Workday Podcast: Why HR Leaders Must Become AI Transformation Champions

Megan Wright: 

From recruitment and onboarding to training and development, HR is at the threshold of a revolution—one that is powered by AI and machine learning. These emerging technologies offer new and exciting opportunities to unlock the power of a business’ most valuable asset: its people. But new Workday research reveals that, of all the C-suite, it’s HR leaders that feel most strongly that it might be too early to say if AI and ML will disrupt business for good, or if it’s simply another over-hyped technology. 

I’m Megan Wright, head of innovation at FT Longitude, and joining me to discuss this is Maryjo Charbonnier, CHRO at Kyndryl. Maryjo, welcome to the Workday Podcast.

Maryjo Charbonnier:

Great, Megan, and thanks. Great to be here today.

Wright:

What is your overall sentiment when it comes to AI and ML? Is it all hype or are we in fact seeing a real game changer for business?

Charbonnier:

We believe it’s a game changer, Megan. Let’s just talk a little bit about who Kyndryl is. We’re the world’s largest managed infrastructure services organization, with about $17 billion in revenue, and at a little under 90,000 employees, Kyndryl is worldwide in 60 countries. So when we talk about services, data, AI, we believe it’s a real game changer. And the hardest part, I think, for any organization to get their head wrapped around when it comes to AI is really unlocking first, the potential of their data. And that’s really what we help our customers with because I think it’s often trapped in all of these unintegrated systems and maybe not as secure as we would all like it to be. And that’s something to be thought through as well.

So I think we really want to help customers unlock that data so that then you can unlock the value of AI, machine learning, and those innovative technologies. And we really think of AI on a spectrum. If you think about it, it can really help you; AI in production, automate routine tasks. But pushing up that value chain is, how do you get it to deliver more experiences, broader services, and really test what it can do, and even in creating content as well. I think a lot of businesses are thinking through the commercial application of it right now.

Wright: 

And actually, you’ve just touched on a couple of very important things there that obviously link quite nicely into the remit of HR. So we’re talking about things like experience, automation, and data insights. I’m wondering: how are AI and ML reshaping the role of HR leaders within organizations?

Charbonnier: 

Well, I think technology’s been reshaping the role for a while. And I think the way it reshapes our role really has three different components to it, or hats we wear, right? One I mentioned already, which is the commercial use of any new technology in AI. So what are the capability requirements for your business? How do you want to organize around that? Getting involved, even on the implications as we create products and services around the pricing, impacts of the use of it. The best HR leaders are really at the forefront of the commercial agenda within their organization. That’s one way. The second role, and one we’ve always worn when it comes to technology, but maybe we don’t talk about it so much when we’re talking about AI, is the role of governance. What is the code of conduct? What is the acceptable use of it?

How do we make sure our customer data is secure? If someone violates our policies around that, how do we address that in the workplace? So if HR leaders aren’t talking to their CIO, their general counsel about those things right now, I would encourage you to do so. Think about, we had to put in when we all got laptops or phones—what was the acceptable use? What could you use your company device for? This is similar, but a little more complicated than that. But certainly, I think HR leaders need to be educated around, and have a thought with their general counsels and their CIO partners and their business leaders about, what’s our responsibility in terms of the proper use of it, and to ensure that we don’t build inherent bias in tools that we’re using. So there’s a lot of, I think, good governance, good code of conduct work. That’s the second one.

Now let’s go to the third one. The third one is really about: how are you using it to do the work of HR? And where are you on the spectrum in terms of using it in your own HR processes, and what business problem in HR are you trying to solve? It’s also a really important discussion to have. So those are really the three hats I think about when I think about: how do emerging technologies—in this case right now, AI—change the role of HR, the commercial impacts of it,  and the code of conduct and governance impacts of it, and then how do we use it functionally ourselves?

Wright:

I imagine too, that that is having quite a profound impact on your relationship as CHRO with those of your colleagues across IT, or finance, for instance. Based on your own experience, can you share a couple of examples of how this is changing your relationship with your colleagues in the business?

Charbonnier:

I think so many problems today are collaborative in their nature. CHROs today and HR teams need to have a really tight coordination with their CIO and legal functions on many fronts. This is just one more thing that we do together. And I think that thinking about how you team on these things—how does everybody learn, how does everybody get up to speed—because every function that we’ve been talking about needs to have a point of view, but we don’t all start with the same level of understanding on the issues, the complexities, the topics. So it’s really important that you first create a common foundation, and then a discussion about risk, so that when your cyber team or your data team, data privacy teams or your HR, your finance teams are having a conversation together . . . At Kyndryl, we talk a lot about being devoted to shared success and having a real common shared understanding of the state of reality.

And sometimes on these new topics, that takes a little discussion to get going. I think one thing HR leaders can do to really help is say, “Okay, let’s come together and just learn for a moment. Let’s all have a common understanding of the issue and the implications, and then create an atmosphere where everyone can bring their functional expertise to evaluate the issue at hand.” Because these are often very multidimensional, and it matters if you’re dealing with employee data or customer data and how that AI is going to be used in those cases. So it’s really important to have a really good understanding of the issues.

Wright:

It’s a good point actually, because Workday research also showed that actually, 2 in 5 HR leaders say AI and ML will enable their teams to deliver more strategic value to the business, which it sounds like is a big part of this. How do you think AI and ML are already starting to affect your own HR practices?

Charbonnier:

A lot of it has to do with, one, just really understanding your technology stack as . . . starting the journey. We became Kyndryl. We’re world’s largest start-up that’s about to turn two. And part of our first two years have been really rebuilding our HR processes end to end. And we did that for a couple of reasons. One, we want to better serve our customers and think about a world where you have 60 legacy systems, 5 data lakes, 4 or 5 handfuls around the world of entities that you work with that should be on your platforms but aren’t. So we really had to totally reimagine and rearchitect our HR technology stack. We’ve renovated everything, from payroll to all of our core HCM processes to our HR processes. One thing that happened to us is that the repository of skills was still attached to our former parent.

So we had this burning business need when you sell skills for a living, to get all of that information into our new platform, which happens to be Workday, and be able then to use the benefits of really having end-to-end processes and clean data and all of  it in one system so that we can get the benefits of it. So what I would say is the first thing that has to be done is to really understand your technology stack. Make sure the data is clean—you don’t want to run AI off of bad data. And sometimes in HR, I think we’ve been on a learning journey as a function on the importance of it, the hierarchies, the cleanness of it, and getting it into one system. That’s a big step, and that’s not an easy one, because that really allows you to harness the power of AI when it’s running on a really good platform.

Wright:

I thought it was a very interesting trend in the research to see that while HR leaders are certainly alive to the benefits of AI and ML; so in areas that we’ve talked about such as recruitment and onboarding, talent development, as well as things like diversity and inclusion at work, there seems to be a growing concern according to the research about the impact they will have on overall employee experience. So I wondered if we could talk briefly about some of the opportunities you think AI and ML hold to improve employee experience across the wider organization?

Charbonnier: 

Can you imagine nowadays doing your job without a computer? And probably when we first introduced them in the workplace, people were like, “What are we going to do with these things?” But now, no one thinks they could exist without them, right? And I think AI is going to just become a part of the fabric of how work is going to be done, how employees experience their workplace. So I think some examples of where I’d like us to push in the frontier is we . . . Right now being a professional services organization, let’s say, for example, today we’re using AI to suggest employees’ skills. What if we can use AI to help us build teams? Because it understands the geography, it understands the skillset, it understands the industry expertise, and it’s telling a resource manager—that’s what we call our folks who work with our business to staff new projects—what if it could prepopulate a team for a customer, and then a manager and a resource manager could look at that and say, “Yeah, that works. That doesn’t work.” I think we should always think about what’s the human touch on things where and when appropriate. 

So I think there are lots of ways that, hey, wouldn’t it be great for our Kyndryls out there if we could use things that made them more discoverable to use their skills to further their career journeys? I don’t think that’s a bad use case of it. As well as just how do we deliver services to employees better and better? What if, when we knew you were going out on leave, it could send you all the information about your particular type of leave to explain it to you, talk to you about it? Those are some of the, I think, exciting possibilities that allow us to deliver that service experience. That’s the business we’re in. So I want our service to Kyndryls to be the type of service that we want to deliver back to our customers.

Wright: 

To wrap all this up then, Maryjo, because obviously we’ve just touched on quite a few different areas, what one piece of advice would you give to HR leaders when it comes to standing where they are today and looking out across this AI-enabled future of work? What should they be doing now?

Charbonnier: 

Yeah, let me ground it in the culture at Kyndryl. One of our core cultural principles is restless: restless to continuously learn and innovate. And I think this is an area where, as HR leaders, we all need to be restless. Finding out, reading things, talking to people, listening to podcasts like this, really continuing to press yourself about what is going on in your industry and in your function in HR. I think this is an area where we’ll all be on a steep learning curve for some period of time.

Wright:

I think that’s a great note to end on. And actually some really good points there for our listeners about how AI and ML are obviously changing the HR outlook, as well as the opportunities for HR leaders to be part of the business in new and exciting ways. Maryjo, thank you very much for joining us.

Charbonnier:

Exactly. All right. Well, Megan, thanks for inviting me, and great to be here with you today.