Speakers

Alexa Goldberg — Director of Partnerships and Content, Valence. Alexa leads partnerships and content at Valence, an AI coaching platform that enables a new approach to performance and leadership development.

Holly Kortright — Chief Human Resources Officer, Navy Federal Credit Union. Holly leads people strategy at Navy Federal Credit Union, guiding workforce transformation, reskilling, and AI adoption across a large frontline organization.

Andrew (Moderator) — Semafor. Andrew hosted this session at Semafor's World of Work.

Introduction: Why the AI Conversation Is Now About People

[00:00:13.980] Andrew: Well, hello again, everybody. It's been a good day of programming so far. Excited to jump in here today. AI is reshaping the workplace at a truly incredible pace right now, but the conversation's no longer just about the technology itself. It's about people, it's about how leaders build trust and help employees adapt and ensure AI enhances the employee experience. We're going to talk about that today in our session. I'm joined by Alexa Goldberg, Director of Partnerships and Content at Valence, and Holly Kortright, CHRO at Navy Federal Credit Union. Thank you both for being here. Together, you both bring a very deep experience helping organizations navigate workforce transformation and the future of leadership. So thanks again for being here. Let's jump in. Holly, let's start with you here. There's a lot of excitement and anxiety around AI in the workplace. At a high level, though, is AI alienating today's workforce or do you think it's actually bringing people in?

Does AI Alienate or Engage the Workforce?

AI can both engage and alienate the workforce, and which one happens depends on an organization's culture and leadership. Holly Kortright, CHRO at Navy Federal Credit Union, notes that employees carry real concerns about layoffs, their future, and how fast they can learn new skills — so a culture of trust, open communication, and involving people in the change is what turns AI into something employees embrace rather than fear.

[00:01:04.620] Holly: I think it's doing both, depending on the culture of your organization, the leadership. We heard earlier today already, employees and team members have concerns about their job. They have concerns about layoffs. They have concerns about their future. They have concerns about how fast they can learn new skills and move forward with the technology. I think that points to the need for a culture of trust and of communication from leaders and involvement and making all of our team members part of this transformation, not something that's happening to them.

Holly: There is also excitement, though. On the front lines, there are so many tools now that team members can leverage. We have our customer service reps that serve our military members with their financials, and they now have tools they can do simulations on when they join us, and they can have learning and growth opportunities and receive feedback before they ever have to get on the phone. They have tools, when they're on the phone, that give them personalized insights that they can share with members that help them do their jobs even better.

Holly: It's beholden on all of us, from a leadership standpoint, to continuously communicate. We have made a commitment as an organization to help people reskill and upskill so they will have jobs for the future. But there's a lot going on in society that people hear, and they see and hear things in the news. So, how do we help people build the skills they need to take advantage of AI? And how do we support the workforce and continue to hire and develop talent? You heard from our graduate about the challenges there. We can't stop hiring people. We have to leverage it in the right ways and build the trust so that people can embrace it.

The Biggest Mistake Leaders Make When Introducing AI

The biggest mistake leaders make is introducing AI and mandating its use for the sake of using AI, rather than starting from a problem to solve or a capability to build. Alexa Goldberg, Director of Partnerships and Content at Valence, an AI coaching platform, explains that framing AI around a real problem — like helping leaders give critical feedback — lets employees see its value instead of fearing it.

[00:03:02.139] Andrew: Absolutely. That really sets the stage because how employees experience AI often starts with how leaders introduce it. We've heard that theme today as well. Alexa, from your perspective, what's the biggest mistake you see leaders making when they introduce AI into their organizations for the first time?

[00:03:16.639] Alexa: I think the biggest mistake that we see with the work we do at Valence — and for those who don't know, Valence is an AI coaching platform that really enables a new approach to performance — is that organizations are just introducing AI and mandating the use of AI for the sake of using AI rather than approaching it from the perspective of, what is a problem I'm trying to solve? Or like Holly was saying, what is a capability I'm trying to build in my workforce, and how can I use this technology to do that in a way I've never been able to before?

Alexa: As an example, one of the things a lot of our clients come to us with at Valence is, “I have this culture that's too nice.” We talked a lot about culture today. “My leaders don't know how to give critical feedback, or they don't know how to have a difficult conversation.” So when we design Nadia, one of the things we do is we help leaders practice giving that more critical feedback, think a little bit more deeply about what they're saying and how they're delivering it. By doing that, we're really solving a problem that leaders have had for a really long time rather than asking them to learn something net new. I think when you frame rolling out these tools in that way, you're allowing people to see a lot more value out of it rather than maybe be fearful of it or have anxiety about it.

What Separates Organizations Getting AI Right

Organizations that get AI right tie it to their mission, equip frontline leaders to translate strategy into day-to-day change, and redesign jobs together with the employees who do them. Holly Kortright of Navy Federal Credit Union describes a first pilot with documentation specialists — a role AI reshapes rather than eliminates — where employees, as the experts, helped redesign their own work.

[00:04:33.399] Andrew: Absolutely. If those are some of the common missteps, let's talk about what separates organizations that are navigating this successfully and those that aren't. Holly, how can leaders avoid some of these pitfalls, and what separates organizations that are getting this right from those that you've seen that are struggling in it?

[00:04:47.860] Holly: Listen, we are all on a journey with this. I don't think any organization has done this perfectly. There are so many unknowns that we're going to figure out along the journey. What we've tried to do is really tie it into our mission and how it can help serve our membership, and how it can help individuals do work that is most valuable to them. One of our learnings has been, even though we've been communicating a lot, we need our frontline leaders to be able to translate what we're communicating at a higher level into what it means in day-to-day jobs. That's hard to do in a large organization, but we have built some programs and some pilots to work with actual team members on how their jobs are going to change in the future.

Holly: So instead of saying, you have this new job because technology has eliminated tasks, we're actually working with them to redesign their jobs because they are the experts in what they're doing and the technology and the processes change and add value. So, what does that new job look like? We just did this early on, our first pilot with our documentation specialists. Obviously, that job is changing massively as we go forward with AI. But there are ways you need to set up data and documents for AI to make it effective, so they're critical in the future. We're designing it with them and making them a part of it.

Creating Capacity for Employees to Learn and Experiment

To help employees adopt AI, organizations must deliberately create time and bandwidth to learn and experiment — which is difficult for frontline staff like member service reps who are on the phone all day. Navy Federal Credit Union runs an 'AI week' every six months, cancelling as many meetings as possible so people can come into labs, experiment, and share success stories as part of the transformation.

Holly: I also think another key thing is you have to create the time and bandwidth for people to learn and grow and experiment. Sometimes people are scared of experimenting because they might get something wrong. That's a culture dynamic and a trust and a leadership aspect. How do you create that bandwidth, which is hard when you might be a member service rep on the phone all day? You have to make a commitment as an organization to create that bandwidth so they can try out things, they can experiment, they see how it works in their day-to-day, and they have a supportive coaching background that's going to help them continue to learn and grow.

Holly: I think the pitfalls are when it's forced on them. The technology is forced on them, and they're like, “It has nothing to do with my job or helping me,” when it is mandated, and when leaders aren't doing the same learning journey as everyone else. Leaders talk about it, but what are they actually doing with AI as a role model to improve how they're operating? Those are some of the things that we're working on. We also have an AI week every six months where we have a whole week and we try and cancel as many meetings as possible. People get to come into labs and experiment and learn the stories of the successes they're seeing and have an opportunity to really be part of this revolution.

What Success With AI Coaching Looks Like

Success with AI coaching starts with building capacity before capability. Alexa Goldberg of Valence points to Delta Air Lines, where a complex, time-intensive performance process was redesigned with Valence's AI coach, Nadia. Managers saved roughly 25–30 hours per review cycle, and employees reported getting both more feedback and higher-quality feedback — capacity that can then be reinvested in building new capabilities.

[00:07:44.019] Andrew: Amazing. Alexa, to close out today, let's talk a little bit about what success actually looks like. Can you share an example of what happens when a company really gets this right and where you see this heading over the next few years?

[00:07:53.639] Alexa: Yeah, well, I'll pick up on a thread that Holly just mentioned, which is the idea of creating bandwidth. We actually hosted a CHRO round table last week, and one of our partners said something that really resonated with me, which is you have to build capacity before you can build capability. I think that is such a powerful framework for thinking through how to measure success of these technologies.

Alexa: To give you a specific example from one of our clients, we've been working with Delta Airlines for a few years now. The problem they originally came to us with was we have a performance process that's really complex, it's really time intensive, and our managers have these large spans of control such that it's really not efficient for them to get through this process. When we were able to implement Nadia and redesign their process with Nadia, the first thing we saw was that capacity creation. We were able to save these managers about 25 to 30 hours on average per review cycle. What we also saw, which was really exciting, is that the employees were saying, “Not only am I getting more feedback, but I'm also getting higher quality feedback.” So you see that balance between creating capacity to then create capability.

Where AI Coaching Is Heading Next

Alexa: My hope for the future is, as these conversations evolve, I think a lot of organizations are still just thinking about adoption and are thinking about capacity. These tools have the power to do that, but I want the conversation — and hope the conversation will move — to what capabilities can we build, because I think that's where the opportunity really lies.

[00:09:17.779] Andrew: Fantastic. Well, Alexa, Holly, thank you so much for being here with us today for Semafor.

[00:09:21.781] Alexa: Thank you.