrupter and say, well, all of these are important. I think what’s been really fascinating recently are the discussions about how to chart this course out, not to think about just how we solve a particular use case, right? Because it’s easy to get distracted, like think, Oh, the traditional view of we need a candidate relationship management solution. So we’re going to narrow down just the use cases around that important value added. But you need to put it in the context now of this different and changing landscape of how we are looking at talent intelligence more broadly? How are we using AI to come across the talent lifecycle, and really think about those use cases kind of holistically and prioritize those for your specific organization?

Jason Cerrato 33:51
Yeah, and I think that speaks to, you know, this increasing conversation around systemic HR. Right, this collaborative, all encompassing, kind of all of the above strategy, where everything’s working together, kind of in harmony, but with this increased automation and personalization, right. So let’s see, let’s see what the results say. Greg, what are your thoughts in these, your first reaction,

Greg Vert 34:21
I almost jumped in before we reveal the results to say while I agree with this systemic HR, and the idea that all of these are opportunity areas, and important, but I would always put my money on recruitment and talent acquisition for being the place where he will see the biggest potential and sure enough, the data supports that. And it’s not, you know, to this on this point earlier, it’s not because these other areas aren’t important. But I think given the nature of the work that goes into talent acquisition to use AI, and the volume of interactions that could be facilitated through AI, it just really is the perfect place for organizations to see Art. And it’s also not not not coincidentally, the most mature area from a market offering perspective, there’s a bunch of solutions that you can evaluate and consider and a lot of really proven use cases for AI. So it’s, it’s not surprising.

Sona Manzo 35:15
It’s interesting. I mean, I would just share what I think can happen when we talk about talent at recruitment and talent acquisition. Every organization who’s focused on talent acquisition, there’s an element of internal mobility. And so kind of lost in that number is, you know, the fabulous opportunity to be opening up opportunities to really optimize the talent that an organization has. So I would say, as we’re having those conversations, right, like in that number with recruitment and talent acquisition, I like to think about it from the workforce ecosystem perspective, right? It’s built by borrowing, and then maybe both equations if we add in the augmented workforce, right, and really thinking about that in a tie together.

Jason Cerrato 36:00
And I was just gonna say, as a former ta leader, and a former life, recruitment and talent acquisition usually leads the charge, but just because of the amount of volume, as Greg mentioned, but also in a former life, I was an industry analyst, during the rise of AI solutions, and a lot of people started with recruiting and talent acquisition, because they were working outside in. Right. So I think that’s why a lot of recruiting and talent acquisition comes to the forefront. Greg, you also made some great points there. But I think increasingly as we become more comfortable, and as the technology advances further, we’re getting closer and closer to the organization, which is, you know, Sona, you make a great point around internal mobility and talent marketplaces. Let’s shift and talk a little bit about the future of HR, from your view of the world.

Greg Vert 36:49
Yeah, thanks. Thanks, Jason. So one of the ways we like to start this conversation is to look at the work that HR does, and the impact that AI can have. And so we kind of think about these four key categories of impact. And I’ll start on the left and move to the right. On the far left, you have automation, AI can automate work, we kind of talked about that, when we were looking at the different categories of AI. And this is really effectively the elimination of work that we would otherwise have to do manually. And that’s gonna have an impact, right? It’s not to say that all HR goes away, or all HR work goes away. Not everything is gonna fall into this category. But for some things that do a lot of the work or transactional, repeatable type of work that HR does, we can talk about eliminating that almost entirely, right? Nothing’s 100%. But you can take a large chunk of that work volume out of your organization. As we move to the right, though, we start to look at areas where AI will augment the work that HR does, right. So we’re never, we’re not going to reach a place at least not in the near term where AI can fully automate, where AI can be autonomous and it can operate without any human intervention. But instead, what it can offer is the first draft of a document, the ability to help an HR professional, find the answer faster, or research a problem faster, you’re still going to be doing the work. But now maybe you can be a little bit more efficient, more effective, more productive, because you’ve got aI assistants to help you in those first two categories on the left hand side are really about how does AI help you with the work that HR does today, when we get into the the right hand side of this, I think it gets a little bit more interesting, because when we talk about how AI can actually extend human capabilities to do HR work that we don’t really do today, or at least we don’t do at scale, you know, this now becomes a value creation opportunity. And its examples are where you wish you could analyze more data and produce more analytics and insights about your workforce. The effort to do that manually and to build the right data models and, and, and spreadsheets and pulling all the data together into the right formats is labor intensive, and, and prohibitive for scaling. But when you have AI in the mix, you can actually start to go after a lot more analytics, you know, opportunities and business problems that you can solve with data. You can also, you know, take personalization a step further, right. So I always use the example with clients that it would be, it would not be feasible for HR to manually create personalized onboarding programs for every new hire. Right. And so as a result, you have to create this sort of standard version, that maybe you’re maybe the hiring manager, if they’re, if they’re really good, can adapt that and create something personal on top of it. But what AI can do is it can actually look at a bunch of data and tailor, not just personalized, but almost individualize onboarding programs to help people get up to speed quickly and be productive in their new roles. And so those are the opportunities that we think about where it’s really AI taking what we wish we could do if you know we had the capacity, if it were more practical and start to do things, offer better services, analyze more data, and create more value. And then the last box on here, which I think often gets overlooked, is as we start to embed AI more and more into how we work and how we operate, there’s a whole new category of work that gets created to manage the AI to monitor the AI to design and deploy. Test testing is huge testing and deploying AI. And so a lot of what I think we’re going to see in the HR function over the next couple of years is the shift out of the work that can be automated and repurposing those the HR professionals that used to do that work to be more on the side of creating, deploying and managing AI solutions. So it’d be a really interesting transition over the next couple of years as AI plays a bigger and bigger role. But Sona Jason, I’d be curious to get your thoughts here.

Jason Cerrato 41:00
I think it makes me think, similarly to some of the HR org shifts and redesign that happened as a result of moving to the cloud. You know, things like shared services and centers of excellence, there were certain things that allowed organizations to adopt those types of models and those types of orgs, based on the nature of the tool and the way work got done. As I’m listening to you, and I’m reading through some of your findings, it seems very similar to the you know, AI is going to have a similar impact.

Sona Manzo 41:30
Yeah, and I think, you know, when we get down to this, that creation of new roles or job responsibilities, and be part of this is, again, helping elevate the human capacity to be strategist and advisors. And I think when you think about our roles, as HR professionals, that’s something we’ve talked about for so long, and we’ve had various tools that have helped us get there. But I do think this is a true transformational opportunity, right, we’re talking about moving from the role of a recruiter of having to manage such a large volume of data in searching and finding the right people to actually being true talent advisors, with hiring managers and with business leaders to think through the utilization of CAP talent, communities and talent strategies that are informed by the information that we’re able to get out through this, you know, extension, synthesis of the data, and the talent insights that were able to get through the AI.

Greg Vert 42:28
And I think Jason’s on a boat, both of your comments are a great segue to what the future could look like for HR. And you know, this is early thinking. We have a lot to learn collectively, as a profession over the next couple of years as AI takes on a bigger and bigger role. But as we look to the future, we kind of project what the future of AR HR might look like. This is a model that we’ve been starting to talk to our clients about. And it really puts AI at the center and has this AI first mindset when we think about the work that HR does the services that HR delivers the consultation and strategic thinking that HR does, and in shifts away from some of those traditional components that Jason mentioned when we saw the mass migration to the cloud with COEs and business partners and shared services, and kind of sees the next evolution building blocks. So instead of business partners, you’ve got workforce solution architects that are augmented by AI and can move a lot faster in terms of using data and insights. And helping business leaders solve their most complex talent challenges. You’ve got aI solution, DevOps, and sustainment as a team within HR that’s responsible for designing and building testing and deploying and maintaining AI solutions. Based on HR’s priorities and the business needs, you’ve got an AI innovation and insights that because you can now scale data analytics and insights, you become a value center for the organization and a place where people can go when they have questions that are related to human capital. And they want to have the right data to help them solve or work through those challenges. And then you’ve got at the bottom kind of the core of the service delivery and AI powered people ops and engagement team, where most of the interactions with employees and managers outside of you know, strategic high touch use cases or exceptions are going to be delivered through AI directly. And the role of humans will be more of monitoring and maintaining those solutions to make sure that they’re delivering the right experiences and providing the right levels of support. So this is a massive shift. And obviously, anytime we talk about AI there has to be a wrapper around it of governance and strategy and management that’s needed in order for this to work. And you can see some of the other big shifts. So it’s not just changes to the roles but it’s also this idea that Agile is critical to enabling this AI and agile kind of go hand in hand and and a If fluency and skills are going to be required for all HR professionals, regardless of where you might sit in this future, hypothetical operating model, so it’s not adjacent. Anything to add here. Should we go to our next polling question?

Jason Cerrato 45:15
Thank you. We’re gonna go down to the poll, let’s go on to the poll. So I love that you’ve put it down. And then we have this kind of suggestion. But always, you know, sometimes things are easier said than done, people do run into some roadblocks. So our next poll question is what are some of the biggest roadblocks you may face when trying to implement new HR technology or go through a transformation like this?

Sona in your conversation with Deloitte clients? What are some themes that keep coming up? In your engagements?

Sona Manzo 46:01
Yeah, I think, you know, the one around resistance to change. You know, we put our change management hat on for any transformation, so fundamental to the success of an initiative. But I think, you know, being able to look at setting that ambition at the beginning, what’s the transformation ambition, what’s the change ambition, making sure you’ve got stakeholder alignment, and then you know, kind of working through the process on change impacts and champions that can really help kind of tamp down that resistance to change. And then, you know, just acknowledging at the front end that it’s going to be an ongoing journey that needs to be supported kind of anchors back to what we’re talking about, about the operating model, and the need to not look at it as a one and done. So I think all of those kinds of messages are things that we’re talking about and confusing and to kind of respond to Item B there. We can have a whole conversation on Item D but they will see the results and then continue that.

Jason Cerrato 47:01
Greg, Greg, before I show the results of this time, do you want to give a guess or any opinion on this before I pull back?

Greg Vert 47:08
Man, this one’s this one’s a little bit less clear. For me. I think we’re gonna see a more even spread. But that’s just a bet. Just a guess.

Jason Cerrato 47:17
Okay, let’s see what we get. I’ll call. Yeah, I think this is the best event of the day.

Sona Manzo 47:29
Yeah. Well, you know, on the privacy data, security concerns, this is, you know, obviously such a hot topic. We’ve seen it just in the media in general, in regards to AI. And it’s certainly been a hot topic at various conferences and conversations we have with our clients. One of the things that I have found really fascinating is the conversation that has been kind of put forth by key Sanderling, you know, the Commissioner of the EEOC. And I think balancing kind of the the risks that concern with, you know, it’s not about if you’re going to use AI in the HR lifecycle and deployment lifecycle, but really, knowing that being able to utilize AI effectively, and having a trustworthy AI strategy is critical to actually reducing bias. And so I think, you know, that dialogue on the national stage, as well as the global stage has been a really fascinating one to watch. And, you know, certainly I think we’re going to talk a little bit more about, you know, our Deloitte perspective on AI and risk and governance, but this is an area, again, one of lot of concern expressed here, maybe of a barrier, but certainly one that there’s a lot of conversation going on to help inform and educate organizations.

Greg Vert 48:46
Yeah, and one thing I would add, add here around the budget constraints, since I came out as number one, is, I think, if you’re struggling to create the value case, that will help you get funding for whatever it is you’re trying to do. You might be looking at the wrong use case, especially given what we saw earlier in the polling, where most of most of the responses show that we’re early in the journey, there are a lot of opportunities out there within HR that should have pretty clear cut value cases tied to them. And, you know, it goes beyond just the potential for ROI or financial savings, right, really looking at the upside or value side of the equation in terms of how it impacts the workforce makes things better for business leaders and enables organizational growth. You know, that should be the way that would be the way that I would approach that kind of budget constraint challenge.

Jason Cerrato 49:39
The answer that I was going to jump into was resistance to change, but maybe that’s a topic for another day. That’s a whole nother webinar. Let’s move forward and talk about what it looks like to lead these efforts in leading the practice. Yeah, so I love this thought approach Greg, walk us through it.

Greg Vert 50:02
Yeah. Thanks. Thanks, Jason. And I think you know, up until now, we’ve sort of been talking about HR for HR. And here we have an opportunity to kind of really think about thinking about the enterprise. And so going back to the statistic that Jason started us off with, right, the impact that AI will have on jobs, you know, that’s not just within HR, that’s something that all the work workforce segments, HR supporters are going to feel that impact as well. And so a different study cymbal came out around the same time, you estimated that 300 million jobs could be impacted by AI. And that impact will be felt differently and at different points in time, right. So we’re kind of heading into the era of AI. This gradual transition toward the future of work, in HR, I think, has a huge opportunity to guide the enterprise through that transition, knowing that it’s not going to be a single round of transformation, like we may have seen in the past with the migration to the cloud, it’s going to be gradual iterative, it’s going to happen in pockets. And it’ll be a challenge to sort of manage what’s happening at the micro level with what’s happening at the macro level, and sort of the cumulative impact of AI on your organization. So you’ve got the 300 million jobs that are impacted, that, you know, clearly paints a picture of the disruption that we’ve seen. But by taking a human centered approach, we believe that you’ll be able to improve the likelihood of generating the right results from your AI initiatives, you can see here right now, and you saw it at the beginning from our state of AI report, that it’s about a 5050 shot that in AI investment you make are going to produce the intended results. And the way to increase that is actually through the human centered design approach. And you can see that in addition to that 95% of people, you can kind of read that as employees or workers have a negative perception of technology when engagement and trust levels are low. And we’re starting to see some really interesting findings in the early days of AI adoption, that suggest trust is a key key factor for how well AI gets used within an organization. And it’s not only trust in the technology that the outputs are right. But it’s also trust and leadership that they’re investing in this technology to not only better the enterprise, but also better the lives of the workforce. And you can see all the opportunities on the right hand side. But maybe a way to kind of make this real is to talk about some of the things that organizations are doing now to set themselves up for success with AI. And these are all opportunities for HR to play a role. In this, these are things that organizations are actively working on now. The first is driving AI fluency and adoption. I saw a question in the q&a about what AI fluency really means. What does it mean? And there’s different levels of fluency or proficiency, you can kind of think of it as a synonym. But it’s all about the knowledge and skills that we as humans need to have, either as consumers of AI, or as producers of AI to be able to use this ethically, responsibly, productively, to change the ways that we work. And it’s also about adoption, right. It’s how getting people comfortable with using new technology has always been a challenge and always been an opportunity for HR to play a big role. There’s a big mindset shift to becoming an AI first organization, HR can play a big role in that. There’s the role that HR can play in helping the enterprise or different business lines and functions, prioritize our use cases, and think about value creation more holistically, not just about financial savings, or productivity gains, but also the impacts that could have on wellbeing, and retention and engagement. So that we’re not just myopically re evaluating each of these opportunities. And then last one, we talked about the importance of trust, but building a culture of engagement and trust, its HR has long been sort of the culture bearers and builders of culture protectors or preservers of culture, along with managers and business leaders. But this is a huge opportunity where we know there’s a relationship between engagement and trust, and, and the ability for AI to be successful, successfully deployed. And so HR can play a big role in driving that forward. And I know we’ve only got a couple of minutes left. But one of the ways just kind of related to trust that we’ve been helping organizations think through is by understanding what makes trustworthy AI. What are some of the components that have to be in place in order for AI to be viewed as trustworthy? And you can see some of those capabilities here have to be private, we have to believe that the data that we’re providing to it and that it’s being used is safe and secure. There has to be accountability, not just within the AI to provide the right answers, but with a team of humans and owners that manage that particular solution has to be transparent and explainable. Sonna mentioned this earlier, right. If you’ve been recommended for a particular job, we have to be able to understand why did AI right make that recommendation? So you can not just believe the output. But I believe the algorithm or calculation that got to it makes sense and can be easily explained. It has to be robust and reliable, reliable means if I go to AI with the same question twice, I’m gonna get the same answer. Or if the answer changed, that it changed for good reason. And when we say robust, it really means dynamic and changing with the environment around us. fair and impartial, you’ll see a lot of legislation emerge, I think, in the next couple of years around this, making sure that bias hasn’t crept into the data, AI is using the models or the outputs themselves, we need that responsibility. And it has to be that safe and secure environment where people can use it without consequence. So all of these things kind of have to come together in order for AI to be viewed as trustworthy. And with that, I think we’ll kind of land on our last page here around starting your HR HR AI journey, thinking big, starting small and scaling fast. And I know we don’t have a ton of time for q&a, but Jason Sona thoughts to kind of help wrap us up anything that jumped out to you that we may want to address during the closing moments.

Jason Cerrato 56:14
I think this is one of the most common questions that comes up in these meetings in these roundtables is where do we start? I think people have moved past the thinking around. Do I have to do something they know they have to do? Now the question is, where do I start? How perfect? Does my strategy have to be before I can turn something on, you know, what, what is good look like. So I like this, think big, start small scale quickly. Because you mentioned how this aligns with some kind of Agile methodology. And I think that that rings true here. Plus, you know, we’re in this period of not relying on our history and building our future through a little bit of experimentation.

Sona Manzo 56:56
I think that’s spot on. And I think we’re seeing some organizations actually even leap, what leapfrogging the start small, because they’re able to take advantage of some of the early adopters and learn from that and actually accelerate the pace of change in their organization in some key areas. And in others, they are starting small, with, you know, like experimentation on areas that maybe are newer, in terms of maturity. But this concept of scaling it quickly and getting the right people involved, you know, we talked about resistance, you know, one way to combat that is get the right stakeholders involved, get the right representation, and get some change champions to really help you think through that, you know, this Agile methodology, you know, get in, feel it, touch it, let people respond to it. And then you know, get going

Jason Cerrato 57:47
ended on time and just want to say thank you to everyone who joined the session today and thank you again to Deloitte for joining us for the hour. And with that, I’ll hand it over to Amberley in the HRD team.

HRE Moderator 58:01
Thank you for attending today’s webinar, you may disconnect and have a lovely rest of the day. All right.