Unlike some executives, Christina Schelling, chief talent and diversity officer at Verizon, appears comfortable when making predictions about the future.
Perhaps the most pressing unanswered question about the future of work is how leaders like Schelling will embrace AI—and whether the technology will merely take over certain less desirable tasks or replace workers entirely. Schelling is quick to offer confident remarks that AI will not replace human workers, but will rather enable humans to work more efficiently.
Today, Schelling oversees the 110,000-person company’s talent, succession, and workforce-planning efforts. Previously she led HR teams at Estée Lauder, Prudential Financial, and American Express.
But Schelling started her career at the Central Intelligence Agency (CIA) where she says she first learned how to make predictions about the actions of individuals.
Fast Company spoke with Schelling about her experience at the CIA and about the future of work, AI, and DEI. (This interview has been edited for length and clarity.)
Tell me about your career before Verizon.
I never thought I’d be in the corporate space. It’s kind of an interesting road-less-traveled story.
My training and education is all in psychology and behavioral science. And when I was in graduate school, I actually ended up leaving early before completing [it] to go to the Central Intelligence Agency to work as a leadership analyst, which is kind of like a profiler of leaders. So I really started my career working in intelligence and defense, but assessing people and personalities and leadership.
After doing that for a little bit, I bridged to the corporate space by working in management consulting for IBM, but it was for intelligence and defense. So I still really didn’t get a sense of the corporate space because my clients were all in the intelligence industry, which I kind of already knew about. But I did learn a bit about organizational effectiveness and leadership and training and change management—a lot of the stuff that I still use today.
What did you learn from working at the CIA?
There are so many transferable things I [learned], whether it be what I do today, as far as helping to build up leaders and create capability and coaching for executives, or whether it be to understand the organizational dynamics of all the things that impact people and to embrace system-wide system thinking.
The other thing that’s really fascinating is that at the CIA—I was in my mid-twenties, so this was a couple of decades ago—we were tasked with predicting future instances or behaviors by looking at the data we had. And this is completely counterintuitive to what you learn in your formal education from birth. We’re taught to compare and contrast. Only give the facts. They were like “No, if I can Google this, I don’t need you.” So instead, they [would say], “You have a set of data. You’ve got access to this data. I want you to be predictive, not just reporting on what I could see if I had the time to look into it.”
At the time, it felt super intimidating and scary to be like, Oh my gosh, I’m going to make a call on some of these things. But now, fast-forward a couple of decades and that’s exactly what we do—especially when it comes to AI. You have to really think about the interesting data points that you have, how you can make them work together to be predictive and to help with anticipation of outcomes—or really anticipation of the best solutions. And I learned that very early on at the agency.
What were the workplace dynamics like?
I was very lucky. There were a lot of mentors that have been retired who come back to kind of coach the newbies there.
Being a woman, being Hispanic, being younger, smaller, you name it, I did definitely try to blend in and fit in for my first however many months. And I had a woman pull me aside as a mentor, who I am so grateful for to this day. She said, “You’re amazing at what you do. You’re smart enough, you’re strong enough, you’re capable enough—just like everybody else—but you’re not being you. And that’s something you have that they don’t. And so tomorrow, I want you to come back as you.” That was really important to me, too, because I was not showing up as myself because I was intimidated.
I’d like to say that I’ve been flawless at that ever since. I haven’t. But I’ve done my best and it’s still a learning process. But that was also something I learned at the agency which I’ve carried with me.
What does leadership analysis for the CIA involve? Is it about assessing potential assets who could work for the agency?
Actually no, I didn’t work in HR until years later. I was assessing world leaders. That could have been terrorist leaders, military leaders, professional leaders. And so my job was to be an expert on leaders and create written and verbal bodies of analysis to help make sure that we had a good standing on who we needed to know, from a country perspective.
As it relates to human instinct and AI, someone could make the case that AI can look at the data but can’t fully intuit. Do you think that’s fair?
I think that’s absolutely fair. I think that that’s true today, too. Data can be very black and white, even with the best inferences. And humans—especially the ones that are really good at these jobs like data scientists, but really any users or consumers of data—can see the gray and the nuances. That’s where the real magic happens, I think.
The other thing I would add, too, is you get better at, and build more muscle around, knowing what data points equals the best recipes. You have to figure out what the ingredients are, and then leave it to AI or machine learning to do the “mixing” for you.
But I do think that the bigger and bolder thinking starts with how you even approach the data points that you have, and the enablement of AI to help mix those together. I think it’s pretty awesome for the outputs and can make you a better executive, professional, you name it.
What are some of the ways that Verizon is already using AI?
We’re a network technology company. We’ve been using AI for a really long time to help us understand how to better serve customers. But when it comes to employees, we very much believe that the same bar we hold ourselves to for quality of care and service for customers, we should do the same for employees. And oftentimes, companies lag a little bit in that area because you invest in your P&L, and HR isn’t a P&L. But Verizon has a huge investment in the employee experience, and has for decades.
When I think about ways that we’ve been leveraging AI for many years, it’s really around simple things like helping answer questions that you don’t need a human for. You can get the best answer based on previous questions for basic needs. In hiring, we are leveraging AI to cast a broad net into the external labor market. We are super thoughtful and in the way that we have a diverse pool of candidates . . . And from a training perspective, [we use AI] to make sure that we’ve got smart training that is individualized, and situational, and interacts with the [learner].
What are some of the ways you plan to use AI in the future?
We’ve launched a pilot around accelerating career profiles. We have a huge ERP system and we’re a Workday customer. When you get Workday, it works brilliantly. And it works even more brilliantly if you’ve got a lot of data in it. If there’s no data in it, it’s just kind of a cold shell. We have over 100,000 employees [and] one of the things that we’re asking our employees to do is update their career profiles, which is kind of like an internal résumé.
Now I know, every company does this. At best, maybe you get what 20% or 30% of people that do it year one, right? But the more people that update their career profiles, the more matches will be served to them as far as what’s next in their career; and the more training that will be pushed to them based on the aspirations that they put in their profile. My recruiters can now look at my internal existing employee base, and search for skills and experiences and aspirations as opposed to just a job title.
Job titles can be a little bit all over the place. So now if I’m an employee who asks the question, “I want to be in X role in 10 years, how do I get there?” We will be able to lay out what that career path would look like, what jobs you should take to get there, what training you need to take to get there. And the more data you put in on yourself and the more data people start to add, the more learning we have that we can, through AI, nudge and help empower people to guide their own development in their careers.
Then, as an HR person in charge of the broader talent landscape, I can see where we’ve got real strengths, or gaps, from a strategic workforce planning perspective. I can help facilitate internal mobility and navigate people more horizontally across the company, before they get too senior in one silo and then are stuck.
When I talk to executives about the benefits of AI, they usually either talk about cost savings or productivity increases. This sounds like a cost saving perspective by using AI to improve retention. Is that the case?
Yes, but I think it’s also more about experience overall. One of the biggest benefits of a company like Verizon is you can reinvent yourself and your career multiple times over. But without progressive tools, like the one I just described, it’s tough to figure out how to navigate. [AI] can help you navigate. So it’s really about investing in our people to retain them for sure, but also help them build toward their biggest potential.
And then from a strategic workforce planning perspective, we know what our business strategy is. We know what capabilities we need to be better than the competition. And that all breaks down into roles and talent. So if I can see where I’ve got strength and gaps, I can really help drive the business toward the differentiated outcomes that I know we need based on skills, roles, and people. I think that that’s really huge.
We shouldn’t overlook the efficiencies. We shouldn’t overlook the cost savings. But the driver for us is really about the employee experience and the business potential here. I think that the cost savings and the efficiencies is kind of assumed. You have to have some of those things. But the real magic is when you get beyond that.
We aren’t looking at AI in HR as a downsizing opportunity. It’s more of an additive to help HR practitioners be even better and be able to focus on the role that they play, and can steer toward the more strategic bigger picture-type work—as opposed to just kind of the manual, tactical administrative stuff.
Many people have fears about downsizing when it comes to AI. I understand Verizon has had some layoffs since you have been at the company. Can you speak about that?
For most companies in the Fortune 100, there’s an evolution that comes with building up in certain areas that they think are the levers for performance, and then pulling back in certain areas when there’s cost measures. There’s kind of a natural swing that happens in the business world anyway. We haven’t had a drastic, like, “Oh gosh, the sky is falling,” laying off tens of thousands of people moment. But it’s just part of the natural business cycle, frankly, as you look at what you need to invest in, and where you need to save.
Verizon is culturally such an empathetic, caring organization. Even when there are reductions or changes in the business model and that impacts people, there’s a care here that is just assumed and high touch, which I think is really differentiated for Verizon. . . .
Some people worry that AI will totally eliminate the need for workers, and optimists say, Jobs may change, but they won’t disappear. What are your thoughts when it comes to HR jobs?
So I actually think [AI] is an enabler for almost anybody. The same way some people reacted when email was invented, and were like, Oh, gosh, what are you gonna do? You’re never gonna need anybody to type stuff anymore. And now it’s like, Oh, my gosh, this just makes life so much easier. . . . So I think [AI] is going to continue to accelerate the impact that HR practitioners can have.
I do think, though, that the profile of a successful HR person will evolve a little bit, too. Over the past decade, maybe even more, we’ve said that you’ve got to have data acumen. You’ve got to be comfortable with data and the interpretation and application of data into the work that you do. There’s an art to human resources, but the balancing of the art and science has been something that we’ve been infusing for a really long time. I think that you have to have that capability now, regardless of your job. . . .
You’ve got to be comfortable and almost native with with the use of data, the interpretation and the application of data, and the ability to influence and consult with that data with all that you do. And so I think there’s an upskilling opportunity.
I’ve heard some leaders say that AI will make C-level work superfluous and force workers to turn B-level work into A-level work. What does A-level work look like in HR?
If you think about which people carry a [business’s] capability, what the in-demand jobs are, and how do we get the best people in them, we can’t do that without AI.
Of course, we look at our data inside and our people inside. But I also look externally. I ask, What does our competition look like? What does the market look like? How do I build us up to be better and to ultimately win and be the most competitive we can be?
We also did a poach-ability analysis, where we looked at not just who would be the most attractive, but who would be the most likely to take another offer and leave? And AI helps us do this. So we look at things like, have they been a high performer? Have they been high potential? What does their compensation look like? Have they been in the same job for a really long time? Do they represent a job or a capability that’s in high demand? Do they reflect diversity that’s absent in other places that would make them super attractive? Did their boss just get the big job over them, which might make them more interested in looking somewhere else? And so we came up with this cool algorithm and AI helped us understand where we really have to focus our retention and engagement efforts.
In terms of diversity, after the fall of affirmative action, what is Verizon’s approach?
Diversity was not something new or just trendy for us. Inclusion, diversity, belonging, equity, and all of those things are hugely important and have been baked into who we are for decades now—in our credo, in our business strategy, in how we go to market, you name it.
I think a couple of things have happened since the ruling on affirmative action, and honestly since past five years. We have been unwavering in our path, that has always been who we are. We have stayed steadfast in our commitment to diversity and the importance of diversity and inclusion in not just how we care for our employees, how we provide that equity for our customers, but also our contributions to the broader world, too. And so our work is sort of unchanged, and maybe even accelerated, and in certain ways. We are kind of unapologetic about who we are, and who we have always been. We know that this matters for us, for our own people, and our customers that we serve.
It would be untrue for us to say that we didn’t pay attention because we obviously will abide by policy. We obviously will follow the rules that govern the way that we do business. But it’s also been really great for us to step back and say, “Here’s our goals, here’s our objectives, here’s what’s different, and here’s what’s new. How do we achieve our goals and objectives in maybe even a more meaningful way than we would have if we didn’t have to think about it?”
I can honestly say we have not changed our direction. We haven’t stopped anything. And in fact, it’s created a real opportunity to even be better and more inclusive in the way that we do our diversity work.
Earlier, you mentioned using a chatbot and using Workday’s AI tools for hiring and training. Which other AI tools are you using and are you building any in-house?
Workday has a bunch of solutions within their platform that helps us manage our talent marketplace and push for internal mobility. But we also are testing Gemini for Google Workspace, where employees are able to generate text and graphics to get started for decks and automate emails. We’re practicing and learning with that. Then we also have a more home-grown digital assistant that helps with some of the queries that HR gets.
We’ve tested out and partnered with others too like Eightfold and Sensia and Degreed. Everybody is on this AI journey to make their products and offerings modern, and progressive, and better than their competition. And we’re up for it. So we’re really excited to test and try [AI tools] in a responsible way.
We, like other companies, have an AI leadership council setup to make sure that we’re consistent in the way that we introduce applications, we’re testing and learning, and we’re responsible with AI. . . .
I don’t think there’s any end-to-end process where AI is included, that doesn’t also have a human as one step in that process, because we know that we need the combination [of humans and AI.] People aren’t replaceable. And we think it’s only additive to the outputs when we’ve got a good combination of the two.
You say people aren’t replaceable. What would you say to someone who is worried that their job may be at risk because of advancements in AI?
I would say it’s probably less about AI and more about the fact that the world changes, businesses change, and the expectations of customers and employees change. And if you don’t stay current in your craft, or evolve your skill set, then regardless of AI, the same jobs that existed 30 years ago, are not the same jobs today. The same jobs that existed 10 years ago are not the same jobs that exist today.
It’s your responsibility to keep moving with the times. It’s not AI that’s going to replace you, it’s complacency that doesn’t keep you modern and competitively positioned in the workplace. And so, your point about the replacement of people, I just think that we need a blend of art and science. And the empathy, the understanding, the gray interpretation, the application to influence and consult, we still need people for that.
