Fit Happens: The Executive Search Podcast

Jason Baumgarten 00:00
I'm Jason Baumgarten and you're listening to Fit Happens, the podcast where top leaders, investors and board directors share the stories, surprises and hard earned lessons behind finding the right fit. Let's get into it.
Jason Baumgarten 00:17
For most of corporate history, we've selected senior leaders partly by looking for evidence that they've seen the movie before. Pattern recognition, experience, a proven playbook. But in the AI era, can experience actually become a liability if it causes you to apply yesterday's playbooks to fundamentally different problems? So here's a paradox I'd love to start with. Is a leader who looks safe on paper becoming the riskiest person to hire? And what are the characteristics that used to look risky or unconventional that are actually becoming valuable as we enter this amazing period of change? Today I'm here with guest Liat Ben-Zur, who has had an incredible career and is a new author. And we're going to talk about both her career and her book on today's episode of Fit Happens. Welcome to the show.
Liat Ben-Zur 01:12
Thanks, Jason. Thanks for having me.
Jason Baumgarten 01:12
Absolutely. So before we assume that AI changes everything, I have to start with the skeptical: is it the real deal?
Liat Ben-Zur 01:23
Short answer? Yes. I've led through, I would say, at least four major technology shifts in my career. The Internet, mobile and wireless, IoT, and now generative AI. And every single one of those transformations really changed how we build products, how we reach and talk to customers, how we run our business. It fundamentally changed so many aspects of business. But this one goes deeper. Over the past three years, I've really been working with a lot of different companies across sectors, trying to help them figure out and operationalize their AI strategy. And what I've observed is AI is doing more than changing how we build products and how we do our work and how we reach customers. It's literally rewiring companies from org design all the way through leadership. And it's happening so fast that I think most people still don't see it. So it's definitely real and it has very big implications.
Jason Baumgarten 02:37
And when you think about you're sitting down with friends at dinner and this topic comes up, because I'm sure it now comes up more, what's the example you would share with people who maybe aren't deep in the tech industry? We're both in Seattle, we're both on the west coast, we're both surrounded by large technology companies and lots of engineers. When you're talking to people who are outside of that bubble, who maybe aren't spending hundreds of dollars a month now on LLMs, and you're like, here's an example of where I've seen this blow my mind, is there something that you would tell them that brings it to life?
Liat Ben-Zur 03:14
I think the biggest and most common thing that I share with those who don't come from technical industries is that AI is not like this new powerful, singular tool or solution that's going to solve some problem. It fundamentally simply changes how every single function works. Whether you're a finance leader, whether you've been an attorney for the past 30 years, whether you're an expert in supply chain, you're a marketer, you're a product leader, you're in customer service, it doesn't matter what function you're in or how many decades you've been doing it. AI forces you to rethink how you do your job. It forces you to rethink workflows, processes, things that you've done in the past, and offload a lot of things that you used to do on your own to agents, automation, and then reload, if you will, new challenges that come up because of all of these changes. But every single function in any corporation, it can be industrial, it could be automotive, it could be retail, it can be healthcare, nothing to do with tech, is being disrupted and should be disrupted. If you're leading an organization and nothing's changed in the past couple of years and how you do things, that would raise some eyebrows.
Jason Baumgarten 04:44
As somebody who's both been a very senior executive in very large companies and as a board member, you've also watched that anxiety between enthusiasm and pulling back. And we saw this with the Internet, where people raced and then after the dot com bubble, people were like, oh yeah, that wasn't such a big deal, let's pull back. Meanwhile, companies like Amazon and others quietly kept building. And for many of the ones who pulled back, they really missed opportunities. There's a lot of discussion right now about how capital expenditure on AI has gotten very high. The ROI is still not abundantly clear for many organizations. And I hear in a lot of boardrooms, boards being more concerned about, hey, great that we did a lot of pilots, great that we did a lot of experimentation, now let's bring those costs back under control and not get too crazy. Do you think there's organizations that are at this risk in the next year or two where they don't see through this change and they don't sort of bet on the bigger horizon of change and they sort of pull back to, you know, everybody gets a fifty dollars of coffee a day kind of concept with AI?
Liat Ben-Zur 05:56
A hundred percent. And I meet with those leaders quite often, the deep skepticism that this is just a fad and it's going to go away and I don't want to get caught up in it and everything's going to crash. But I think the bigger trend that I see, Jason, is like, probably like all things in our world today, you kind of read what you want to read and pull out the takeaway that you want to take away in the narrative. So those who are very skeptical can find a lot of examples right now in the news of why to be skeptical, where AI has gone awry, what are some of the negative consequences. There is no lack of examples to feed that fire. And those who are super, super bullish and just want to talk about how AI is transforming everything and how every company and every individual, our lives are going to be transformed, can find so many examples of that too. And like all things, I think in our personal as well as work world, the answer usually is in the middle. For a living, my focus is helping companies, helping leaders, whether I sit on a board or I'm advising operators, accelerate AI adoption. So I'm very much in the camp that believes that AI is about to transform every industry, every corporation, every function and every individual in incredible ways. Ways that are so epic that even the previous transformations in mobile and wireless and Internet will seem trivial compared to how much our world is about to change. Doesn't happen overnight, but it's happening. Having said that, the whole premise of my book is about why that can't just be done with our eyes closed, and why we need the right leaders in the room asking the right questions, the right skeptics challenging, the right governance, the right guardrails. You don't just kind of let it happen. It does require shepherding, and shepherding it in a thoughtful way with human interests, with ethics, with empathy. So I think the answer is somewhere in the middle.
Jason Baumgarten 08:11
Well, you started this journey from the book a couple of years ago. Let me start with just why write a book? What was the impetus behind it? And tell us a little bit about why you decided to take that leap. That is not a quick journey. So what got you excited?
Liat Ben-Zur 08:25
Yeah, I wrote the Bias Advantage because I just kept on seeing the same leadership patterns across totally different industries. And it started making me question about how companies were judging talent for the future. I've spent my career leading major tech shifts. And as I started working with these companies that were across completely different sectors, healthcare, consumer, financial services, enterprise technology, the leadership challenges I observed were common. Regardless of the sector, there are these leaders who really struggled with this AI shift. And they tend to be very highly accomplished executives whose authority had been built on hierarchy, on control, on being the person with the deepest expertise in the room. And all of a sudden they felt very unsettled by AI. They would get defensive when their decisions were questioned, when organizational silos started to kind of break apart. These are leaders that were excellent at optimizing existing processes, but they tended to freeze when we'd ask them whether we even need those processes anymore. Like, why are we doing what we used to do? And then the leaders that I observed that were really adapting well and leading through this shift successfully, they tend to operate in ambiguity very, very well. They would also not just accept all the data or all the answers that we're getting from AI. They tend to question the assumptions underneath it. They would pay very close attention to human consequences of the products, of the systems that they were building. They would notice weak signals very early. And there's all these patterns that I would start to observe about, I think, leaders that were successful and those who were struggling. And then the spark for the book came because while I was having these conversations in boardrooms and stuff, I was also mentoring a lot of leaders that I've known over the years. And there's all these brilliant people who had delivered major results, but they were being sidelined, they were being pushed out. And as I was listening to some of their stories, I don't know, there was just this aha moment when I realized some of these folks, they really learned how to operate without a map. And they built all of these, we might call them soft skills, but muscle that were built from adversity. That is exactly the muscle that AI needs today. And when I started connecting those dots, I realized I have a premise for this book.
Jason Baumgarten 11:07
Well, I'm so glad you wrote it. This idea that, and we saw this with the Internet, probably as the closest modern analogy, it really changed who rose to the top in a lot of organizations, and it also changed what was needed. It's interesting when you look at where the most value has been created in the public markets, it's a good public proxy, it's often from unconventional leaders. It's often from people who are difficult in many ways, who challenge the status quo, who don't do things the way everyone else does it. And yet we get taught that leadership is a certain thing. And actually leadership is about creating value and winning and having people do that with you. If you destroy value, you're not a particularly good leader. You might have followers, but they're not following you to a really good outcome. So I think this idea of really trying to separate the noise of leadership or the noise of experience from what is needed right now is very powerful. You're talking about AI changing work so fundamentally, whether it's in different functions, different parts of the organization, and you have argued that it really changes who rises to leadership roles. Tell us a little bit more about what your thinking behind that is. How does that change that pathway to leadership?
Liat Ben-Zur 12:47
Yeah, you know, if we look back for decades, I think one of the ways that you rose in a company is by becoming an expert. You know your function better than anyone else. You build a bigger team, you take on bigger budgets, you eventually kind of have this level of expertise and track record that gives you authority. And in many ways, AI is disrupting a lot of those signals. You can imagine a marketing leader who's built their whole career on managing a large organization that produces content and analyzes campaigns and maybe does some customer research. But now, all of a sudden, AI can do a meaningful amount of that work. So the leadership challenge changes. And it's not just about how am I going to use AI to automate what my team's been doing for the past couple years, but what does my organization look like if half of the work now could be done with AI or by AI? How do the functions in my organization, the silos, change? What should be collapsed, what new work needs to be created, what new oversight is needed? It's just a very different set of experiences that we need. Some leaders feel threatened when that expertise gets distributed, when their old ways of working that they're very good at suddenly get challenged. And so you need leaders that I think are more curious about what becomes possible, that can rethink their work, rethink how their team does their work, and also question a lot of the historical organizational boundaries and how to influence across those boundaries. That's some of the, I think, new skills that are becoming really relevant.
Jason Baumgarten 14:26
And you talk about the unconventional leader gaining power. How would you define unconventional? You've alluded to some aspects of it, but when you say unconventional, what does that mean?
Liat Ben-Zur 14:54
So unconventional doesn't just mean someone that is atypical. I'm talking about leaders who've had to learn how to operate in systems that just did not automatically work for them. And I want to separate out two things very clearly. Bias itself is not an advantage. I'm not trying to romanticize being underestimated or excluded or passed over. But the advantage is the muscle that some people have built navigating that bias. So if you've personally experienced bias, you tend to become very good at detecting it, and detecting it early. You will notice when the official corporate story doesn't quite match the lived reality in the office, or you'll notice who's missing from the table. You'll notice when supposedly neutral rules keep producing unequal results. You learn to read the room. You learn to understand even what people are not saying, which can sometimes actually say quite a bit. Now, if you put that into an AI environment, this becomes very relevant, because what we're seeing now is that bias kind of hides inside something that looks very objective, very mathematical. Right? A human opinion, someone raising their hand and saying, hey Jason, I think that we should move to the left, that invites challenge. But when a machine provides you a recommendation that we should move to the left based on a score, a ranking, an algorithmic recommendation, it kind of shuts the conversation down in a way, and I think that's dangerous. It's dangerous because AI learns from our own human history. It absorbs a lot of our old decisions, our old exclusions, and then it reproduces them faster and at much greater scale. So now you have this output, it looks polished, it sounds confident, and we start confusing consistency with fairness. And so that's why I think some of these unconventional leaders become incredibly valuable, because they've developed an instinct to ask who's missing, what's the proxy that we're using, whose experience isn't represented in the data, who's paying the price if we get this wrong. And when you recognize the texture of bias, you could see it even when it's wearing a lab coat, which I sometimes feel like AI is wearing a lab coat. So bias can stop sounding like opinion and it starts sounding like fact, and that makes this sort of bias detection a real leadership skill.
Jason Baumgarten 17:24
Yeah, I think it's such a powerful example. And AI agents in any setting, I always try to remind people, it's like having employees who are early in their tenure or early in their journey. It takes a lot of stewardship and leadership to get an agent to do the work in a way that is fitting, the same way it would an early stage employee. And yet somehow, because it's a computer, we expect it to not require that investment. In fact, I was just reading an article somebody wrote about the bottleneck of humans now babysitting their words, agents, and I took some issue with it because I felt like they were not addressing the fact of, if you don't spend the time improving the quality of the output of that agent, improving the training data you're giving it, improving the way in which it's trying to get to that outcome, you're not doing it a service. You're treating it like an employee who brings you the wrong answer and you say, no, that's wrong, and you tell them what the right answer is. You actually have to go through that journey of apprenticeship that I think somehow we forget that we're not actually very good at doing that with humans, and yet we skip over it entirely when it comes to a computer. And your coming up bias is like a very good example of that. If an employee did that, in an ideal world, we might call them out.
Liat Ben-Zur 18:42
You're exactly right. We're not always good at calling out that bias with humans, so just imagine when it's replicated at speed with agents. It's very, very true, and it's much more dangerous.
Jason Baumgarten 18:55
And it's much more dangerous with agents too, right?
Liat Ben-Zur 18:55
Because it gets encoded, and so it scales in a way that a human who maybe is making bad decisions will never scale.
Jason Baumgarten 19:04
Yeah, and I think it's important, because I think when people hear the word bias, they often think of DEI and some of the things that have been villainized in the last 12 to 18 months. It's also very important to recognize that this is very commercially important. If you're trying to reach a customer and you have a message that sounds biased to a huge percentage of your customers, they will not buy your product. It's your employees, it's your customers, it's your partners. And so I think that it's very important for people to realize, I think bias itself can be kind of a word that is easy for people to say, no, no, that's just, you're talking about this thing over here. It's actually pervasive in successful businesses. You need to have products that people can use, services that people want to adopt. And if you are automating that bias at scale in a negative way, you can lose competitive advantage. So, and imagine that in systems that impact hiring, imagine that in systems that impact your healthcare being denied, your approvals being denied, imagine that in finance where you're trying to get loans, imagine that in schools where your kids are trying to get accepted. Like at a societal level, these are very big decisions that are being automated, and really understanding and asking the right questions plays a massive deal. And we don't have to look that far. I mean, even when we look back at social media and some of the decisions that we made in social media to optimize for engagement, there was second and third order impacts that we're all paying the price for today, that will be the same with AI, so maybe even at a larger scale, given how many systems are now going to be controlled by these agents. So we really need to think hard about these second and third order impacts, and we need leaders in the room who are asking those sorts of questions.
Liat Ben-Zur 20:26
Yeah, it's such a good example.
Jason Baumgarten 20:26
I remember interviewing a social media executive very early in the advent of social media. He had young kids. I said, are your kids on your product? And he said, no. And I paused and I thought. Would you want them to be? Absolutely not. And I thought, okay, I probably should think about my own parenting approach to technology. Because I think for so many people, we're sort of in the iPad parent generation where it was like, many of us grew up with TVs with three channels or 13 channels, and then our kids are now, grew up with all of this explosion of technology, which, as a parent, you had this competing tension of you want them to use the latest and greatest stuff and be conversant in the world. On the other side, you're like, is this going to change how they think forever and negatively impact them? So technology always brings this duality. I want to talk about your own story for just a moment. You spent many, many years at Qualcomm, and then Philips and Microsoft, three very different kinds of companies, different cultures, different origin stories, different sectors, and different operating systems. And I'd be curious, because we always talk about fit in this show and the power of getting fit, right, when you're in a place that really works for you. One of the things I'd love to hear you talk about a little bit is what did you feel like you could always bring with you? And then was there a good example from your own career trajectory of having to really reinvent or shift to adapt in one culture where you really had to change how you operated to feel like you fit in better?
Liat Ben-Zur 22:33
Yeah, I could give a lot of examples of that. So first I'll say, I don't think I ever fully fit in into any culture. And every strength is also your weakness, every weakness is also your strength. And so we can talk about that a little bit. But in many ways, I think that unbeknownst to me, that became a strength, because it allowed me to challenge the status quo and ask the questions that those who I think were very comfortable in the environment didn't ask. And over time, what I realized is I kind of became the change agent that drove a lot of transformations in each of those companies. There was a lot I did to try to fit in. So especially in the semiconductor industry in the 90s and early 2000s, rose up pretty quickly, I was usually one of the only female leaders in the room, whatever room it was, one of the only female leaders on stage doing keynotes, CES, IFA, South by Southwest. And you notice that there's a lot of really inappropriate behaviors that you kind of experience. And you notice that I was so uncomfortable at times being the only female, that I was deathly afraid to come out as being gay, because that would be even more weird and even less of a fit. I was already not so much of a fit, being one of the only female executives. And so I hid who I was most of my professional career, until quite late, till I was quite senior. And I thought that was fine, because it allowed me to continue my career progression and be successful. Ironically, when I finally did come out, my wife and I decided to have kids, and there was this moment where I was like, I'm not going to have kids and raise them and be afraid to say who I am. Like, that's not how I want to raise my children. So when I finally did come out, I only then realized how much it actually impacted me as a leader, how much energy I put into covering that prevented me from building deeper connections with my team, with my colleagues, with people around me. And I think I actually was able to become a better leader after I came out, although that was a very scary experience for me. And so, the word fit is kind of a weird one, because I don't know, I never really fit in. And then you kind of experience this in a Silicon Valley tech world, and then you go to Europe and you're in this 120 year old conglomerate in Europe, and the boardrooms in Europe are a whole other cultural phenomenon that's very, very different from the tech scene on the west coast. And you learn again, what does it mean to fit in, and their expectations of kind of fitting was very different than the west coast expectations. Either way, you don't quite fit, but you try, right, you try. And the best analogy I could share is fish that have been swimming in the same sea for a very long time can't really describe their waters. They don't really notice that they've been swimming in a sea that's super, super salty and hazy and not very clear, and they've just been swimming in it. It's just like another normal day. And all of a sudden a new fish comes into that sea that's come from different waters and they share that, wow, the water here is murky, and how, don't you guys wish you can have clear waters, here's some other things that we can do. These are different fish that you've never seen before. And they're like, what are you talking about? Our waters are great. You've been swimming in these waters for a really long time. I don't know what this fish is seeing that. So there's benefits of not fitting in.
Jason Baumgarten 26:28
Yeah, fit can be overrated. It just depends on what you want to get out of your role. I have a colleague who many years ago wrote a book about culture called Fish Can't See Water, so I appreciate that example quite a bit.
Liat Ben-Zur 26:53
That's funny.
Jason Baumgarten 26:53
You touched on this issue of AI is pulling expertise up. So if you're the marketer who had expertise, your junior employee can now access that expertise, and probably even more expertise than you might have had, and make it accessible in that world. What quality becomes the differentiator for executives?
Liat Ben-Zur 27:13
Number one, I think systems thinking becomes enormously important. We're seeing that intelligence and execution are becoming cheaper, more abundant with AI, but that doesn't mean that businesses are becoming any simpler. If anything, they're becoming more interconnected, more automated. And so an AI decision that looks like a technology decision might also impact your workforce. It might change your cost structure, it might impact your customer experience, your data strategy, your business model. So executives who only see their piece of the puzzle, I think, become less valuable. I want the leader who can see how these pieces affect one another. Think of a company that's automating customer service, this is a common example these days. The obvious question is, how much money are we going to save if we start using AI? A systems thinker who is leading that team should be asking much bigger questions. They need to ask, hey, if we start automating this interaction, what's going to happen to our customer trust? What new data are we going to generate? Could that data improve the product? Could that data become a new product? Does this change what people are willing to pay for? What happens to the employees whose roles are now changing? Is there a new business opportunity buried inside what started as a cost reduction project? There's connections that need to be recognized, and I think that's the difference. The other thing I notice in great AI leaders is they just ask better questions. They understand the importance of problem framing. AI is only going to be as good as what you ask it, or what goals you set. So what are we really trying to solve? What are we optimizing for? What assumptions have we buried inside the question? Are we optimizing the right KPI? And if we optimize for that KPI and the AI does an incredible job, what's the second and third order consequences of just improving that? I think AI is going to do an incredible job answering the questions that we ask, but leaders have to be better at knowing which question should be on the table in the first place.
Jason Baumgarten 29:01
Yeah, I love this train of thinking, and I think so many executives don't actually think dramatically about the system, because they're living in it, right? To use your fish example, they're not being asked to reinvent or dramatically change the system, they're optimizing little bits of it to get to the next stage of their career. And the longer you're in a company, the more you tend to be rewarded for micro optimization. In fact, I just did a session on why do CEOs never get told the truth, and a lot of it was the same concept of, well, you're not rewarded, you're the same person who is the incredible entrepreneur who starts a company quickly, their employees realize that same level of entrepreneurial questioning doesn't really get rewarded. So they make little suggestions to be sort of helpful, right, oh, why do we paint the walls once a month, why don't we paint it every other, you know, but it's not really an important question. Whereas you're really challenging this notion of, ask the more important questions, which I love. And by the way, I think that's one of the most important skills on the board. Like, how many times have you sat in board meetings where 80% of the time we're focusing on questions that aren't going to move the needle, and we should be focusing on questions that will really have a bigger prize, and being able to think through that and stop a conversation that's super interesting, it's a little bit down in the weeds, we all care about it deeply, it's not a bad question, but we're the board, is this the right way to spend the five hours we have together? That mentality is the leadership skill that is needed in the AI era even more so.
Liat Ben-Zur 30:46
Yeah, it's a really good point.
Jason Baumgarten 30:46
I was talking to a board chair recently, and they said, I'm trying to get the board to spend more time on fewer questions. And it was really interesting, your normal board deck's 400 pages, board agenda is 20 items, and he's like, you're spending 10 minutes per item, and it's a lot of like, yeah, okay, that looks good, check, move on. And he said, but if there are two or three foundational questions we should be discussing, why don't we spend all day discussing those two or three questions? And he said the amount of pushback he was getting from seasoned board members, that that wasn't the way a board works. And he's like, but it should. And so he was going through this transformation in his own, and this, by the way, wasn't how he historically had run the board, so he was really trying to change the way it operated and the aperture, because he said, if I can come up with 90% of the questions we're going to ask and can come up with 90% of the answers management is going to use to answer them, we don't need to ask any of that in a board meeting. He's like, we should only talk about the things that are kind of around the corner and are either massive risks or massive opportunity, that's what the board should be spending its time on. I thought it was a very bold observation.
Liat Ben-Zur 32:02
Yeah, and I understand why that's hard, right, because when you do sit on a board, these are very, very smart, seasoned, successful people that sit on boards, and we all want to be valuable, we're not there to look cute, we're there to add value, you don't have that much opportunity to add value, right, and so there is this inherent desire to add value. And so sometimes you get into these discussions, and so how do you create the space where everyone can be heard and everyone can feel like they have, but scope it around the needle movers.
Jason Baumgarten 32:37
Yeah, it's a great point. One of the things you touch on is the mistakes boards and leaderships make around succession planning as they're confronting this AI transition. Obviously it's a subject very near and dear to my heart, having led hundreds of transitions and successions. What do you see as the biggest risks or opportunities?
Liat Ben-Zur 33:06
Well, I usually start by reflecting on, like, where are AI transformations failing, what are some of the patterns that we're seeing? And I think there's quite a few patterns, right? You're seeing a ton of these companies that are definitely already adopting AI, they have 50, 100 different AI pilots, but nothing is really impacting the bottom line, the P&L isn't changing. And so you start to dig in, you start to look at what's really going on inside the corporation, and you learn that they have AI automating a bunch of processes, workflows that were built four years ago, but instead of asking, should we be automating this, do we even need that workflow, should we be redesigning that workflow, they're just speeding up the way things used to be. Or you have teams that are already using AI and their work is dramatically faster, they're getting through their process 80% faster, but then they have to go through all of the internal processes, they have to get four VPs to buy off, they have to put it through 12 different committees. And so AI is accelerating the work, but the organization can't handle that acceleration, so leaders haven't really accelerated the organization. You have these companies that will go buy the latest and greatest technology from Anthropic, from OpenAI, from all these companies, they tell their employees the benefits of why they need to use it and they encourage them to use it, but they never change the incentives, they never change the behaviors internally, so employees barely use these things. One of the biggest ones I see is AI gets handed to a tech team, like the chief AI officer or CTO or whatever, some other team, they're in charge of AI, even though the real work is happening at the business, right, the real problems that AI needs to solve is happening inside of marketing, inside of product, inside of engineering, inside of customer support, inside of legal, but the individual functional owners, the CFO or the CMO, the CHRO, your head of legal, they don't feel accountable, they don't feel ownership of AI, they're waiting for the tech team to tell them what to do. For me, these are all examples of leadership failures more so than tech failures. So when I think about succession planning, I am looking for people who've actually transformed something, have they had to redesign businesses, operating models, incentives, what are examples of that, can they connect the dots between the technology that they've implemented or brought to a company and how that impacts very different parts of the system, like customer behaviors or internal culture, how are they on bringing people along, can they get different parts of the organization to change in a very disruptive environment like AI can create. And I also look for learning agility. This one's really interesting to me because honestly the next CEO is going to make consequential decisions about technologies and business models that don't exist yet, right, and we're already seeing that, like I'm playing with things that didn't exist six months ago, so it's really hard to hire just based on who has the relevant, quote, relevant experience, because I think the tools and the environment and the org structure, the hierarchy that you're used to, it's all changing so fast. And so really just trying to find people that are comfortable leading through big shifts, through big changes, and they're not looking for stability, I think those are some of the things that I'm finding is really relevant.
Jason Baumgarten 36:46
Yeah, it's such a good area to probe on, and I think often with those kinds of experiences come a higher rate of failures. And so the other thing I think people are going to have to grapple with is the sort of Teflon executive who's never had a setback or a failure, probably hasn't tried to do much transformation, because anyone who's lived in transformational roles can give you much longer lists of things that didn't work than usually the things that did. And the goal is, okay, each time you tackled it, did you get a little better at the success list being better than the failure list. A question on the learning side, you spent so many years in your career helping organizations navigate transformation, is there something that you've had to unlearn about yourself over the last couple of years as you've both transformed your career, but also really engaged in using AI differently, is there something where you've had to really reteach yourself?
Liat Ben-Zur 37:48
I feel like in the past couple years, I'm almost unlearning everything. I mean, I've been a product leader for a really long time, right, so I pride myself in my love and care for product experience, the aesthetics of products, the user journey, the flows, bringing PLG into Microsoft consumer business was a big part of what I did. AI just completely transforms everything we have ever known about product building and user journeys, and the whole PLG mentality of user journeys, the idea behind PLG, I think, is still relevant, but the awareness and onboarding and all that is very different with AI. And so there's just a lot of product building that you have to, and it's a perfect example of this, right, because I'm a seasoned product leader, I'm not going to use old, I'm going to use seasoned, I'm a seasoned product leader, there's a lot of wounds and scars and lessons that I've learned, and I pride myself on being the expert in the room that could share best practices and all the kinds, and now that is disrupted and in many ways less relevant. And so this is a perfect example of, for some leaders, that's scary and threatening and makes you want to dig in even deeper, and for others, you might lean with curiosity and just go play and test. And how does that change how we should be thinking about, and if your expertise in the room is no longer going to be just on providing that knowledge that you've given, where can you bring expertise to that conversation that still is relevant, that's a really great example of that.
Jason Baumgarten 39:28
Yeah, and I do think it's important for people not to give up on the benefit of their career journey. There's so many lessons learned that are still there. A great example is I always tell people, employees still need clarity, it's like, as a leader, you realize how, how do you become more and more clear in the direction you give employees, that isn't changing with AI, it's just that you have a whole other group of things called agents that need clarity too. Products still need product market fit, even if there's different ways to get there, or understanding how customers interact with the product, you still need to have that capability, that perspective, you may just use different tools to get there. But I think it's a great example for everybody of just watching somebody who's been so successful step back and relearn and rethink and use tools differently. Let's do our quick speed round and then we'll wrap. We'll start with common leadership advice that you actually think is not very good, maybe even terrible, and this kind of goes into the fit question, right, like, what can you do to fit in better?
Liat Ben-Zur 40:41
As a female, the amount of times I've gotten in my career feedback that I'm too assertive or too bold or too direct, or any of those things, if I could have gotten a quarter for every time I hear that, it would probably be equivalent to some bonuses. And those land, like those land pretty hard when you're trying to make an impact and do the right thing and help the organization, you think you're doing it right by sharing what the elephant in the room is that no one else is willing to say, and you think, and then you hear that feedback, it really makes you question yourself at a very deep level. I think there is an important aspect of mentoring employees on their journey of how to make a point successfully. You can make a point and ruffle so many feathers that your point will be rejected, and you can make a point that brings people along. I think there's very much value in that. And I think there is an aspect that is just unique to women leaders, that women leaders get, that male leaders never have to live through that. You just gotta learn to let it roll off your shoulders, and sometimes it's hard to decipher, but that's tough feedback.
Jason Baumgarten 42:05
Yeah, it is definitely something that is common leadership advice, and illustration pointed sort of at the wrong part of the problem, I think. On the flip side, what's the best career advice you've ever gotten?
Liat Ben-Zur 42:15
One of the best pieces of advice I've gotten is start with yes. The more seasoned you get, the more it's easy to start with no, because very quickly, someone starts to tell me something, my synapses are already going at 300 miles an hour, and I will find the 50 reasons of where there's holes in the thinking, what's missing, why this can be, and it's very easy to start with no. Whether it's looking at new opportunities, new businesses, new partnerships, networking opportunities, it's amazing where things will go when you start with yes. This doesn't mean you won't get to no, you very well may get to no, but give it a chance first. That served me very well.
Jason Baumgarten 42:48
I worked with an executive years ago who taught improvisational theater for many years before joining the corporate world, and he would take everyone on the yes and journey, and it became almost ridiculous. We were like, yes, and I think this is a terrible idea, but you would go with it. And by the end of the session, everyone was like, it became almost fun to try it. And I love that advice, and I think everyone should try it on for a day, try it on for a week, make it your yes and day, and see if it changes how people respond to you. Okay, you get to go back to the 25 year old you, just like yesterday, what advice would you tell yourself?
Liat Ben-Zur 44:01
I would say the hardest things that you are about to experience are going to be the ones that will give you the most advantage and edge later in your life. You won't realize it when you're going through it, but writing this book was a bit eye opening for me, because I open up in the book on some of the experiences that I've had that when I was in it did not feel like heroic stories that I would ever write about. They were very embarrassing, they made me feel small, but I got through it and I kept my head high getting through it, and the muscle that that built is exactly the muscle that we need now more than ever in AI. So yeah, persevere, it's good for you.
Jason Baumgarten 44:19
I mean, when Angela Duckworth introduced the concept of grit, I think a lot of people misunderstood it, and when you really dig into that research, you realize that exactly what you're talking about and what you champion in the book, this idea of these really hard things, and particularly when it's structural, when your organization or the community you're in, it seems almost all unsurmountable, as opposed to, well, I did something, I ran a road race, it was hard, yeah, it was hard. But just imagine if everyone else had it easier than you and you were doing it, how much harder would that be, how much more insurmountable would it feel like? So it's really powerful. One of the things certainly when I talk about fit, I talk about it a lot with the perspective of flow, when in those moments where you feel absorbed in the work, absorbed in the team, and it's always interesting what the hobby or activity outside of work was where we feel flow, is there something where you lose sense of time, where just you're in it?
Liat Ben-Zur 45:18
Yes, eating.
Jason Baumgarten 45:21
Oh, I love it.
Liat Ben-Zur 45:21
I love good food, good wine, restaurants, and I love sushi, and I love traveling the world for great chefs, and then not to be fancy, but just incredible experiences, I lose myself in those moments, I mean, talk about being in the flow, yeah, that's my flow.
Jason Baumgarten 45:43
Early in the show, I had the CEO of Big Green Egg on, which is an amazing outdoor grill, and he had amazing stories that he travels the world doing cooking classes with chefs, and his stories, I was like salivating listening to him talk about these experiences. So I think I'm with you on that one, I'm glad AI is not taking that away from me.
Liat Ben-Zur 46:07
Oh yeah, I'm still gonna eat. I have this running joke amongst my friends that my dream in life would be to have somebody who could run around the block while I eat, so if I could just transfer the calorie burn to someone else so I can enjoy the eating more, that's the business idea right there, Jason, let's do it.
Jason Baumgarten 46:32
Well, I had a trainer many years ago, and I was talking about working out more, and she just looked at me and she goes, Jason, you cannot outrun your mouth. And it was like such a perfect thing to say in so many ways, and I've always, I feel like I need swag that says you can't outrun your mouth. Now okay, we'll end on a fun note because you are so in the world of AI, you've got so many things you're working on, what is a technology product or service that you are just loving right now, maybe one that not everyone is using?
Liat Ben-Zur 46:54
Perhaps Grokbot, the new Grokbot that came out a few days ago. I have like 10 different bots right now that I'm just using all the time, it doesn't matter, from my phone, from whatever I'm doing, I have like the money guy, the deal guy, I have the web dev running a bunch of my developer sites, I'm using it for everything from marketing to shopping to buying tickets, to making reservations, and everyone in my family now is used to me, we have a conversation, I'll be like, yep, I'm gonna get my guy on it, and one of my Grokbots. And this is just such a great example of, didn't exist versions of this that were more technical and harder for, I would say, consumers to pick up, didn't exist, and now you can just imagine in six months, this is going to transform how so many people just do everyday things. And a lot of it has to do with people just realizing how to get started, it feels overwhelming, there's so much AI news out there, there's so many tools, you don't know where to start, if you're not living and breathing AI, you don't know where to start. I created a website to kind of help leaders that are like, just in HR, just in legal, just in finance, just in customer support or supply chain ops, where do I go to get started, what's relevant for me, what are success stories in my world, which vendors should I go talk to, what questions do I ask those vendors, it's like just helping people get started is sometimes half the battle. Once you start and you start to play with it, and this is a good, just consumer example, don't have to be a big techie to go, holy cow, this is amazing, it's so fun, and it's so fun to hear the energy people have around these tools and how they're impacting their lives.
Jason Baumgarten 48:46
Final question, when you strip away the title, the compensation, the prestige, everything else we attach to jobs along the way, and you think about just having a good career, what is having a good career in terms of having found that thing, is there something you'd share with people who are maybe earlier in their journey where you'd say, I felt like I had a great career when?
Liat Ben-Zur 49:18
I help others succeed, very simple, bringing other people along and helping others succeed, that's, you look back on your career, the most incredible products, the biggest strategies, you know, built one of the largest open source IoT products, it doesn't matter, no one remembers any of that, no one remembers any of it, no one remembers anything anyway, but the impact you've had on other people, whether it's just helping them with their career or just giving them the space that they needed, the advice, that's really what it's all about.
Jason Baumgarten 50:05
That's such a good thing for everyone to remember. Liat, thanks for being on the show. I do want to say the Bias Advantage, if you haven't read it, I actually buy physical books so normally I can hold up a book, I happen to read this on Kindle because I was traveling for the last like four weeks straight, but it's a wonderful book, it'll make you think, and I appreciate you sharing so candidly, not only on the show, but in the book, you really brought yourself fully to it, so thank you for that, thank you for giving that gift to so many readers, and thanks for all of the unique perspective on leadership, AI, and why bias can be a good thing when you're ready to hear it.
Liat Ben-Zur 50:48
Thanks for having me, Jason, I appreciate it.
Jason Baumgarten 50:48
Take care.