Speaker: You’re listening to a new episode of The Brave Technologist. And this one was recorded live at the AI Summit in New York City, where we sat down with Elise Neal, who’s the global Head of Strategy and Strategic Partnerships for Panasonic Go.

In this role, she’s responsible for driving business transformation through AI and expanding AI enabled solutions to 30% of Panasonic sales by 2035.

Elise was previously senior VP of New Business Innovation at Verizon and served as the CEO of MapQuest.

In this episode, we discussed lessons she’s learned from leading innovation with large legacy companies and the cultural challenges she’s come up against in driving transformation,

how organizations should rethink AI governance and talent, and why roles like the CHRO may become central in the AI era.

And now for this week’s episode of the Brave Technologist.

Luke: Elise, welcome to the Brave Technologist. How you doing [00:01:00] today?

Elise: I’m doing great. Thanks so much for having me.

Luke: Yeah, thanks for coming. I know you’re here at the AI Summit. you’re speaking at the conference what’s the core message you’re hoping to spread

Elise: So I think there are two core messages. So the first core message is from a leadership perspective, as we think about these changes that generative AI are making in terms of the way that we need to lead with human hybrid agent teams. It’s really about engaging leaders to not just be consumers of ai, but to be contributors, to learn and to edit, and to interact along with the machines and to be a part of the narrative in the story.

Not to be afraid to just receive the tools, but to actually use it and be a part of the resource. The second piece is to hopefully share some of the things that we’re learning at Panasonic in our transformation journey. About how we’re taking experiments and we’re moving them into execution at scale, the things that we’re learning, the things that we’re breaking, the things that we’re ruining, and kind of working that along the way, hopefully to inspire all of the other companies that we need.

As we kind of think about this culture of building and innovating together.

Luke: That’s awesome. I, I love how engaged that [00:02:00] is. you’ve led innovation kind of inside giants like Verizon and MapQuest, and now Panasonic. When you step into kind of a, a established organization like that what’s the first signal you look for to gauge whether it can truly transform?

Elise: Oh, well, I have this really crazy desire to transform these old legacy brands. I love an underdog story, and so I’m always attracted to those that kind of seem like. Maybe everyone’s doubting them in the market. And so I think the first thing I think about in terms of whether or not I wanna take on a transformation challenge is, is there an imperative in order to really think about that opportunity change is hard and naturally we across the globe resist kind of any kind of change whatsoever.

And something as foundational, as generative AI will disrupt every part of our process, every part of our culture, the way that we get work done. And so if, if there isn’t that imperative, if there isn’t the. Hey, we’re gonna get our stock prices in the pooper and we need to figure out how to improve, or our margins are razor thin and we think that we can [00:03:00] get half a percentage point, you know, by increasing and leveraging generative AI in a new way.

Like that sharpness and desire that kind of goes all the way through the culture of an organization so everybody understands the reality of where they are. To me, that’s what will drive and propel change because there is no other option. Because if there is another option, we as humans will take the easier way out.

Like we don’t wanna lean into the friction.

Luke: Right, right, right. No, it’s a, it’s a heck of a challenge too. ‘cause you’ve got, you know, within the orgs, I would imagine too, What’s the most surprising resistance you’ve encountered when you’re trying to transform somebody like Pan Panasonic?

In the culture that’s been around for that long.

Elise: I really like hard jobs and this one has been really difficult. I think the most surprising piece, I understood that the culture would be very, very different working in an Eastern culture and one that’s very specific. So the Japanese culture is not just a broad Asian culture.

They all have a lot of their idiosyncrasies. And I think one of the most surprising things has been Panasonic has been around for 106 years. They’re a manufacturing master. They understand process and technology, precision [00:04:00] manufacturing, and those processes you would think would really enable them to be systems-based thinkers.

To really think broadly in the Western world. We like to imagine that we can solve any problem and that we’re just, you know one iteration away from greatness. And so as a result, we tend to be and operate in a little bit more of a generalist fashion. We give a lot of autonomy to our staff and to our teams in order to really inspire that creativity in the Japanese culture.

They have achieved kaizen in their manufacturing excellence by having each person understand the depth and clarity of their specific job versus thinking about the whole system of change. And so when you think about implementing a foundational technology like generative ai, one that. It leverages consensus, it leverages collaboration really pushing those challenges to have people think about what happens before and after.

Because effectively we’re redesigning the workflow, and so just taking an individual who works on one specified [00:05:00] task and pulling them out to really be more of a systems thinker. Has been a challenge that I didn’t anticipate and is one that is a really fundamental change in terms of how they operate and frankly, how it’s made them so successful as a culture for so many years.

Luke: It’s wild. It’s wild. It’s a lot to think about too. ‘cause you, you’re having to shift the culture with the people that are building the technology, but also the end user of the technology is gonna be in this kind of more generalist kind of effect. Really, really interesting perspective. For a leader who’s absolutely not technical what, what is the first mindset shift they need to make to step confidently forward in the new ai?

Elise: Oh, well, I am a non-technical leader and I like to gallivant myself and lead, you know, lead technology teams and engineering teams, but I’ve never written a line of code in my life, and so to me, like the most powerful piece is just to kind of step into the curiosity. So we like to think about transformation as having a magnetic pull.

So magnets have an energy, but they also have the ability to pull and to attract or to repel. And so you as a leader or we as leaders have an [00:06:00] opportunity to say, I now have the natural language ability to also step in and to create myself, to move from being a consumer into a contributor.

And so as we think about those opportunities, the fact that I can run side by side, I, I, I’m not ever gonna have a deep coating background and you should not rely on me for your technical architecture diagram. I can read one, but you don’t want me to design it, but. Thinking about that generalist capability, and now that I can create and co-create alongside my team, I can create new tools for myself versus just waiting for another firm to do it for me.

It is invigorating. It’s a little bit terrifying, but it’s quite activating and so it creates this magnetism, which also compounds. So if me as a leader, I’m starting to create new AI agents for myself and for my team, it totally changes the dynamic from a leadership perspective. And it means that now my team isn’t just waiting for me to make decisions, that I’m, we’re all participating kind of collectively as well.

And then that breeds more magnetism on, on and on it goes. So, yeah. Yeah,

Luke: I think that’s [00:07:00] kinda a secret weapon. Like not having, I mean like having worked with a lot of engineers, it’s just, you know, you. You really kind of showing the trust in the team, trust in everybody’s ability to get the job done and, and all of that and, and, and kinda making it work off of that.

You know, for, you said governance in the past is the bottleneck and, and, and the unlock for ROI on ai, I mean what does good governance actually look like in practice and how is the ROI picture too, like, I mean with, with the current state of market fit in the AI space.

Elise: Yeah. What’s really interesting is in our Western culture, we love governance because we love command and control.

And in an eastern culture, they’re much more, consensus building. And so there really isn’t that top down control. So words like governance are like cuss words in Japan. And so so the first answer is we manage governance very delicately. But I think when we think about this opportunity with generative ai, again.

The most powerful technologies are systems that collaborate amongst one another. Like generative AI is by its very [00:08:00] nature collaborative. Like if you think about the technology that’s underpinning it, and so how can we create governance that isn’t a top down, but that we are designing systems. That actually allow us collectively to make better decisions over and over and over again.

And so I think from that perspective, we’re looking at governance kind of in all areas. How do we govern talent? How do we govern our deliverables? How do we govern safety, compliance, regulatory components? And some of them are inflexible, but many of them, all you need is really those rough boundaries. And then you need to step away and allow for enough innovation to kind of happen and autonomy to happen inside of the.

System, if you will, and the system could be inside the dynamics of a team or inside of a technology system, et cetera. When we think about return on investment, though it is a bit tricky these days, right? Because we’ve all seen the studies and the stats that, you know, if you just have top down, everybody needs to use AI every day, and this is what you have to do, that actually productivity gains don’t happen.

And actually it tends to be more expensive. And so when we think about [00:09:00] ROI. The fundamental question is, well, what is the value that you’re trying to capture? And what is the outcome? And so is the value increase human judgment? Well, we don’t really have a design metric for how you govern and manage and report out on that.

Or is it that we have increased decision making speed? Well, you need an understanding of what was before, what is current in there. And so frankly, we’re still navigating through some of those pieces. But what we’re trying to do is move from return on investment of being purely financial components.

In the Western world, we think very simply, mostly about, well, this is how many people I can let go of in order to, you know, achieve this new metric that doesn’t really work for Panasonic in terms of the way that we treat and manage our employees. And so finding different ways to really measure value that are that capture a broader kind of range of value-based components that we’re looking for in individual contributors and leaders.

And so we’re still working on it. It’s hard.

Luke: Well, I think that’s what’s cool about seeing you here, having you all, and, and what you were talking about earlier about how engaged Panasonic is with, with the [00:10:00] community and kind of picking up, that’s the only way you’re gonna find out what people want by talking to other people, right?

Like, yeah. Yeah, yeah. So what do you think the biggest gap is right now? As far as AI talent acquisition goes,

Elise: I think, hmm. I think one of the biggest gaps in terms of AI talent is figuring out how to how to find the right set of individuals who are deep, critical thinkers and how to not just take the first answer.

As we think about the way that work gets done today, a lot of times it is the speed of execution is what’s valued versus the quality or the thoughtfulness of the execution. Well, we all have the same access to the same intelligence on tap, so it’s very easy for you and I to both go into chat GPT or into clot or to whatever.

We have access to the same information. So if all of that is quite equalizing and you no longer have that deep, deep specialty that’s required to kind of get somebody over the hump, what’s the differentiator and what’s the extra value? And so I think it’s about finding and [00:11:00] then investigating and interrogating how somebody got to.

Some specific outcome that isn’t just your first pass. And so when I think about where LLMs are today, we’ve now gone beyond just kind of that core foundational knowledge that gets us all to that same point. And now those LLMs are being fine tuned for specialty. The same goes as we’re starting to think about AI talent.

How do we think about those deep specialties that can leverage the core and that get them to the same point of, you know, an executive or a leader who’s been doing the same thing for many, many years and add that specialty. So I’ll give you a great example. We have an individual on our team who. Has no technical experience and no business experience.

So she came into the team as my executive assistant, but this woman has incredible gusto and wanted to learn. So we equipped her with some AI training and said, off you go. And within the first six months, I have I have her on my team who is performing at the same level as some of my [00:12:00] strategists and senior members of the team.

Now what is being refined is her ability to critically think. She doesn’t have the lived experience where these other individuals do. So that deep thinking and referenceability is there. But from an equalizing perspective, it really has been this phenomenal like unplanned experiment to say, hold, hold. If my executive assistant who has zero business experience ever and has never really done anything in the coding world, is starting to create her own agents that are doing global program management.

Okay. Like, let’s, let’s go.

Luke: That’s awesome. That’s awesome. I mean, I think, you know, it’s kind of calling back to the questions earlier about like, shaking up organization. I mean, you’re doing it, it’s like the experimentation is like so key. And kind of being open about it. You know these AI amenable executive functions, you’re kind of talking about that second ago or growing idea.

Which executive role do you think will be most transformed first and, and what will that look like day to day? And, and maybe you just answered that, but I’m really kind of curious.

Elise: So. Earlier this year, I started thinking about the role of [00:13:00] HR or just as a resource officer, forget the human part of it, and the disruptions that have happened in that function kind of over the last 20 years or so.

So if you think about the role of a resource manager in a technology firm, over time, the role of A-C-H-R-O has actually diminished over time because there’s been so much outsourcing, particularly on the technology side. And so what that does is if you quantify someone’s value as an executive versus their oversight ability, any kind of technology outsourcing or call center outsourcing, that was then led not by the CHRO, those decisions were led and then managed by the CIO or the CTO, et cetera.

And so what the CHRO was kind of left with is this kind of interesting patchwork of a workforce instead of something that was more holistic. Now, as we see with generative ai, we see those investments being made mostly by the technology organizations, but that have massive human and resource implications because you’re actually building and deploying new resource.

In [00:14:00] fact, when we think about generative ai, we think of it. Effectively as the operating system of the future, and if not carefully watched and edited and cared for, that actually will redefine the culture from the technology out. And so this partnership, I think that needs to be created and cemented in a much stronger way between the C-I-O-C-T-O and CHRO.

I think that’s gonna be fundamental for the future because if you just have technologists who are excellent at launching and scaling and deploying global technology, but they’re not caring for ethics or culture or how decisions get made, we have a problem. If you go only to the human design and you don’t leverage the technology, you also have a problem.

So my punchline answer is, I think it’s the CHRO, and I think that those roles. Will change the most because it’s not just how you deploy your resource and having A-C-H-R-O now having to really think about business implications and resource implications. But it is also how do you incentivize employees who now have augmental second selves?

How do you think about, we were just in a [00:15:00] conversation a couple weeks ago with our CHRO about. How do you incentivize an AI agent that’s now showed up on an org chart? What is their promotion path? And it was kind of this like blah, like mind blowing kind of conversation. And I give them huge credit for just engaging my whims as we’re imagining this world.

We just developed our very first org chart with agentic human agent teams, and we’re playing around with these different hierarchical structures. And it’s really interesting, everything about how we get paid, how we get compensated, what makes us wanna work, what makes us wanna be visible. I think all of that is gonna change.

And maybe that’s. Also super exciting.

Luke: It is, it is. It’s really interesting. I’m just kind of thinking in my mind like, what does that org chart look like? And, and, and kind of even among agents kinda managing agents, right? Like for different things. But I really like what you were mentioning too around like having the different c team players kind of like working together because I think that.

Aside from even the human resource side, there’s a huge amount of like privacy implications for users, but also like within the org and sensitive information. And, and if you have people using all these tools making sure that they’re not [00:16:00] either where the, where’s the data going? Like are we, we giving proprietary stuff away?

That kind of stuff. It seems. I, I really like that idea that you have of like, kind of the collaboration between those two people. I mean okay. Like, just to kind of add, add some fun to it. What’s one area of Panasonic’s business that you think will look unrecognizable by 2035?

Elise: Well, if we do our jobs right, hopefully a lot of areas will look unrecognizable.

But the one that I think might be the most provocative is the way that we think about what happens after the purchase. So our after sale and customer support and ongoing support and maintenance. So today. When you buy a product, whether it’s an EV battery or a washing machine, or you know, a headphone or whatever it is, you as the purchaser kind of own the product and also own the reality of when it breaks or when you need something, right?

That it’s your responsibility to kind of move that forward and to figure out how to solve the problem by reaching out to the company. I think all of that after sale model will fundamentally change as we put more intelligence kind of into the products and services and the [00:17:00] ways that we service those customers.

Those products should, in theory, based on AI and a wide variety of other personalization components, they should self-heal, they should self maintain, they should. Predict the maintenance that is required. And so you go from kind of owning a product and then just saying, this is what I own, and somebody else is responsible for fixing it, to actually owning more of the value chain yourself as a customer where I now am purchasing this product and I’m purchasing it from a lifecycle perspective where this product is gonna tell me.

How do I use it the best? How do I optimize it? What do you need for it? And so it takes a lot of that. We, we hope a lot of the burden of having to call if there is a problem or if you wanna elevate your experience some way. I think those self-healing, self diagnosing, self predicting elements will fundamentally change not only how products are.

Used post-purchase, but also how they’re sold as we change the value proposition as well.

Luke: I think it managers are gonna have a much different experience too in this kind of environment. In a positive, in a positive. I think it’s really cool, like in accountants too, maybe.

Where can people follow along [00:18:00] what you’re doing and then also what, what Panasonic’s doing? Is there anywhere you wanna point people?

Elise: Yeah. So everyone’s welcome to come and connect with me on LinkedIn, which is just Elise Neal. You can also follow along in Panasonic’s journey.

Our AI transformation journey is called Panasonic. Go is the number five in Japanese, which represents the fifth era of transformation of the company. Our original founder, who founded the company 106 years ago, was the only founder that I know to set out a 250 year vision that’s broken up into 10 periods.

We are currently in the fifth period, which is why we are Panasonic Go. So it is an imperative to transform the company every 25 years. He’s an incredible visionary man. Of course he is no longer with us. And so Panasonic Go. You can search for our activities, what we’re doing, what we’re experimenting with along the way.

Luke: Fantastic. Thank you Elise. Really appreciate you making the time and love to have you back to me and revisit how things are going in, in the future.

Elise: Thanks so much, Luke. Best of luck at the show.

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