Before he became New York Life’s chief data and analytics officer last year, Don Vu spent decades working for a variety of companies in the tech space, including building streaming platform BAMTech through the digital arm of Major League Baseball and as VP for data and analytics at WeWork. Even though he’s at a more traditional company now, Vu is still bullish on the huge opportunities for using AI and building technology to impact the future.

I talked to him about how he shares that value proposition with potential hires, and how companies that people may not associate with tech can attract some of the best talent. This conversation has been edited for length, clarity and continuity. It was excerpted in the Forbes CIO newsletter.

Tell me about your background and how you ended up at New York Life.

Vu: I’ve been in the New York City tech scene since ‘99, when the first internet startup boom began, and so I’ve been steeped in a digitally native sort of ecosystem. I worked at a startup that built startups back in ‘99. I worked at MLB Advanced Media, the digital arm of the league for 13 years. While at that company, we built a video streaming platform that was sold to Disney for $3.5 billion. Then I worked at WeWork—so these digitally native startups.

Then I went to Northwestern Mutual, which is a mutual life insurance company based in Milwaukee. That’s when I really started to understand some of the challenges of being in the insurance space, and recruiting talent.

When people think of a company for tech talent, they probably don’t think of a company like New York Life. Why should they think of a legacy insurance company as a good place to hone their tech skills?

[I’ve been] trying to take everything I’ve learned over that time, recruiting for data and AI talent specifically in New York for about 25 years, and now I feel like I have a pretty refined perspective on it. When I have conversations with folks about opportunities at our company, I focus on a few different things. There’s basically four main pillars.

The first is around impact. One of the things that’s really remarkable about New York Life is we are a mission-based company. Ultimately, what we’re trying to do is secure the financial future for families. We want to be a leader in providing holistic advice and guidance for folks. Oftentimes at other organizations, you might be getting someone to try to stare at their phone more, or click on more ads. No shade meant to be thrown to those activities, but it is a different type of organization that we have. Similarly, there’s an opportunity to lead a transformation and truly leave things better than you found them at a company that has incredible heritage. We’re 179 years old, so this notion of impact is a really big one.

The second thing is most tech folks that are trying to implement AI solutions really want to have business impact, and they want synergy with the business strategy. One of the things that’s really compelling is that our organization’s business strategy and our AI and data strategy are incredibly in sync. Craig DeSanto became the CEO of the organization two years ago. He set our company on a course to really focus on the client and agent experience, as well as operational efficiency, and that’s really meant to be driven by tech, data and AI. Because of that tight synergy with the business strategy, the partnerships we need in order for our work to be successful, to see the light of their day, [are] already there. It’s baked in. There’s already inherent belief and understanding in the work that we do and its importance for our overarching business success.

The third thing is we have long-term time horizons. Oftentimes if you work for a tech company, it could have a little bit of whiplash and skate to the shiny new thing, or be beholden to quarterly earnings and what shareholders are beating the drum on. We’re very focused on the long term. We’re privately held, owned by our policy holders as a mutual insurance company. And ultimately our interest and our goals are in the long-term commitments that we have to our policy holders. We can have the patience that’s often required for these strategic capabilities to develop, take root and have an effect. For folks that have been in the space for some time, they really understand that these things don’t happen overnight. You really need to keep banging on the rock before you finally break through.

The [fourth] thing is there’s quite a bit of talent and technology partnerships that we are able to leverage. We work with leading technology providers. [We have a] very deep relationship with AWS. We have relationships with OpenAI, Microsoft, Anthropic. We are very intentional about making sure that we are partnering with the people that are setting the front edge of innovation, such that we too can be pioneers in that space for our industry. I think folks would be very surprised.

I’ve had people say that, ‘I could work at Google and be one cog in a multi hundred thousand person machine and one of hundreds of thousands of developers.’ Or you can have an inordinate impact within a smaller team and with a company that’s at a different stage of their maturity curve.

What are things that you get from working at a place like New York Life that is not a tech company that you wouldn’t get if you worked at Big Tech?

Google probably has us up on their cafeterias and their food. I’ve had some nice meals there.

But putting that aside, I think the synergy with our business partners is one of the things that’s so compelling to me. We really are in lockstep and in such tight partnership with all the folks that are really operationalizing and bringing these AI solutions to life. I found that to be one of the most appealing things about working here. Candidly, [as] part of our overarching generative AI transformation, we’ve reevaluated and rebooted the way that we work together with our business technology partners. I don’t know if that’s always the case in some of these other companies. Because they’re so big, there’s more separation.

In many ways. I feel like it’s the best of both worlds. There’s the blend of being able to use leading edge technologies and then also having close business partnership and tangible and visual evidence of when these things get deployed.

Nowadays, every company is looking for AI talent. What is the market like for you?

We find it to be challenging, for sure, and certainly the value proposition needs to be laid out. What I oftentimes look for is the profile of an individual that will be a good fit and successful, not just for the short term—to land the individual as a hire—but to be successful in the long term. I look for an individual that has experience across both digital native organizations, as well as maybe a traditional enterprise.

This is just based on my own personal experience. Major League Baseball Advanced Media was a digital spinoff of the league. It was a true startup, but it was owned by a company that was 125 years old: Major League Baseball. After Commissioner [Rob] Manfred took over, he consolidated MLB Advanced Media with the league office. The league office had more of a law firm’s DNA, and it was a bit of a culture shock. The reason I bring that example up is if you were to take a purely digitally native startup [candidate], that’s all they know. Bring them into a more traditional enterprise, there is going to be an adjustment period.

I tend to look for, particularly in leadership positions, someone who’s had experience in both dimensions. Leaders with that sort of profile, that have straddled both worlds, tend to have more success, traction, [and] a lot of the horizontal collaboration with business partners that’s required to be successful.

Are these people applying to work at New York Life, or are you trying to find them?

It’s a balance of both. Certainly the New York Life brand is strong as a whole in the space of data, technology and AI. I would say that we’re not at a place yet where we’re top of mind, so we do have to be intentional about reach out. Things like LinkedIn, as a venue within which we communicate all the traction and success that we’ve had thus far. [We’re] using LinkedIn to amplify the openings and opportunities of growth that we have. Really conveying that even in times where some of the big tech firms were laying off double-digit percentages of their workforce, we were hiring.

We 100% have to put effort into it. This isn’t a situation where folks are just flocking to us uncontrollably.

What is New York Life doing with AI, and what kind of talent do you need to make that happen?

We have strong belief from our CEO, and then all the way through the deepest parts of our organization, that generative AI is an incredible force that is going to change the way that we do work, and change the way that client and agent experience manifests in the years to come. There are a whole variety of areas in which we are investing in generative AI.

One way to describe it is to think about the way that we’re measuring our success. One of the things that we’re really focused on is having an AI-empowered workforce. How do we build the workforce of the future that’s powered by AI? One of the ways we measure our success with that is the reach of AI solutions that people are using on a weekly, monthly basis. Things like OpenAI and ChatGPT Enterprise, things like Microsoft 365, these enterprise software tools that have generative AI embedded in them, we try our best to distribute as widely as possible to the people that are closest to the business problem so they can try to solve problems themselves. That’s one category that we’re focused on: Democratizing those capabilities.

The second thing we think about is impact. How can we have significant business impact? Oftentimes, there’s a very specific business use case that we’re most focused on. We’ve built custom generative AI solutions for a few different domains. One was related to the claims area. We had another one related to marketing. A third is related to the service area. The really appealing thing is because it’s very use case specific, we can measure the incremental impact of adding this capability into an existing workflow with a relatively high precision. You can almost have an A/B test.

Then we have a whole variety of moonshots: systems-level disruption, frontier business disruptive ideas that are in the pipeline. Some of them we can’t talk about because we’d rather keep them close to the vest. One of the big areas that many are optimistic about is this notion of AI agents: Essentially the capability for generative AI to not just answer a question like you see with a chatbot, but also take a subsequent action. In a customer service context, you might ask a chatbot how you can get a refund. With an agent, then that inquiry might actually lead to the refund being issued inside that customer experience. The general notion of AI agents is something that we’re super interested in, both because we think it’s going to greatly facilitate the way our employees operate, how we’re able to generate software and code and build the digital products that fuel our client and agent experience, and how we do business. It sounds like sci-fi, but it really is pretty much here and now, and even greater capabilities are around the corner.

Looking at your own career, you went from digital startups to working for the digital arms of very traditional companies. Why did you make that pivot, and what would you tell someone who may be considering it?

The way I’ve always been wired is [looking at] how might I have the maximum amount of growth and impact in my career journey. For me, I am so grateful for every one of my steps. Being at Major League Baseball, the nation’s pastime, for 13 years was an incredible experience, especially with the unique part of that journey that included BAMTech. That being said, after being in an organization for 13 years, for me as a technologist, it felt like I would grow even more working in another business context and another organization where I could use different muscles. I ended up going to real estate and WeWork, which was its own adventure. I certainly learned a ton from that. Success, and maybe not as much success, in both dimensions, you learned quite a bit.

Ultimately, after having what I would call quite a bit of instability in that part of my journey, I looked for something more stable. I have two kids, they’re now 12 and 10. At the end of my WeWork journey, I wanted a bit more stability. I wanted to make sure I could provide for them. In more than one way, going to the life insurance industry seemed very appealing to me based on the stability of it, the focus on securing the future for families. I found that to be very appealing, especially understanding just how much time it takes for these things to take root.

One of the things that is often talked about is the chief data analytics officer role has an average tenure of 18 months. I think one of the reasons why that stat is so prevalent is because the nature of the role is very different at each firm based on what’s needed at that moment in time. Two, value is hard to measure of the changes that a leader in a role such as mine is bringing about. Then three, it just takes a long time. It’s not easy to lift yourself out of tech debt. It’s not easy to get an organization aligned from a process perspective on the appropriate way to move forward and leverage data and insights for an organization. It takes a lot of time to build AI solutions and operationalize them and have to have a material impact.

For all of those reasons, coming to an organization like New York Life: 179 years old, incredible success, $52 billion a year in revenue, incredible stability, and not beholden to the whiplash of quarterly earnings and shareholders was just very appealing to me. I care so much about having lasting impact, and having a place with the stability for that to take root and ultimately blossom has been what drew me here.

What advice would you give to CIOs in situations like yours: At companies that aren’t necessarily associated with exciting tech careers, but needing to attract top tech talent?

At the end of the day, top talent really can sniff out what’s real and what’s not. I think there’s so many things that are appealing about working in a traditional enterprise. For any leader that wants to make their value proposition resonate with folks that are out looking for jobs and are top talent, you need to think about people, process, and tech.

I think that top talent wants to be around top talent. I think strong engineers want to be around strong engineers. I think good data scientists want to be around other good data scientists. Continue to raise the floor of your talent. Think about anchor hires that then are catalysts for cascading and broader teams that are of high quality and increase your talent density. That’s something that’s real. I’ve seen firsthand the effect that has, almost like an attraction mechanism when you have strong leaders in an industry.

As long as any company remains anchored to old technology, it can be a headwind not just for business agility, which is something that we’re all mindful of, but also for bringing talent on board. There’s so many things that explicitly implicitly are communicated to a candidate when you talk about your tech stack, your architecture. Are you working in the cloud? Are you working with leading vendors in the space in AI and data? Those things convey and make very clear and tangible to top talent what the opportunity is, and what DNA the organization has with respect to technology as a whole.

And then process. Are people working in Agile methodologies? Are people working in more antiquated ones? Is there close synergy with business partners? Are folks iterating and shipping and then testing? I think those sorts of dimensions are also really important. If folks hear about multi-year plans, multi-year projects and long cycles by which software and solutions are being shipped, I think that can be a bit of a flag for folks as well.