Michael Fraccaro and JoAnn Stonier on AI and HR Alliance Shaping Work

Siobhan Savage: How are you?

Michael Fraccaro: Good, how are you?

Siobhan Savage: I am great, good to see you, Michael. Good to see you, JoAnn.

JoAnn Stonier: Nice to see you.

Siobhan Savage: Welcome, everyone! Tell you what, folks, we've got a super exciting conversation today. I'm… this one is,, in the top, top, top of the conversations that we've had for our community, so I hope everyone's as excited as I am. I'm just gonna give a little minute just to allow people to get in, get settled, get your cup of tea, get yourself your lunch. And then we'll kick off shortly. Welcome, everybody! Where is everyone dialing in from? Where have we got in the chat? You can see a little bit of Los Angeles. Where else is everyone coming in from? I'm in New York. Oh, London! Orlando! New York? Hey, New Yorker! New Jersey… You got anyone outside of… oh, Paola Lumpur, that's cool!

JoAnn Stonier: Oh.

Siobhan Savage: Thanks for dialing… it must be,, super late for you, right? India, Munich… Well, thanks for joining us, Dom. We'll hope to make this a good one, since it's,, probably,, 2 in the morning for you right now. All right, folks, well, welcome! This is gonna be one of these conversations that I have to pinch myself after, that I got to even be a little part of this topic. So, as you all know, we are living in a once… In a generation shift to work. And every single company right now is hurtling towards AI. And the question is not,, if we're going to do this, but really it becomes about how are we going to build our AI-powered workforce? And how do we do it in a way where we can create really bold strategy around reinventing with AI, but on the other side of that, making sure that we're super responsible, and that we don't leave anyone behind?

Now, today, we are joined by the Dream Team. And it is so exciting to have them here, because it's not often that you get access to leaders this. who have had careers they have had, with the expertise,, both on the AI and the data side, but also on people and strategy and workforce strategy, and bringing them together around this table to help us all navigate how we all help our companies, make sure that we're really bold. In how we reinvent, but also responsible So I would love to introduce you all. Welcome, JoAnn. JoAnn Stonia is the Fellow of Data and AI at MasterCard. Welcome to the conversation, JoAnn. We're so grateful to have you here.

JoAnn Stonier: And thanks for having me. It's really a pleasure to be here and to be chatting with you, Siobhan, and Michael. Michael and I go way back, but we don't always get a chance to chat in front of everybody, so this is great fun.

Siobhan Savage: We invited 400 people to come along for that conversation, JoAnn. And we've recorded it for those who couldn't make it as well. And a massive welcome as well to you, Michael. Michael, I've tracked your career, my whole career, so to have you as part of this conversation,, is a personal privilege for me, but also for everyone else on the call. Michael is the fellow and former Chief People Officer at MasterCard. Welcome to the community, Michael.

Michael Fraccaro: Thank you, Siobhan. Thanks for pulling us together, and yeah, it's a great privilege and honor to be here with you and JoAnn, experts in this particular field, so really looking forward to the conversation and see where this goes, and to answer the questions. And actually, when you do these, you actually learn a lot as well, so….

Siobhan Savage: 100%. My knowledge base and expertise base is just hanging around with smart people, has made me get further in my career, so the more we can do of these, the better. We've linked, their bios into the chat as well. Folks want to just check out their incredible careers. We also are encouraging folks, this is a really,, dynamic conversation, so any questions,, we're going to keep an eye on the chat, we're going to make sure that we can get as many of your questions answered as well, so try and participate as much as possible. So you heard me framing this to start. So there's … the way that I see the world is there's two parts. There's one part about,, the reinvention of a company with AI. So we've got this one side of the coin where,, every CEO, every board, every leadership team right now is having this conversation about how do we do that?

How do we know what AI to use? How do we know what are the implications of using AI? What are the risks? And how do we really reinvent our work in a way with AI? So what we're going to really do is focus in splitting the conversation into two topics. One, that really bold side, where we're doing workforce,, the work reinvention, and then on the other side, we're going to talk about, okay, so if we take that action, and we look at,, reinventing our work, and using AI, and really creating that force multiple in our organization. What does that mean for our people strategy? And what does that mean for our people, and what are the things that are going to be really important? And I hope everyone's got their notebook, because,, there's going to be a lot of,, magic that's going to come out of this conversation about,, things that you really need to think about.

And I'm really inviting on you, Michael, and JoAnn, really just to be brutally honest about some of the things that you see that,, work, some things that don't, and,, really, everyone is here to learn. So really helping us point us in the right direction of where to go. So, JoAnn, I'm gonna start with you. I mean, from your perspective as a fellow in AI and an expert in all things data, when it comes to,, your priorities and the priorities of your executive team. what… what are they thinking about? What is the conversations that are really happening at that level when it comes to AI?, where are we at the,, as an industry?

JoAnn Stonier: Yeah, sure. So,, when you think about how AI has become upon us, really, from generative AI jumping on the scene in late 2022 and early 2023, I think what everybody is recognizing is that it's a real transformation moment, right, for all sorts of organizations. And depending upon your organization or firm, you can be anywhere on a transformation journey, right? Because it's a transformation of your business strategy, perhaps. your data strategy or data strategy. I'm going to say data, because of where I come from, right? And then, how do you use AI to continue to transform your company, your business, in this moment, as you look at where do you want your firm to go, right? MasterCard is a payments organization, right?

We're a technology firm, we're a data firm. And we want to make payments safe, simple, and smart, but we do so many different business activities, and while we'd been using predictive AI, we also had to start thinking about where was generative AI going to take us on a journey? Where did we want to go from a business strategy? And then how is AI going to transform us From not only our business practices, our products and services and solutions, but then all of the enabling functions underneath that, which includes, of course, human resources, but it includes our technology platforms, it includes financially, how are we going to Keep our company moving and growing from a business perspective, as well as an investment perspective.

And so even if you think about departments legal, legal has to transform for this moment. So there's so many moving parts, right, that executives have to really think through. And while we've had a few years, I think some organizations recognize they have, well, they have technology debt that they have to fill, they have data debt that they have to figure out what data are they going to use. And certainly, they have to train up in different aspects of people, process, and technology for AI itself. And so we're at this moment right now where executives need to step up and recognize it's a moment of really significant change, and while they're feeling it at the top of the house, certainly the rest of the organization is feeling that as well.

And so, everybody's gotta be ready for new thinking, new products. new ways of working, which can put an incredible amount of pressure on all of us, and we have to recognize that we're in this transformation moment, and really take care of all of these things all at once. So that's what I think most executives, as you started, are worrying about and trying to navigate. not only the CEO and the executive team, but all leaders throughout an organization, and then, of course, all employees that work for all of our firms.

Siobhan Savage: I mean, I've got a follow-on question, if I may, just on the executive side. Sure. What typically is the outcome really the leaders and the CEOs, is it velocity, productivity?, is it more innovation?, what do you typically see, JoAnn, as the underneath all of this that's happening right now that's creating this,, sense of urgency?

JoAnn Stonier: Sure. So, I think most organizations, when they looked at,, this very big agenda, did a couple of things. First, they looked at efficiency. So, we talk about the… from a data perspective, we call it the defensive use of data. And why did they do that? They looked at, well, how can we use AI data for efficiency plays? Why? First of all, I can do that behind the scenes. I don't have to be very public about the changes I'm making, and it allows an organization to experiment on its own processes to improve them. And it also then allows an organization to learn, right? So there's two things. It allows experimentation, it allows for learning, and then it allows for more efficiency, which CFOs love.

Because then it gives some bandwidth for the next phase, which is product extensions, looking at the current products and services that a company has, and how do we improve them? How do we surprise and delight our customers, increase personalization, go deeper on the data set. do better in our product interactions with customers, right? And go from there to then the leap forward to innovation. And so, depending upon your company or firm, usually that's the trajectory that we've seen companies use. So, first on the efficiencies, next on product and service extension, and then this next wave of innovation.

Siobhan Savage: 

And we've got a question from George in the channel as well., who do you typically see leads these AI projects?, where does it usually come from? Because in most companies, it can come from different places. What do you typically see?

JoAnn Stonier: Yeah, so there's lots of different use cases, right? So, oftentimes there's a lot of excitement, a lot of different, employees want to participate in developing use cases, but what we're seeing is a need for AI governance. We call that AI governance so that organizations can vet,, which idea should we go after first, right? What should we do first, second, and third? Typically, we have an AI or data officer that will lead the governance process, but the governance council is made up of executives from across the firm. It will include your technology team, it will include your privacy and security team, it will include people from your product and sales teams as well, to make sure that we're understanding all the different attributes.

In some cases, it will include your marketing team, it might include.

Siobhan Savage: Who you're.

JoAnn Stonier: HR team, depending upon the type of company that you are, in order to make sure that we are prioritizing things in the right way, for the right return on investment. also to understand how big a change is it? Is this something small that we can do quickly and spin up that might be really fun for the organization, or that's something we can learn on quickly? Or is this going to be a significant investment that we need to do in phases? So that's the type of council that's usually spun up, but it's usually under a chief AI officer, or in combination with a head of strategic planning.

Siobhan Savage: Given that there's so many different teams that are getting involved, and it feels this… it goes viral in companies, where everyone feels that there is a conversation that they're wanting to have. what is your,, thinking around why,, bringing the AI teams and the HR teams together is super important for you?, where do you What do you think the connect is, and why do you think that?

JoAnn Stonier: Well, if you… if you think about it, companies are filled with people, right? And I… I love this idea that we all think that,, companies are the… they're these artificial people, but they're made up of all of us. And so, if your AI team isn't really thinking through the people aspect. well, who do you think is doing the innovation? Who's doing the learning? Who's doing the new product development, right? It's going to be your employees. And while you may have a centralized AI team, or maybe you have a data science team, or maybe your technical teams are better versed in this new science of AI, or generative AI, or agentic AI, the implications go. widely through your firm. So everybody needs new baseline training, just we all did when we first got,, computers, or when cell phones, right?

Or when we all went virtual,, during the COVID-19 virus, right? Everybody's skill set needs to have a new baseline. So who better to partner with than your human resources,, team to begin to think through How are we going to approach this? Because how… we can't disrupt our entire business, but we need to start prioritizing the new training and the new skill sets. And then certain teams need to have their skills accelerated, right? Even though they may have some skills, they may not have all the skills. And then there's a learning journey. That everybody has to go on as the technology continues to change and increase. And then, of course, HR itself is going to be applying these tools, right? Because we already know that many HR teams, and I'll let Michael talk about this, have used AI in the actual people journey itself, in hiring, right, in evaluation of teams. in trying to determine performance, right, in efficiency of teams, and in actually planning out what does the organization of the future need to look, AI and HR teams need to work together to figure out that puzzle as well.

Siobhan Savage: Michael, what's your take on the other side of the table?

Michael Fraccaro: I feel ….

Siobhan Savage: But bringing the two things together.

Michael Fraccaro: Whenever I hear Gianne speak, I'm just always mesmerized. And I think she's positioned extremely well. I think,, a couple of things. One is, as we think about AI, and particularly at MasterCard and other organizations, I think this is really a transformation, and we have to think of it in a couple of ways. One is around, how does this. How does AI fit with your overall business strategy? And,, if you take that, what does it mean also for your people strategy? And then the second piece is really around what are the people and culture implications as well, as you think about deploying AI across the organization. So, I think that's a really important point. The other one, just as a bit of an aside, if we think about this conversation, this isn't about a technology conversation, but it's how we drive change, as we think about workforce planning, or some of the examples that JoAnn mentioned about how we think about commerce, how we think about customer experience, how we think about education.

I mean, there's so many aspects to this that it's a significant change, and it's not just a technology, it's all of these other components we need to think about. Last week, as an example, I was down in Africa. And if you take Africa as a continent, it's predicted or projected to grow by another 800 million people, over the next few years. The median age is 19, and if you think about access to, capital, so financial inclusion, think about digital data protection and fraud, that's an important aspect. And if you think about access to education, particularly as you've got a young population that's growing as the economy grows, we need to provide them with skills. And so, there's a ton of Specific use cases that we're already looking at in that particular content.

And then you've got other more mature markets, where you've got aging populations. So, what are the implications and what are the use cases for AI, where you've got economies that may be slowing down, as well as you're not going to have as much new entrants into the workforce because of their population growth stagnation. So, a lot of really interesting aspects there. And if I think about,, again, coming back to the HR, conversation. When we think about employees as well, they're obviously going… we see data, and we see reports about employees are anxious about.

Siobhan Savage: Hmm.

Michael Fraccaro: What's going to happen as a result of AI. I think, to a large extent, if I think about our own population, less on the anxiety, but more on the curiosity, aspect. So, show me what does this mean? Teach me how this is going to make a difference in my work. And I think we need to be thoughtful about how we turn that cautious and curiosity into something that's really productive and meaningful, and that's the cultural aspect. And here, there's another dimension, which is around what role does a leader play in demystifying some of these aspects about what AI is and isn't. And I think that's a really important part, and the role that HR plays in actually helping be the steward in navigating the organization.

Final point would be, there's a lot of conversation about who owns this? And I think that point about this has got to be collaborative, it's got to be joined up, it's got to be a convergence of all the different skill sets across the organization, but HR does play a critical role, and if you're in a key role within HR, and I would assume that everyone, if you are in HR, or even if you're in some other area of the business. this is not a time to wait to be asked, it's really to come forward and step in, and highlight what are the insights, and what are the areas that you see opportunities, and really help, be part of the dialogue. I think that's a really important part of this.

Siobhan Savage: Hear, hear. I'm, yes, yes to everything on that. One of the things that you've said I just want to touch on, because it's probably one of the things I get DM'd about the most, is,. what's gonna happen to my job? all the data in the world about career,, what's gonna happen to me? And I think one of the reasons why I personally invest so much time in the community stuff about,, bringing these two conversations together is,, if Michael is going to communicate at skill. he needs to be in lockstep with JoAnn and know what the actual plan is, where are you thinking about going, how is it going to evolve?, you're not going to overnight completely transform the whole company with AI. So, there has to be, and I can see there's a question similar to this in the chat as well, it's the phases of which you'll go through whenever you're starting.

So, JoAnn, you're probably the best person to answer this, but when you're looking at the AI transformation strategy. We're not crazy to think it's not going to happen overnight. What do those phases look? And then Michael would love, then, you to go, okay, and at each step, then how would we think about then communicating so that our people know,, transparently as much as we can share? So JoAnn would love, love a little bit of,, how would you think about,, that transformation journey playing out?

JoAnn Stonier: Everybody thinks it's. journey. And I think that's maybe also….

Siobhan Savage: Did your volume disconnect? You sound a little bit quieter than you were just before.

Michael Fraccaro: There you go.

Siobhan Savage: Oh, there you are, you're back!

JoAnn Stonier: Okay, okay, sorry guys. I think everybody thinks that it's going to be one journey, and I actually think it's a lot of journeys, and I think that's the first thing that everybody's got to realize, that And I think part of this was the excitement of generative AI back in 2023. We all thought that it was all going to magically happen super fast. And it is faster than any other technological transformation, for sure, but what we're going… what we're typically seeing in companies is that it's a series of transformations as you prioritize, right? And if you think of every AI project, okay, that a firm undertakes. typically, it surrounds itself with four phases is right, but the four phases are design phases, right?

So first, we have to discover. What are we trying to solve for, right? What is it that we're trying to apply AI, and is AI the right tool? So there's this discover phase. And then define, right? Define exactly the problems we're going to try to solve, what are the solutions we're going for? Do we have the right data? Do we have the right tools? Do we have the right talent? That's one of the places where HR is key. key, right, to that conversation, in the same way we need to make sure we have the right technology. Do we have the right partners, right? So there's… and there's a whole host of new skills that we need to start keeping track of, right, as we assess these partners. I mentioned legal before because so many legal departments have been approaching me about retraining lawyers to be able to negotiate these contracts and skills that we need partners, right?

Then we need to develop, right? That's the third time moment. Where we're going to actually develop this new process, this new product, this new way of thinking, and then we're going to deliver, but deliver is no more just, oh, we're delivering a product. With AI and generative AI and agentic AI, there's constant monitoring, there's constant intervention, and so there's a whole host of new skills in the monitoring, the auditing, the adjustment, the fine-tuning, that we're also not exactly used to in the way we typically used to manufacture or deliver, right? And so we have to think about it a little bit differently. And so if you start thinking in those four phases over and over again in iterative loops, it begins to be clear that it's not one phase.

It's a series of phases that firms are going to get better and better at as they go through this transformation journey. So that's the first thing I want to say. Next, as we start thinking about how we're going to collaborate to be effective. We need HR leaders to begin to skill up, just the rest of the organization. You and Michael mentioned, I need a partner who's going to be able to be my people expert on this journey, because if I'm going to be the head of AI, I've got to be thinking of all these things, but I need somebody that I can hand off to the skill sets, and say, Michael, can you start thinking about how do we do a transformation journey on skilling? And how… and I, in turn, also have to point out what's ahead. as we start asking our employees to create agents, and we start thinking about a hybrid organization that's people and agents., together, we have to design that together, right?

And we have to use these four phases as we think through, well. When's that gonna happen? And in what teams are we going to deploy that? what… where can we begin to do what we call at MasterCard, proof of concepts, right? To test things out. All of that requires,, design thinking and key partnerships to start thinking through all of the changes that are going to happen. So there's all these small projects that begin to… I don't know how to say this, stack up into a significant amount of change, and plans for the next year or two of the transformation that we're seeing at MasterCard and elsewhere.

Michael Fraccaro: Yeah. Yeah, I'll just build on that, I think, and there was a question that popped up in the chat while Joan was speaking, but that point about change, this is a significant change management challenge, right? And all of those aspects are really important as a business partner to help the business navigate through all of the different components, because there are multiple work streams, there are multiple touchpoints, and overcoming some of the first piece about the anxiety and so forth, but more importantly, what are the… what are the areas of the business that we're really focusing on? So, coming back to, I guess, the question you were asking to JoAnn from an HR perspective, if we think about the language of, the business, what are the key drivers?

Are we looking at these tools to drive efficiency? Are we… do we have a cost question or challenge? Do we have a revenue, opportunity that we're looking to unlock? Are we looking at reallocating resources to areas where we're looking to grow and invest from a business strategy. And I think at the moment, how a HR professional starts to navigate those questions, it's a very manual process, and I'm encouraged that now there are potential platforms that are helping navigate through those kinds of questions around what does workforce change look? How do we actually assess this? So, if you take the example of, in the early days,, you're looking at wage arbitrage, you're saying. where can I find high-skilled talent that meets my business needs, but in high-value locations?

And you start to look at where you reallocate your resources, and you de-risk of having an over-concentration in one location or country, whatever. I think the same thinking can apply to this, is looking at your various job families, and start saying, of these jobs, what are the potential tasks or activities that could be, moved to an agentic AI? What would that look? And therefore. are we increasing capacity of those particular, jobs now because you're freeing up capacity in a different way, but you need a starting point, and I think that's the part where HR leaders, we did in COVID, we didn't have a playbook, and I think now we need to co-create what this playbook looks to give practice.

Siobhan Savage: Yeah, no.

Michael Fraccaro: Tools to be able to have that conversation with the CFO and the business leaders as well. Your AI partner, right, needs to be able to help create those models.

Siobhan Savage: You're quiet again, Juwan? I think your mic's disconnected again.

Michael Fraccaro: Yeah, there was nothing… here we go.

Siobhan Savage: Oh, you're back, you're back, it's the AI!

JoAnn Stonier: It just takes a minute.

Siobhan Savage: Agents.

JoAnn Stonier: It's not real JoAnn, it's a digital clone. I think it takes a minute for my microphone to catch up with my speaking, but….

Siobhan Savage: It's my brain and my voice.

JoAnn Stonier: I think it's so important what Michael is saying, because what we need is AI partners to know what HR needs and create the models that are needed, so that we can do the modeling together. Because there's so many… there's often times when we need to know, what is the information that HR needs? How can we assist in creating a model that will help dissect how do we make these decisions, right? As we look at the different tasks, right, everybody's so worried about,, my job is going to be out,, is going to be,, taken over by AI, when actually what we're trying to do is disaggregate tasks that can be done agnically. And then, to Michael's point, free up the time. But here's going to be the challenge.

It's going to be a little bit of time from this person, and a little bit of time from this person, and how are we going to reimagine, then, the organization so that time, right, becomes available In a person, and that we deploy our people well into tasks that are really, first of all, enjoyable, part of the job, and also that we understand how, potentially. different teams have to work better together. So I use the example of,, marketing and finance may find themselves needing to partner differently in the future. Because their agents cooperate better. So those are the things we also have to start planning, and there is no playbook for this. It just requires constant work together.

Michael Fraccaro: Yeah.

Siobhan Savage: I had a conversation with a leader the other day, and they said that they didn't think AI would be a thing happening to their business for 5 years, and I was, what?, where, what, what?, I don't think you're gonna have a job if this keeps continuing. But this is the thing, it's, to your point, JoAnn,, the businesses have already been in that early pilot-y POC phase, and it was all test and iterate, and they're building that muscle. That is going to enable them to be able to look at this at an enterprise-wide approach, so that they can become very focused on,, where they're going to focus their energy based on where is the work and the tasks that have the greatest opportunity to be reinvented.

And then what agents are there you gonna use to,, really add value to that work? And then how do we think about the reallocation or the re-engineering of that work so that,, your employees can go to more higher value work? And that's a lot of what we're seeing happen in the market right now, is what you were saying, is that,, journey. And the other thing, JoAnn,, before we hand over and talk more on the people side, one other question on the agent side., given the agents are at,, they're still early in terms of,, this is not fully fleshed out yet, and at the rapid pace that transformation is happening, and the advancements of this technology. is it fair to say that we're gonna be in transformation forever as companies??, are we gonna be just… is this it?, we're just gonna become re-engineers, and that's reworking, and that's how we're gonna do it?, is that true?

Is that… am I wrong?

JoAnn Stonier: I don't know. I don't have a crystal ball either. But I do think this. I think….

Michael Fraccaro: Your volume again. Whatever, whenever….

JoAnn Stonier: I don't know what I touched, does that.

Michael Fraccaro: Oh my god.

JoAnn Stonier: Can you hear me? Yes?

Michael Fraccaro: Not really. Pretty fun.

JoAnn Stonier: I don't….

Michael Fraccaro: Alright, there you go, you're back.

JoAnn Stonier: I'm back. Okay, I'm back. I don't know if we're going to be in transformation forever. I don't think so, because I think eventually this will feel the new normal, right? That we constantly are upgrading ourselves. But what I will say about agents is this. Agents are starting out small, we think of them as small, but I also use the example of Waymo, the driverless car, is a series of interoperating agents. And so agents can be very sophisticated, so I just want everybody to understand where we can go with agents. can actually drive cars, right? But they still have a supervisor. They still need somebody monitoring how they're driving, and are there for,, instant assistance. And so, what I think is going to happen is more of us are going to be able to design agents, more of us are going to be able to understand how agents work.

And what I would say to everybody is, as our skills move up the curve of AI, and we're better and better at using it, I think that's the transformations, but they're going to feel small, just in the same way that we now use AI to check our documents, review our presentations, right? It's part and parcel of our everyday. I don't think it will feel quite as big a transformation. I think it will be constant transformation, but at a scale that we're much more comfortable with. That's what I envision.

Siobhan Savage: And with that, Michael, in mind,, how do you,, for an organization of your skill, complexity. how do you design a workforce transformation strategy?,, what's the key blocks that you're thinking about around,, we're moving in this new direction, what does that mean?, where do your head sit with your team when you're starting to rethink how to design for that world?

Michael Fraccaro: Yeah, I mean, a couple of things. One is,, starting at the beginning to really think about how do we integrate AI into the people strategy. So if you take even just at the most foundational level, what are the processes and activities that we currently have that can still provide … a great employee experience or a candid experience, but still with the human in the loop,, still with the human involved, because I think some of the pieces that JoAnn has done a lot at Mastercard is really around data principles and governance and compliance, all of those guardrails that you need to have. I think it's a really important aspect, that even within HR, we need to continue to, ensure that whatever tools we're deploying, there is,, you're accountable for whatever it is., if you're bringing in a third party, you're accountable for whatever the outcomes are.

So I think that's an important part of it. The other piece is around, beginning to think about this macro. So, ones the day-to-day, just looking at the here and now, what we can do and change, and what are those use cases, so things,, scheduling for candidate interviews, all those kinds of things that I think many organizations have already done, and these tools are really helpful in doing that. We've done things internal talent marketplaces, matching people with their skills and mentors, or job opportunities, or projects, and so forth. But this next, more meaningful change is really that point, because I think at the executive table, and at the boardroom level as well, questions are now being asked is, okay, we've heard about all these things happening about AI, but what is it that we're doing transformatively for the organization that's going to,. hit some of these key business drivers that we mentioned earlier.

Revenue, efficiency, cost, whatever it may be, productivity, whatever they are for your organization, it's really important to be able to answer them. And from an HR perspective, it's beginning to break down what skills do we need What jobs do we have that actually, if we break it down in terms of the tasks, that could be done, more effectively. by an agent that can actually reallocate those resources to other things. Noting,, the point that JoAnn mentioned earlier, but some of this may be, passed out, where you've got to find, then, what's the critical mass that actually gives you the benefit. But those things are beginning to happen now, and I think even directionally, it gives you a starting point to start having that dialogue to say, hey, if we look at an analyst job, or if we look at a customer operations role. here are 10 tasks, or 15 tasks that they have in their job description that could be solved by an agent.

That's actually meaningful conversation, because now…. a dollar figure, and actually say, if we look at this, and then that's the part of the org design and thinking through some of those aspects that Joe mentioned, that's where you start having a real dialogue, and that's where you can affect change. And so, that's a big part of this conversation as well. And I think,, HR can lean in, to go deeper in these particular pieces, and I think it's really important. The final part would be around,, how are you measuring, and accountability as well. So then that's that whole piece around how do you… how do you measure the return on investment? What it is that you're setting out for, and having that up front, and then the governance structure just to make sure that you're staying on track as well.

So they're the key things that I would say. Are important to kick off this journey.

Siobhan Savage: One of the things… Yeah, go ahead, John.

JoAnn Stonier: Yeah, can I add one other piece to this journey? Because I'm very aware of the emotional moment that I think is real for our employees, right? And we're also living in a time where,, we read a lot, I read a lot about,, people feel isolated, they don't feel they're part of communities. And, AI can also strengthen that, right? There's all sorts of chatbots that people are talking to as… their therapists, their best friends. I read a scary article in Wired last week about,, you can have a relationship with a chatbot or an agent. And I think we have to recognize that all of those people are our employees, and that our employees, need a sense of community at this time of change. And, and because emotionally, all of us are going through the change, okay?

So please know that. But it is different for some of us of different, age groups, of different, bonds in companies. Of different employee groupings,, whether they're working in office, or they're virtual part-time, or they are,, full-time people, or they're in a call center, or wherever they are. And I think as leaders, never mind as HR leaders, we have to have a fair amount of emotional intelligence as we talk about the change, because we need to tell them we're changing too, right? That some of us, I mean, I'm on the longer end of my career, right? I've had to go through several transformations in my career, right? I mean,, there was… this device, this device was not given to me upon college graduation.

I don't know about Michael, but I did not.

Michael Fraccaro: 

Not?

JoAnn Stonier: lovely things. And so,, that changed how I was connected all the time. That was not the norm when I graduated, and got my bachelor's. And so, talking about some of those transformations, as old as that might make you, and how organizations try to work together for transformations, I think are an important piece that we have to recognize that there's a very human element in the midst of AI And Michael knows this, because I'm the old privacy officer for the firm as well, that if we design with people at the center, we 9 times out of 10 are going to get it right. But when we design for everything else, and we forget about the people at the center, we sometimes,, we forget about them. And I think this moment in particular, because everybody's going through it in different ways, we need to just be mindful of the emotionality of all of it.

Michael Fraccaro: 100%. 100%.

JoAnn Stonier: I mean, you've spoken a true leader., generally, that is….

Michael Fraccaro: Yeah, I mean, all this HR, all this HR, it's actually worked, it's worked.

JoAnn Stonier: If it's.

Michael Fraccaro: No, it's this work, but it is… it's so true, it is so true, and I think the,, the technology and the AI literacy, they're one component, but this is… this is,, there's ethics around this, there is… Systems thinking, there's, anxiety, all those aspects, and we need to take people along the journey with us. And not leave people behind. I think the aspect that, HR can also lean in on is making sure there's a level of transparency in how you're thinking about this, and also saying, I don't have all the answers. I love that piece around, I'm on this journey, too. And if you can model curiosity and your own learning and create space for people to,, demonstrate their questions and their… I think that's a good place to be, for sure.

Siobhan Savage: Yeah. One of the things that's really interesting is,, and that I've been banging this drum for quite some time, about the language of work between the business and HR needs to be the same.,, people have skills, absolutely, but jobs and work have tasks. And in order for us to really be highly valuable in the JoAnn use case of,, where am I actually designing for? I need to be able to understand what is all of the work that's happening within the organization, and what work has the highest value opportunity. And it turns out that HR are sitting on a gold mine right now of data which understands a lot more about the actual work and the way that we describe work within the organization. And I think, Michael,, one of the things that you and I have talked about over time is this evolution from,, the skills and tasks movement, where we need to have this new language so that when we're talking to JoAnn, that we're not talking about it in the HR context, we're talking about it in practical,, here are the tasks that are operational right now, these ones have high value for AI, and here is the opportunity for you, JoAnn, to then allocate agents that you may have already internally that are able to do these, and this is that bringing the theory and thesis to life in terms of the way that,, that we're reinventing, right?

I mean, Mike, what's your view on that, right? You've been on that, right?, with us in terms of the tasks.

Michael Fraccaro: Yeah, no, that's exactly it. I mean, some of that work that we've,, done with you and Microsoft and others is to really start to test this out,, looking at particular jobs, breaking them down into,, what are the tasks, what are potential options of those tasks to be done by agents, and then obviously,, what's the cost avoidance, or what's the investment, what are the cost savings, and so forth. So, I mean, that's a… that's a great starting point, and I think… There's some of the insights that I believe HR can bring to the table to start having those conversations, because whilst that may be,, level one, there is so much else that needs to go into that conversation., what is the context for change?

Where would we reallocate? how long will it take to,, re-engineer these particular jobs? And if you think about the role of the leader, and the workforce of the future, the workforce of the future will be,, a combination of full-time employees, part-time employees, gig workers.

Siobhan Savage: Yep.

Michael Fraccaro: Vendors, agents, and fellows, JoAnn and I. I mean, that's… that's what the workforce is going to be, and… and I think having a much more broader view about workforce and workforce planning and the skills that you need to, again, support and drive your strategy are just such important elements of the language. that we need to have, and I would say that if we think about skills, the one skill, apart from the technical skills of,, AI literacy and so forth, but this ability to tell the story. and convey the story, and that, that intuition that you bring with humility, I think is just such an important part, and it's an art, but it's a… it's a skill that I think is going to be called on more and more of our leaders around how you craft that story, depending on the role that you're in.

Siobhan Savage: The other thing I think that is… becomes really important when you stitch the two parts together, on one side, it's, I understand my work, I know intelligence for where to take action, so,, that GPS of where to go, and then I know what agent to use. The thing that becomes really important is,, what are the skills our people need? to be able to use the agents, because if the employees do not adopt this thing, we're gonna have a problem of adoption, right? And that's one of the things we see across multiple,, big clients that we work with right now, is that you then deploy the agent, and you put it out there, and what it's! It's, okay,, change management, people!

JoAnn Stonier: And they also have to be able to supervise these agents, right? So it's not just that they have to work alongside them and agree that they understand what they do and what their use is and use them. But whoever's,, supervising that combined team, they have to have a fair amount of AI knowledge to know, is the agent doing their job? Is that the right answer? Have they gone off script? Have they started… is the model started to drift and do some funny things? Learn some bad behaviors from the interactions that it's had, right? And so, all of that is also going to be part and parcel now of management's job, right? So, how are we getting ready for those moments, right? So, it's not only, right, that team members embrace the use of the agent in their jobs, but then who's managing and navigating the team also has to embrace it and be able to supervise it, right?

Because it's not going to be the AI team supervising all the agents. They'll be exhausted. It's gotta be in context, right? Because only in context can we really do the evaluation, so… It's going to be a very different, future workplace, for sure.

Siobhan Savage: And Nicole has a really good question, Michael, and I think this one's more… more on your,, area,, how do you assess employees' capabilities to use the AI? Nicole, tell me if I haven't seen the earlier question, but I'm assuming the question is all around,, how do if your people are able to use the AI, and what skills they're going to need to adopt AI? How are you thinking about that in MasterCard more broadly?

Michael Fraccaro: Yeah, I mean, we've been on this journey the last,, 2 years or so, but,, even if I just take some data points, when we do the employee experience survey, we've seen in the last 12 months, a 17%, so close to 20% increase in terms of our employees' aptitude, in terms of feeling more comfortable with the use of various tools, and that's because we've been very intentional In the training, in the awareness, and the deployment of tools, and we've identified particular use cases in, say, our consulting business, or with our software engineers, or parts of, HR and legal, where we're really taking people along, and demystifying a lot of the concerns that people may have had at the beginning. So, there are… there are ways in which we're doing it.

I think the big question now is,, coming back to the point around what skills do we have now, what are the options of moving some of these tasks to, Agentic AI, and how do we then reskill and upskill.

Siobhan Savage: 

Hmm.

Michael Fraccaro: the excess capacity that you've now freed up time. So, does the individual, if you're a talent acquisition,, your recruiter, do you now just spend even more time in quality dialogue with your screening or your interviewing of candidates, or do you deploy it in terms of increasing the number of,, jobs that you're now recruiting for? I mean, they're some of the things that we're working through. But that's another way of actually looking at this.

Siobhan Savage: I think is… there's the… the making sure your people have the right skills to actually adopt the AI, there is the reskilling for… let's be real,, JoAnn, if your vision comes to life, and there is going to be rules that are going to have a decent chunk of those tasks go, how do we pivot them into work that we know that MasterCard still requires? And again, Michael, what are the skills that are needed to actually move someone from A to B, and what can they use? And then I think there's a really important component around,, the communication and the change management. So that's all of the… what I'm hearing,, how do I make sure my people have the right skills to operate in this world? And then how do I communicate that effectively, to them?

And,, if they don't adopt it, there isn't no ROI, which I'm assuming, JoAnn, you'll get questions then if you're spending millions of dollars on AI tools and no one's using them, right? So there's this,, flywheel that needs to be in place For this whole thing to really work.

JoAnn Stonier: Absolutely, and I see one of the questions is about,, well, everybody's just going out to the market to hire talent. There isn't enough talent to hire, so…. know that. That's one issue. Yes,, schools are trying to,, adopt and train out new students, but even education has to get,. has a transformation moment of itself, all the way from,, kindergarten right through university, right? So, please know that organizations cannot hire enough talent, so that's not really a sustainable strategy. So, engaging your employees, getting them excited about it, doing this learning journey, and let's face it, the contextual knowledge… I had this conversation with one of my doctors. The contextual knowledge that my doctor has, right, her medical degree, right, and her specialty degree.

She wants to be assisted by AI. I want her to be assisted by AI. But I also want her to use all of her knowledge, right, that she has obtained in her medical career to treat me. It's the same thing inside of our firms. We don't want to lose all of that. But yes, do we want to be more efficient? For sure. Do we want to be smarter in how we're deploying things? For sure. But it requires everybody to run toward this transformation moment. not run away from it, because it's here. It's gonna happen, and it's gonna happen in our day-to-day lives as well. So, I just think that,, that this… if we can get everybody excited.

Siobhan Savage: Hmm.

JoAnn Stonier: Right? Really embrace the transformation. I think we'll have a much more fun time in having these discussions. They won't quite feel so hard, and before it, we will have adopted a fair amount of the change into our daily lives.

Michael Fraccaro: Yeah, I love it, I love it. I think the other point on that one is, last week, there was that MIT research paper that came out that had the headline, right? 95% of all.

Siobhan Savage: Click, click, click, click, click.

Michael Fraccaro: Yeah, click right. that have not shown any, any return on investment. But I think that it goes deeper than that. It actually talks about,, measure, ROI on AI deployment, not just on,, the productivity.

Siobhan Savage: really bad.

Michael Fraccaro: other aspects as well,,, shifting from just, hours saved to new skills gained, or something broader, or,, how you've increased your customer engagement, whatever it may be, but there are other ways of measuring this versus just the productivity, and I think that was a really provocative headline, but when you go into it, it actually goes into a lot more thoughtful detail, which I thought was very great.

JoAnn Stonier: Yeah, it was a.

Siobhan Savage: The mark… the marketing skills were good on that one, because everyone clicked., it did… it did what it was intended to do, right? Because here we are all talking about this, right? Exactly, exactly. And I think one of the things that we've seen, back to a point that JoAnn made, which leads back to the HR capability and strategy, is,, the teams… I mean, when we first started talking to companies, every major company in the world said, we're gonna build it all ourselves, we don't need any outside vendors, everything is going to be built in-house, it's going to be amazing. And then they realized how expensive it was, and they realized that they couldn't find any talent, and they realized that they were going to have to think about what do they build versus what do they borrow, and really, from a talent strategy, JoAnn,,, when you think about,, that would have caused absolute craziness for talent teams to go out and try and find and fight off Facebooks and all of the other,, open AIs of the world who are all competing for this talent, as everyone's probably seen in the news, right? ….

JoAnn Stonier: We looked, everybody looked,, can we build a model, right? I mean, MasterCard has a lot of data, we looked. But the problem is, even as much data as we have, and it's good for lots of things, let me first be the first one to do a commercial for our data, right? It's very good on lots of different dimensions. it's not enough, right? You need so much data to build the baseline model, but it's very good for certain things. And in partnership with firms, we can do a lot with our information. And that's true for lots of different organizations, right? So yeah, build versus buy is always a big thing, but we're going to partner in different ways. We're going to build different kinds of ways of thinking.

It's an exciting time if you can get out of that, we have to do it all ourselves mentality that I think many, many organizations are used to, right? They're used to going it alone, and now, I say it all the time, I think partly for MasterCard, we've had a leg up because we operate an ecosystem, right? We've always partnered with our banks and our merchants and governments, so we're used to this partnership idea once we realize that, oh, maybe we shouldn't build everybody else. So, it's the same even for us.

Siobhan Savage: Michael, you would have seen the… it hit your talent acquisition team, it'll hit your reskilling and learning strategies,, it's this… I think when people think about AI, they think about the tool. and not the use of the tool and the impact of what is required to enable the tool, because the tool is just a tool, right?, unless you put all of the wrapper around that,, so has that flowed through your thinking when it comes to your total, I suppose, people strategy, right? When it comes to all of the elements? How have you thought that through?

Michael Fraccaro: No, absolutely. I mean, this… this can't be seen as just,, an AI adoption strategy. This is a workforce transformation. So all of the things, how we're thinking about,, employees resolving their questions on their benefit plans, or, the talent acquisition, how we're… being able to screen passive candidates, all those kinds of aspects, I think are really important, and it's got to be built… it's got to be integrated into the people strategy. It's not a standalone. and just have a bullet point, AI is over here., a full… transformative approach to the way that we're going to work in the future. This has just got to be embedded. It's just internet is, just electricity is,, we don't think about,, turning the lights.

It just happens, and I think AI, that's the point that JoAnn was making earlier. This is an iterative process, and whilst we're… we're at that,, we're getting to that peak of change and what we need to be thinking about. There will be a point where we will become so adept at it, it'll just be BAU. I don't know when that time frame will be, that's the question, but you can't just wait for the perfect answer or time.

Siobhan Savage: This is….

Michael Fraccaro: got to be part of the journey, just GPS and navigators were, early on. They've just got better and better and iterative,

Siobhan Savage: Yep. One of the things that I've seen,, on my journey is that there's still a little bit of teams off doing their own things. And would love, from both of you, a perspective, so we've got a really mixed community on this call. You've either got,, builders who are re-engineering work, or you've got architects that are re-architecting workforce. And,, on both sides of the coin, it would be really interesting if you could share a little bit about,, how,, could I be useful?, if I'm back in my previous HR career,, JoAnn, how would I be valuable to you right now? What can I come to? If you're off and you haven't been connected, how are you expecting me to show up in that moment? Michael said,,, let's go, let's step up, let's take the moment and actually push yourself forward. what are you expecting?

And Michael, I'll throw straight back to you after as well, from the other side,, how do we think about,, on the CIO, the Chief AI officer view?

JoAnn Stonier: Yeah, so I think everybody is waiting to be asked, right? So I was with some chief marketing officers, and they were, so how do I get asked to be part of the governance council? And I was. Go volunteer. Go chat with the AI officer. Please don't wait for them. They're really busy right now. And while they might love to work with you, it may not have even entered their consciousness that they should be talking to you, right? Because they're struggling with a contract with Microsoft and OpenAI to get ChatGPT in, right? Or to get just,, a simple tool, a chatbot, into the organization. Or they're trying to figure out the platform issues, or they're trying to struggle with their data scientists working on A-B testing, right?

They have so many different They're working at all the different levels, that they may not have picked themselves up to realize. Oh my gosh, we need to be working on the people strategy. And so, if you are in HR, start talking to your leadership about what we've discussed today, that there's changes that need to happen for the organization, and use your relationships inside your organization of what you're hearing from employees, what they want to learn, what they haven't learned. where they're excited and where they're disappointed in what your organization hasn't provided. Let… then bring that to the AI team so you can begin to partner on a program to begin to fulfill those needs. Trust me, the AI team wants to be doing this stuff with you, they just don't always have the capacity, because some teams are a year old.

A year and a half old. Some of them have had massive change in their team as people have come and go, so you've got to also be kind to those people, too, right?, they're not always aware that they should be reaching out to you and including you in the governance, including you in the plans, and then be ready to lead that change. Use your AI team as your key partner, key resource, but you still have the best contextual knowledge about leadership. about people management, about people transformation, right? I would never tell Michael how to be a leader, right? I would… Michael, I would listen to Michael about how to be a leader. Remember that. Just because I have AI and data knowledge doesn't make me automatically a better leader in this moment.

We need all of our HR skills to navigate the organization in this moment.

Michael Fraccaro: 100%. I'll just pick up a couple of things. One would be, from a closing remarks, I think that point at the beginning about how is these AI initiatives, how it's embedded into your business and your people strategy, really think about what is the workforce of the future, and really think about this integrating within that. I think the second one is around the skills, so how we think about what the roadmap is going to be over the next few years to upskill in the critical areas that are important for your business, and I think that point about change management,? What is the plan to overcome a resistance, and how do you build trust in your system as you're going through this change? I think they're probably the key questions that every HR leader should be, or even just any leader should be asking themselves, or their HR team, how are we thinking about this?

And I think with that, it can help you kickstart, if you haven't already, to lean in and to begin to, be part of this transformation that's happening, which is super exciting.

Siobhan Savage: It is, it is, and as I said at the start of this conversation, we are living in a once-in-a-generation change to work. Our careers will never experience anything this again. And,, to JoAnn and to Michael's points,,, lean in. After this, what we'll do is we'll share the recording with folks, we'll share lots of nuggets of,, insight and expertise from Michael and JoAnn as well, just to really help you kickstart you on that journey as well. JoAnn, thank you so much for being with us, for sharing your knowledge, for your expertise. It's been incredible. Thank you so much. We appreciate you. Michael, thank you so much for, again, giving your incredible insights to all of us, and essentially our role here to play on the Reejig side is to really help the community rise., how can we make sure that we're enabled for this new world of work?

We're very excited about,, building these AI-powered workforces, but we want to make sure that we're doing it in a really bold way. but also in a responsible way, so we believe that this is the dream team of the future. Well, it's actually not even the future, right? It's the… it's the dream team of now,, we gotta get this team in place. Thank you to everyone who's dialed in. We will share any of the insights and recordings and questions directly to you as well, if we don't get you. Have a great day, folks. Thank you!

Michael Fraccaro: Thank you.