In this next episode of The Heidrick & Struggles Leadership Podcast, Heidrick & Struggles’ Adam Howe speaks to Sophia Velastegui, chief product officer at Aptiv and member of the AI Advisory Committee for National Science Foundation NSF. Velastegui discusses the leadership capabilities most important to her success and the challenges of digital transformations, sharing what she has seen some of the world’s most acclaimed technology organizations get right from organization, culture, talent, and leadership perspectives. She also offers her advice to executives looking to create a culture where people can lean in, regardless of their experience or level in the organization; how to start building new technologies into both current operations and new business models and propositions and how to accelerate the organizational leadership’s role in understanding and cultivating curiosity about emerging technologies.

Below is a full transcript of the episode, which has been edited for clarity.

Welcome to The Heidrick & Struggles Leadership Podcast. Heidrick is the premier global provider of senior-level executive search and leadership consulting services. Diversity and inclusion, leading through tumultuous times, and building thriving teams and organizations are among the core issues we talk with leaders about every day, including in our podcasts. Thank you for joining the conversation. 

Adam Howe: Hi, I’m Adam Howe, a partner in Heidrick & Struggles’ New York office. I lead our digital transformation service offering, and I’m a member of Heidrick Consulting and its Culture Shaping Center of Excellence. I spend my life advising clients on how to best align their talent, culture, and organizational design to deliver on their purpose and strategy.

Today I’m excited to be joined by Sophia Velastegui, chief product officer of Aptiv, based in Boston. Aptiv is a worldwide technology company with a mission to be green, safe, and connected and to drive the future of mobility. Sophia has streamlined Aptiv’s product platform and portfolio, especially around AI, software, and cloud.

Sophia also serves as a board director and an audit committee member for BlackLine, a financial accounting software services company based out of California. Before Aptiv, Sophia spent five years at Microsoft as the chief technology officer of AI for business applications and was the general manager of AI products and services, including search. During her time at Microsoft, Sophia’s team was responsible for investigating OpenAI and ChatGPT applied across Microsoft assets such as Microsoft Dynamics, Bing search, and the power platform. Sophia also worked three years at Google Alphabet as the global head of silicon and architecture, and at Apple, where she was the platform architecture think-tank manager as well as manager of special projects.

Sophia has been recognized multiple times at Business Insider as the world’s most powerful female engineer, and she also works with the World Economic Forum. Sophia, thank you for joining us today. 

Sophia Velastegui: It’s a pleasure to be here to have this conversation.

Adam Howe: Sophia, in your career, what would you say are the leadership capabilities most important to your success and why? 

Sophia Velastegui: Whether in leadership or technology, a growth mindset is key. This framework encourages curiosity and experimentation, which is important, as the world is changing faster than ever before. Curiosity fuels continuous learning and problem solving to help me look around the corner, and experimentation helps me to constantly look for improvements and new ways of solving problems.

For every A/B testing, one will fail, and that’s OK because you’ll be learning throughout the journey. This growth mindset was key for me to go from mechanical engineering and semiconductors for applied materials, to CTO of AI at Microsoft investigating AI and ChatGPT, and now chief product officer at Aptiv in automotive and autonomous driving.

Adam Howe: You’ve worked for some of the world’s most acclaimed technology organizations, and in the spirit of curiosity, I’m curious as to what you’ve seen them get right from an organization, culture, talent, and leadership perspective. 

Sophia Velastegui: I’ve been very fortunate to work at some big tech companies, but before they became big. As an example, I was at Apple in 2009 when the iPhone was new and it was only 34,000 employees—it’s now180,000 people. Nest was a start-up that got purchased by Google, going from 250 people to over 100,000 with Google as a whole. When I joined Microsoft in 2017, it was literally considered a dinosaur in Silicon Valley, and Windows was a separate business unit. After I joined, AI really exploded, and OpenAI and the infusion of AI across all business units became the top priority, and that increased Microsoft’s market cap from $670 billion to $2.6 trillion.

One of the things I’ve noticed in my journey is that there’s a real focus on people and the organization that’s set up for experimentation and agility. The companies I’ve worked for achieve this on numerous fronts. A McKinsey report states that a high-performance software engineer outperforms an average engineer by eight times. So how can you pan this out, not just in software engineering but all for engineers to see this improvement? How does your culture amplify an environment that really infuses and fosters that culture of high performers? One of the things we did was review who was leaving the company and where they went, and who was joining the company and where they came from. Is this the right blend of infusion of talent and mindset to make our culture that much better?

Adam Howe: I love that analysis of who’s leaving and who’s joining, and what that tells you about the organization. I’d like to get your view on the claim that most digital transformations fail to meet their stated objectives. Thinking about the reasons for failure, what are your thoughts on what those reasons might be from a people, culture, and leadership perspective?

Sophia Velastegui: One of the things I saw in common across organizations, and when I was a CTO of AI I actually worked with a lot of non-digital-native companies across the world, is that when a digital-native company thinks about digital transformation, it is not a one-time event. This continuous learning and enhancement of the environment is across all aspects of the company. It is not just about infusing technology for IT or infrastructure. It’s not just infusing technology or AI in the product or engineering. It’s how we do work, it’s how we operate end to end, whether it’s with HR or finance or how we recruit. It’s how we use that data and that knowledge in order to enhance everything we do. 

Adam Howe: I love that. And going a bit deeper, if we think about the traditional or non-digital-native organizations, if they’re to be more successful with their digital transformation efforts, how can they, for example, organize for digital? How do you blend specialist expertise and a center of excellence with building digital in the business? What are the two or three mindsets you think are required in the culture? And, perhaps interesting for many listeners of this podcast, how can senior leaders build their digital savviness?

Sophia Velastegui: One of the things is that the digital transformation has to be tied to a business outcome and a business benefit, so that there is not a conflict of interest. This is a way to infuse and enhance, maybe even accelerate, the digital transformation.

Another is learning from digital natives. What I mean by that is having that culture and mindset of infusing digital across the organization and being very comfortable with leveraging digital assets. You need about 10–15% of the population to cross that chasm and increase the adoption rate because that’s enough of the workforce to advocate and evangelize it across the company. The area I focus on is first-line managers. How do you get 10–15% of them to be more digital native? And you need about 10–15% of the executive level, the sponsors and across sponsors, to be bought in as well.

Acting like a digital native means you assume that technology will change and that people and the company will change with it. You’re constantly changing with the technology. There are new apps, new capabilities. You’re always looking forward. These are the people who are the early adopters of cell phones or leveraging AI into the work environment.

But one thing that’s really important when you do digital transformation is making sure that you measure and monitor it to determine the effectiveness. And knowing what your baseline is beforehand is really important.

Acting like a digital native is in some ways like an overall purpose, almost like a religion, in how you think about digital in everything you do. If you can use technology to improve HR, even if you have nothing to do with HR, that’s great. 

And these are reinforcing practices. Since it’s a practice in behavior, that’s why having 10–15% of the population on board is very important, because a practice in behavior is the basis of a culture, and you need to have a community that’s strong enough to go reinforce that practice. 

Another thing that I saw across all of the organizations is how they got the message out. They really leaned on storytelling. How do you leverage storytelling to demonstrate why people need to change their mindsets to become more digital native, and in a way that is tied into, and benefits, the business and the market as a whole? Storytelling is what makes it memorable. 

I have an example of an intern at Apple. She had a problem with the iMac. This was one of the first iMacs, where the display and the tower were integrated with each other. Apple always wanted to make its computers thinner and thinner, but most of these desktop iMacs were rectangular in space. So the intern determined the optimal curvature to give the optical illusion of thinness: at the edge, it’s very thin, but at the middle, which is farther away, you don’t see that it is much thicker. She was just an intern but was asked to head the product design. This is where practical innovation, that delight, is rewarded. And it’s not about your time or your role in the company. It’s the fact that the innovation fundamentally changed the perspective of the product.

Adam Howe: I love that story. What is your advice to organizations that could look at that example of really empowering an intern to bring his or her best views and ideas into a use case like that? That’s easy to say, harder to do. What’s your advice for executives to be able to create that culture where people can lean in regardless of their experience, regardless of their level in the organization?

Sophia Velastegui: One of the things that I find key to the culture that really amplifies this digital-native environment of curiosity and experimentation is determining the culture that you need in your environment to encourage rapid experimentation—that is, A/B testing. And as I said earlier, one of them will fail, and that is a good thing. You will learn from that and quickly determine that insight so you can incorporate that into the next experimentation, which will be more refined.

There’s a saying I had at Microsoft: “Celebrate the red,” which means I would rather find out what the issues are in my development environment before it gets deployed to a billion users. That’s when you get real problems.

Another thing is that you need to “dogfood” [try out] your own work. I give the example of when we were making our first thermostat at Nest and optimizing the algorithm. I was living with my grandmother at the time, and I said, “Grandmother, this is the future of the thermostat. It has AI, and it’s going to learn everything about you. It’s so cool.”

And she was like, “That’s so beautiful.” Because it was very beautifully designed, with the glass feature and everything. “I’m so glad you work, that you left Apple to go to Nest.” 

And then three days later, she’s like, “Why does this Nest thermostat want a relationship? I don’t need it nagging me. I have your grandfather for that. Why is it constantly asking me to give it more input or more adjustment of the thermostat? I told it this yesterday.” 

I said, “Grandma, it’s AI. It needs to learn your habit. Your habit is changing throughout the week.”

She’s like, “Sophia, you need to get rid of it. I don’t need this nagging relationship. I can only do one, and it’s your grandfather. I’m sorry.”

And since we were dogfooding it, I could have obviously dismissed her statement and said, “What does she know? She doesn’t know anything about technology. She grew up in the 1920s in South Korea,” versus “The return policy on this device is 7 to 14 days.” My grandmother would definitely have returned this, or she would’ve told me to return it. And so I said, “Grandmother, thank you. Let’s not have this kind of relationship. I’m going to return it.”

But we still had to address the issue. We knew that what you do on weekdays is very different from what you do on the weekend. So how do we preset the information, understanding that learning will be in two phases: the first two days on the weekday and then one day on the weekend? And then the second thing we did because of the feedback was to look at how other people behave on the weekdays or a weekend that’s similar to this household.

Obviously my grandmother took all credit for the success of Nest and that it got purchased by Google. It was not her, but that’s OK. The fact of the matter is that you’re dogfooding and really understanding in real life what is happening. And how do you make that a great thing versus “Hey, you’re in trouble. Your customer wants to go return this product.” It’s not a failure. You’re learning from this, and you’re learning in a way that’s constantly making the product better.

Number two is self-organization. How do you have collaboration that’s fluid across functions and geographies and hierarchy and organizational boundaries to get things done? So really empowering and encouraging that. 

Number three is driving decisions with data. Collecting and using accurate data to make decisions and solve problems is key. It may be that you’re measuring the wrong data, but you will understand that because the data will show improvements but you will see that it’s not the case in real life. But it’s having that understanding to quantify things. It’s that discipline that’s needed. 

And on that note is AI and machine learning (ML). AI and ML are about data. As you get used to leveraging decisions with high-quality data, you can then leverage that same data for machine learning and AI benefits and productivity. 

And last of all is being obsessive over the customer. I’m not saying that you adhere to everything they want. Like my grandmother said, “Just take the product out,” I’m not going to listen to that customer and just get rid of the product and that’s it. It’s about understanding that what she says has validity. How can we improve the product so it’s not a point of frustration? Our job is to go delight them and really understand the customer. With Apple and with Nest and Google, it was ages 7 to 70. It’s been a long time since I was 7 years old, and I haven’t been 70 yet. So how can you really obsess about your customer and put yourself in their shoes?

Adam Howe: I love the specificity of some of those insights. We all know that grandmothers are usually right, so that was a good example of dogfooding. As you think about some of the non-digital-native organizations, those that haven’t grown up being a digital organization or that are doing something more traditional or have been around for a long time but that aspire to build some of the things that you’ve talked about here, who are some of the organizations that you would look to as exemplars? 

Sophia Velastegui: One thing I think is important for top leaders in the organization is that mindset of continuous learning and curiosity. Focus on learning things, quantitative and qualitative. What I mean by that is reading books, attending seminars, listening to podcasts, and meeting experts in their field. Most of the experts are passionate about sharing their insights.

There’s a great example of Apple learning from other industries. We found out that most people’s passcode for their iPhone is 0000 or 1234. We’re like, “That’s not going to provide the security they’re expecting.” So we asked them to change their passcode, but what ended up happening is their passcode got changed to 1111 or 2345. Again, not really meeting security objectives. We knew we could do better. We also knew that everyone has the secret wish to be James Bond or, in my case, Jane Bond. And so that’s how the fingerprint volumetric came to be and launch on iPhone 5s in 2013. 

So as a leader, how can you [embrace curiosity and learning? This a critical mindset because things are going to continue to change.] Here’s an example: the CIO role used to be about IT infrastructure and bringing various devices online. It’s now about cybersecurity and AI and business application, leveraging data structure, and anthology. A chief marketing officer used to be about print and then TV and then social and influencer. How can a CMO now leverage search engine optimization and ChatGPT to provide a compelling story? Consider the CFO: years ago it was Excel and then various SAP. How can a CFO now leverage SAP and other ERP systems with other systems of records and automate the flow of information to ensure that forecasting predictive analytics are even better than before and introduce automation? The CHRO went from performance management and people management to looking at people analytics. I gave the example before of a previous company at Microsoft where we looked at the culture and the people that were coming into the company, where they came from, and who they are, and then also looking at the people leaving the company, and how does that impact our culture?

These are just some of examples of how technology is impacting the executive suite. 

Adam Howe: Which traditional or non-digital-native organizations would you look to as an exemplar of some of the things that you’ve talked about in this conversation?

Sophia Velastegui: Some of the success stories you’ve heard are companies in which I have worked: Apple, Microsoft, and Google. Aptiv is incorporating modern software considerations with middleware, DevOps, and the software development tool chain, making our organization exemplary. 

Another example is John Deere. How they are leveraging autonomous driving capabilities in their agricultural use cases to really optimize the pressure, the gathering, and the care of the different agriculture that feeds the world I found to be very innovative. They have a great culture that is very open to learning from other industries. 

That’s one thing I appreciate in a lot of these companies is that they know that maybe it’s never been done in their industry, but they are looking for ways to learn from other associated industries.

AMD is another example, in semiconductors. In the beginning, they were working and competing against Intel, but they decided that instead of being monolithic in their architecture that they would review areas that could be modular in design and focus on nano releases based on how market conditions or advancements happen. And it was long-term view; it took five years or so. And it took a different mindset and capability and conviction from the top down. 

Adam Howe: We’ve seen a lot of buzz around generative AI with the surging popularity in ChatGPT this year, and it seems disruptive technologies will continue to emerge like this. What is your advice to C-suite leaders around things such as how to start building these technologies to improve how your company currently operates and/or creating new business models and propositions?

Sophia Velastegui: One of the things I want to highlight is that what makes generative AI or ChatGPT fundamentally different from these earlier ways of AI is that traditional AI is designed and trained by specialized, highly structured tasks and highly educated data scientists and those who have worked in those environments.

The game changer for generative AI is that now it has these humanlike capabilities in using reason, using language, generating content, and making decisions, and it is accessible for anybody that speaks the language. So you no longer have to have this breadth of technical knowledge before getting the benefits of AI.

One of the things that will happen with generative AI is that because of the accessibility, more and more people will adopt it and feel comfortable with it. There’s a lot of AI behind search, whether it be Bing or Google. The fact that it’s now accessible by many people and how it can be surfaced, whether it’s for business application or personal application, is one of the biggest differences.

And going back to your question of how you start building these technologies into improving your current company operations as well as creating the new business model, the first thing is to really focus on what are the business needs as well as the value creation you’re targeting. It should not be disconnected from that. It’s not a separate technology or project that’s disconnected from the business needs of the company. 

Adam Howe: How soon do you start building these technologies into improving how your company currently operates or to create new business models and propositions?

Sophia Velastegui: AI is not going away, so it’s very important that one becomes comfortable with it. And one of the ways that generative AI is fundamentally different from earlier ways of AI is that traditional AI was really designed and trained for specialized, highly structured tasks by highly technical data scientists and machine learning engineers. What generative AI has shown the world is that it has these humanlike abilities to use language and reason, generate content, and make decisions in a way that’s accessible to everyone.

And so it’s important that you have your framework that allows you to leverage it now because it will not be going away, because of the accessibility. It is something that can be adopted across an organization.

The one thing to note with ChatGPT specifically is that it is an open platform, so any information that’s inputted there will become public knowledge. If there’s any concern of something be shared out to The Wall Street Journal or to your competitor, that’s not something you would use ChatGPT for. 

There are three things to consider when leveraging AI. Number one is having a cross-functional governance group that provides the policy of how AI can be used. Number two is having an understanding about the data that is available in the company. And number three is finding very high-value business needs that can leverage AI. This framework is essential so that you do not waste resources and give yourself a better chance of successful pilots. 

Adam Howe: Building on that point, how do you think about allowing broader access to these technologies? I suppose there’s a balance to get right, between letting individuals experiment organically and building more dedicated teams with more formal training. 

Sophia Velastegui: The formal training and building of a dedicated team was because of the fact that traditional AI was formed in a way that you had to be highly specialized. What is nice about generative AI is that it’s accessible to numerous types of people. When I mentioned having various pilots going across the organization prioritized based on business needs, it’s because it’s important that the experiment happens across multiple different functions and capabilities within the organization. That will help the leaders and the C-suite to understand the benefits as well as the capabilities of AI in their environment. That’s one of the most important things to understand the full value and potential of AI. 

Adam Howe: Whose job do you think it is to spot these emerging trends? AI’s been around and talked about for a while, but ChatGPT over the past 12 months has kind of arrived on the scene. Who do you think holds that responsibility inside organizations? And linked to that is how do you accelerate the C-suite’s understanding and accelerate curiosity around these emerging technologies? 

Sophia Velastegui: I have seen various different models of whose job it is to spot these emerging tech trends. A lot of companies have a chief technology officer, but in a company like Apple, there is no CTO. It should be whomever is responsible for enabling technology in your organization across the company, not just for productivity or for IT reasons, and that may show up in different ways. It could be a chief product officer who has a technical knowledge and curiosity, or it could be the CTO to enable some of the technology infrastructure. I’ve also seen cases of different parts of the CFO organization take responsibility for this, because of the implication of how AI can amplify their business and the gains in productivity and innovation. 

Adam Howe: How do you accelerate the C-suite’s understanding and curiosity in emerging technologies?

Sophia Velastegui: I find it extremely helpful to have monthly brown-bag lunches or fireside chats with experts in the field, whether it’s from a start-up to specialists, it doesn’t necessarily have to be someone in your own industry of how they’re leveraging AI as well as other Emerging Technology. It’s also important to ask these hypothetical questions to those experts. If you were to apply for supply chain, considering your technical background, what are some of the things that come top of mind?

A lot of times people think about Emerging Technology and that it’s limited to technology or it. I’ve seen that in the high tech company. Technology is something that is infused in every single business unit and subject matter area across the whole company. I. How can AI be used as example in human resources?

How can AI be used in finance to give various insight and higher prediction? I see that that’s something that’s been done at scale across Microsoft, under Amy Hood. 

Adam Howe: From a leadership perspective, if you had one piece of advice for a CEO or a senior leader about to embark on the latest iteration of their digital transformation journey, what would be that piece of advice to prepare them for continuous technological evolution? 

Sophia Velastegui: Yeah, stay curious. Have speakers or experts come to their board or to the CEOs to speak about the different technology, and not just the technology itself, but also what are the behaviors you would see if it was implemented?

Well, And the reason I say that there is this constant shadow of the leader, well, that also the shadow of a behavior or culture can be seen in their secondary behavior and church area behavior. So asking those expert, if this is done well, what are the things that’s obvious from the top level, but what are other secondary behaviors I should start seeing?

Because sometimes as executives, information does get filter. This is a great way to really see in a measurable way how things are truly happening in your company. Whether you sit on a board or you’re a C X O. 

Adam Howe: Yeah, I love that. And that kind of what we need to be true is really permanent, so that’s great.

Sophia, well, thank you very much for taking the time to speak with us today. We’ve really enjoyed the conversation. 

Sophia Velastegui: Thank you so much. It’s been a pleasure. Always having a conversation with you.

Thanks for listening to The Heidrick & Struggles Leadership Podcast. To make sure you don’t miss more future-shaping ideas and conversations, please subscribe to our channel on the podcast app. And if you’re listening via LinkedIn, Twitter, or YouTube, why not share this with your connections? Until next time. 

About the interviewer

Adam Howe (ahowe@heidrick.com) is a partner in Heidrick & Struggles’ New York City and London offices. He leads the global Organizational Simplicity and Digital Transformation service offerings and is a member of the Culture Shaping Practice.