
Winning Season · 2026-06-25 · 29 min
Key moments - from our scoring
Substance score
40 / 100
Five dimensions, 20 points each
Erica Rooney reveals how large language models are systematically reinforcing historical biases by perpetuating patterns in training data rather than introducing new ones. Her starting point is striking: women AI experts at MIT's AI Powered Women's Conference asked ChatGPT to generate images of themselves based on its knowledge, and nearly every woman received the same image - a white male. Even Greg, a Black male CEO, received the same result, demonstrating how AI doesn't recognize minorities in leadership roles. Rooney frames this through four gaps in her book The AI Gap: the awareness gap (work visibility), authority gap (recognition and ranking), compounding gap (pay and capital disparity), and infrastructure gap (who shapes AI development). She positions Her Collective - a $684 annual membership platform - as an antidote, offering weekly coaching calls and hands-on AI training through a point-and-click model. The conversation emphasizes that organizations must prioritize access to AI tools for women and minorities, as skill gaps are already widening due to men being encouraged to experiment more. Rooney advocates for staying curious and developing AI fluency rather than mastering specific tools like ChatGPT, comparing it to learning to drive any car, not just Toyotas.
When AI experts at MIT asked ChatGPT to generate images of themselves based on its knowledge of them, nearly every woman received an image of a white male - sometimes with glasses or a beard, but always the same demographic. Even a Black male CEO got two images of white men, showing that AI defaults to depicting leadership as white and male based on historical training data patterns.
The four gaps are: awareness (visibility of work), authority (recognition and ranking), compounding (pay and capital), and infrastructure (who shapes AI development). Rooney emphasizes the compounding gap as most critical because capital equals power; women receive less funding, so they can't build wealth or scale solutions at the pace men do.
A year-long membership is $684 (about $57 per month), including weekly Tuesday coaching calls, access to a Mighty community platform with discussion feeds and themed rooms, and monthly point-and-click AI training sessions on different tools.
Rooney starts with values exercises to understand what truly drives clients, then helps them validate whether they actually want their stated goals or are pursuing them because they 'should.' This often reveals that clients don't want the CEO role - they pursued it due to external pressure.
AI fluency means learning to talk to machines and habitually asking 'how can AI help?' with any task, not mastering one tool like ChatGPT. Rooney compares it to learning to drive any car, not just Toyotas - the principle matters more than the specific platform.
Our reviewer’s read on each dimension, with quotes from the episode.
The conference anecdote about AI image generation and the explanation of why LLMs reproduce historical bias (pattern recognition on skewed training data) are genuinely illustrative, but the rest of the episode is largely promotional content for Her Collective, the guest's books, and her podcasts, with substantial filler and platitudes in the back half.
there are more men who are CEOs with the name of John than there are women CEOs. And so when AI, which is a pattern recognition machine, looks at the data
men in the workplace are being encouraged to use and experiment with AI at, uh, greater rates than women are. And it doesn't sound like a big deal, but that's where the gaps start to compound
The MIT conference demonstration is a vivid, memorable story that illustrates AI bias concretely, but the analytical framework underneath it - that AI reflects historical power imbalances in training data - is widely circulating. The 'four gaps' framing is semi-original but the episode never develops it with fresh thinking; references to Carol Dweck's growth mindset and 'be curious' add nothing new.
AI didn't necessarily get it wrong, right? AI is not introducing bias into our world. That Part AI is accelerating everything that it's been trained on
in a world where people dream in black and white, I'm asking them to see it in color
Rooney has genuine practitioner credibility as a former Chief People Officer, an author, and someone who works with Fortune 500 companies on AI adoption, and she is not purely a podcast-circuit thought leader. However, her positioning as 'the first AI expert' on the show overstates her technical depth - she is primarily an AI-literacy advocate and community builder, which limits the ceiling on practitioner insight.
I was still very much in the work. I was a fully employed chief people officer. I was still in tech
I go out to Fortune 500 companies and, you know, well known brands and I help them learn how to use AI
There are some concrete anchors - $684/year membership price, the 17% CFOs figure, the 'more Johns than women CEOs' statistic, the Mighty platform, 300+ podcast episodes, and a Silver Telly Award - but the four-gap framework is described without data, and the claims about Fortune 500 work and organizational AI access disparities are asserted without named examples or metrics.
A, uh, year long membership for her collective is $684. Like literally it's one meal out for a single person a month
only 17% of CFOs are women, it is going to automatically identify the pattern
The host asks mostly open, soft questions ('Can you give us an overarching view?', 'Can you tell me more about how the members interact?'), frequently inserts her own anecdotes and agreements in ways that consume time without generating insight, and never challenges a claim or probes for evidence - the conversation functions more as mutual promotion than rigorous interview.
What I'm hearing you say is be curious
I love that you do point and click inside of her collective because again, we're taking away the fear
Computed from the transcript - who did the talking, and the words that came up most.
A room full of women builders at MIT asked ChatGPT to draw them based on everything it knew. It drew the same white man over and over. That moment sparked Erica Rooney's new book, The AI Gap, and this conversation. Erica joins Jacqueline as the first AI expert on Winning Season to break down the four gaps quietly widening between who AI was built on and who gets left behind, and the surprisingly simple mindset shift that closes them. If you have ever felt like the tech wasn't built for you, this one is for you. KEY TAKEAWAYS AI is not introducing bias, it is accelerating ours. It is a pattern recognition machine trained on a history that was never neutral. When the pattern says most CEOs are named John, that is what it draws back. There are four gaps, and the costly one is compounding. Awareness, authority, compounding, and infrastructure. The compounding gap (contribution versus ownership, who gets capital) is where the existing wealth disparity threatens to explode rather than close. You don't have to learn ChatGPT. You have to become AI fluent. Mastering one tool is like saying you can only drive a Toyota.
Transcribed and scored by The B2B Podcast Index.
Speaker A: Hi, Winning Season family, welcome back to the pod today. Joining us, Erica Rooney is an executive, an author, the community builder. She is the first AI expert joining us on Winning Season. So, Erica. Hey. Hey.
Speaker B: That's very cool. I'm so excited. Thank you.
Speaker A: Likewise. You've just written a book, the AI Gap. But the story. Story that sparked this book kind of threw me for a loop. But I could relate to it a hundred percent. What happened?
Speaker B: Yes. Okay, so I have a podcast. I've got a couple podcasts, but this is my AI podcast voice, or victim. And it was selected to be the podcast at the AI Powered Women's Conference up at MIT M. So super cool opportunity to be surrounded by a ton of incredible women who are all, like, getting their hands dirty into AI. And, like, this is an important piece because I'm not picking people from the streets who are using AI or who've never heard of it. Right. Like, these are builders, these are founders, these are educators. And all of these women talk with their AI and they use it in a way that absolutely showcases their women. Right. So talking about being a mother, maybe they're talking about hormones or menopause or whatever. So you can't mistake that they're female. So, anyways, we're all at this conference. I hung back at the hotel, but I got the. The text thread of all of this, which is how I know. But while they were at dinner, one of the women had this idea to ask Chat GPT, like, based off of everything you know about me, and it
Speaker A: knows all of our business. Yep.
Speaker B: Generate an image of what you think I look like. Now, again, these are builders, these are founders. These are people who are doing the dang thing when it comes to AI, and they know more than anyone. And so they start generating the prompt at the table, and every single woman started getting a very similar picture back. And it was your Brad, your Chad, and your software developer dad. You know, a white man with a little bit of salt and pepper. Some. Some people had glasses, some people didn't. Some people had a beard, some people had no facial hair. But that was the image that we saw. And, uh, everybody at first kind of giggled a little bit because, of course, it was this old, pale, stale, white male that showed up. It just kept coming. One woman finally was able to generate an image with that prompt of her, and she got a female image, and she was like, oh, my gosh, I got one. Like, hallelujah. And as everyone looked at this image more closely, they had a little, like, poster sign, you know, like, you can buy at TJ Maxx. That's like, in this family, we live, laugh, love. Except for it was a motivational quote taken from, um, our girl, Ruth Bader Ginsburg, but altered just a bit. And the quote behind this woman said, we men belong in the rooms where decisions are made. Girl. That is what it said. And it's like, if that isn't bias slapping you across the face big time, I know what is. And you know, this conversation took place over a year ago. I want to make sure that that is known. But I also want to say this is still very relevant because I was just giving a keynote about the AI gap less than a couple weeks ago. And while I'm talking, the women in the audience were like, dang, I want to try this. They click back away. And a lot of them, all of them, but a lot of them generated yet another Brad Chatter, software developer dad. So it is still happening.
Speaker A: The crazy thing about that is I think if the winning season community is listening to this real time, you should run this and Tag Erica on LinkedIn and let her know the image that you get, because this is, um, unbelievable.
Speaker B: So let me tell you this too, Jacqueline. So I've got a business partner and a dear friend. His name is Greg. Greg happens to be a CEO, and Greg also happens to be black. And so I asked him, being a minority man, hey, run this prompt. Tell me what you get. Because it's different, right? It's not. It's not about gender now. It's about race. And he's like, erica, I work with AI so much, which he does. He's literally coined himself AI. Serious. He goes, there's no way. It's not going to understand. I've given it pictures of myself. I've told it I'm black. Like, there's no way. And I was like, just run the experiment. So of course he does it. And what does he do? Not one, but two images of an old, pale, stale, white male to choose from, because a black male could never be a CEO according to the LLM. Could you believe that?
Speaker A: I can and I can't. I'm like, we give these tools so much information about ourselves. So what is it in the LLMs that's saying, I'm going to override everything you told me and I'm going to change your gender and your race? In Greg's case, yes.
Speaker B: Here is the system and, like, here's why it does it is like, AI didn't necessarily get it wrong, right? AI is not introducing bias into our world. That Part AI is accelerating everything that it's been trained on. And what do we know about, you know, the training data is. It all comes from history. And what do we know about history? It's never been neutral. It's all been concentrated areas of power. And so when you start looking just at basic statistics, and this is what I tell people all the time, there are more men who are CEOs with the name of John than there are women CEOs. And so when AI, which is a pattern recognition machine, looks at the data and says, okay, wow, you know, only 17% of CFOs are women, it is going to automatically identify the pattern that the people who should be depicted like that should be a certain image. And y', all, we all know, let's just say it like, that image is of a white man, because that is historically, who has always had power. Like, take it all the way back to King whoever in England. Okay, guys, I'm, uh, not hating on the white man. I'm just giving you a history lesson. And. And that's what we have to remember. AI doesn't know who is capable. It doesn't necessarily take into context that this is 2026, and we know that diversity increases your revenue and all of these other things. It just knows what's common.
Speaker A: You also have the people leading these organizations. Many of them are cozying up to people who just think, at least in the us that citizenship look like one thing, and you cannot be an American if you don't look like this one thing. There is a different layer. The four gaps that you talk about in your book. Can you give us an overarching view? Also, I want to know what's the favorite gap to talk about?
Speaker B: Ooh. All right, girl. So we've got the awareness gap, we've got the authority gap, which that's really the distance between you're doing really amazing, strong work and having work that is actually being seen by the people, by the LLMs. How are they being ranked, all of that? So awareness gap, authority gap, the compounding gap, which, for me, that is the distance between the contribution and ownership. And that's where we start talking about dollars and income. We also have what I call the infrastructure gap, which is really the distance between who is participating in the system, who is actively shaping what comes next. Right. And who is sitting it out. Right. Who is creating the infrastructure, who becomes part of the infrastructure. And, uh, I think. I think the most popular one to talk about is the compounding gap, just because it's all about our Dollars. We all know that women have been underpaid for the same work that men do, and that our, uh, women who are people, you know, identify as a person of color, any black woman is making even less. Like, the data is there. I don't even need to dispute it. Right. Nobody does. And so my concern, and I think a lot of other people's concern, is with AI scaling everything so rapid, we have this gap that we haven't closed. It's just going to expand even further. And what's interesting, too, is when we're talking about the compounding gap, we're not just talking about the pay gap. Right. But we're talking about, like, who gets capital, who receives funding. What do those people look like? We already know, for women, it's a very small number. And so. And again, people of color, even tinier, you know, small pieces of the pie. And so to me, the compounding gap, it's probably one of the most important, because when you have capital, you essentially have power, or at least you can build it. So I think that's probably the most fascinating one.
Speaker A: Appreciate that. There's this theme that's coming up in my, uh, conversations, the ones on the podcast and offline, gender equity and the wealth disparity. And that's exactly what you're hitting at with a compounding of impact. When I started my work in gender equity and the pay gap, I learned that it was 78 cents on the dollar.
Speaker B: Uh-huh.
Speaker A: That women were earning a decade later. That hasn't changed 50 plus years from the equal pay legislation. That hasn't changed years after Obama signed the Lilly Ledbetter Act. Still, nothing has changed. But I do see that AI could potentially help us close that gap with the compounding gap. What are some of the ways that you are building pathways to close that with the organization that you founded, her collective?
Speaker B: Yeah. So one of the biggest solves for this is really investing in your skills as it relates to AI. And that's why, uh, when I originally. Yes. When I originally launched her collective, it wasn't necessarily an AI training platform. It was a community where women could come together, they could harness the power of connection and executive education. All of the things that I wish I had had on my climb into a chief people officer role. And my issue with that was I didn't have the funds to get access to that kind of education. I mean, I remember many people don't, girl. I remember talking to a coach one time, and I was like, this is what I need. I'm new to The C suite. And she came back and she was like, oh, it's a ten thousand dollar commitment for three months. And girl, I about fell out of my chair and passed away. I was like, I got these two little kids, like $10,000, girl, that'll take me to Aruba for a week. And I remember feeling so, uh, oh gosh, like it's not for me. Like I'm just not gonna have to figure it out. It's not for me. I can't afford that.
Speaker A: You know, I have to say I can relate because the first time I found a coach that I was like, oh, this person's gonna help me do it. When she told me it was 50 grand, I like looked over the back of my shoulder like, who is she talking to? Cause she's not talking to me.
Speaker B: I got a lottery ticket back here, a winning.
Speaker A: So you make her collective accessible for all women. And also you're taking away the shame of like, because when coaches quote those big prices, then you start to internalize it, like, oh, have I really effed up? I don't have enough money to invest in myself.
Speaker B: And you must not be like all those other C level people out there, that part.
Speaker A: But you're taking that shame away and you're making it approachable.
Speaker B: Yes. I mean, girl, A, uh, year long membership for her collective is $684. Like literally it's one meal out for a single person a month. And yes, the level of access, the frequency of access, like we meet every single week. Right after this call. I'm jumping to a coaching call. But as her collective grew and as this AI era really kind of came upon us, like this big wave I had kind of started, not kind of. I had leaned into AI to help me with my own business. And I was completely self taught. Like, I am not a techie person. I tell people all the time. I was the chief people officer, I was a fitness instructor. I was never a coder, I never did any of that. And uh, if I can teach myself these tools and I can teach them to others, like other people can learn them. We just have to help them get there. And what's fascinating about AI is it really is a mindset. It is all about do I believe that I can keep going. And I'm a huge believer. One of my partners calls it the Great Unlearning because he's very big on, we have to unlearn all of the ways we used to learn and learn a new way. And I'm like, no, I think we Just got to switch that mindset shift, which is all about unlocking infinite possibilities, right? And I.
Speaker A: You're speaking my language. Yes.
Speaker B: I tell people There are 52 ways to get to Texas. Probably more. Right? You get to pick which one you want to do. And so inside her collective, every single month, at least every single month, it kind of depends on what the women are interested in. We dive into a tool, we do pointing and clicking, and we learn. But one of the most interesting things that I'm seeing is, and this is what I really want people to know, is you don't have to learn ChatGPT or Claude or Co Pilot, right? That's like saying, I only know how to drive a Toyota. Like, right? You just have to learn how to be AI fluent, how to be AI native, how to be an AI architect almost. And a lot of people are like, okay, whoa, Eric, I don't even know what that means. It just means two things. How do I talk to the machine? And when you go through your day and you're thinking about all the things you gotta do, right? Whether that is plan a family vacation, map out a project for work, you know, pull stats, whatever it is, you should be thinking, how can AI help me with this process?
Speaker A: What I'm hearing you say is be curious.
Speaker B: Always, always be curious.
Speaker A: One of the ways I'm similar to you, I don't have a deep tech background, but I built five tools end to end with AI. I simply got to the point where I have this idea, or, uh, this is how I'm living my life. This is my morning routine. What can you help me with? It'll give me some ideas. But I love that you do point and click inside of her collective because again, we're taking away the fear, we're taking away those barriers, and yes, you're unlocking the mindset. I'm a big fan of Carol Dweck with the growth mindset.
Speaker B: Yup, A hundred percent.
Speaker A: And what I'm hearing about her collective is you're going from fixed mindset to, uh, a growth mindset in real time every month.
Speaker B: Yeah. I like to say in a world where people dream in black and white, I'm asking them to see it in color and never seen that before. It's impossible. It is impossible to imagine. But when you have someone who is, you know, clicking and pointing and showing you and, oh, uh, also messing up in real time showing you how do they fix it and what happens when they get stuck, you start to see it's never really a dead end. You Know you're not gonna break anything and you just have to get your hands dirty. You have to get familiar with it. And the curiosity piece, you can't let what appears to be a dead end stop you.
Speaker A: Can you tell me more about how the members interact inside of her collective? I'm really curious about that.
Speaker B: Oh man, we are all up in each other's business all the time is what I tell people. It's um, a. It's become this awesome tight knit community, but also so expansive at the same time. And I really attribute that to the fact that we get together every week. Tuesdays at noon is when we come together. Everybody has that time on their calendar blocked. We run through a three step framework just to get a high level heartbeat of where people are. I call it the her framework. And it's what are the highlights going on? What's the energy behind those highlights? Because, for example, you might have a really amazing highlight, like my kid just graduated fifth grade, but she might be freaking exhausted because not only do you have that, but you also have all the other things going on. R is the real talk. What do you need right now? Or what are you able to give, right? If you're in a great place and you're like, hey, things are rocking and rolling, you are there to pour into others and sometimes those other people pour into you. But we exist on the mighty platform. It's almost like this glorified. Think of it like a Facebook page, right? We've got a feed where people can type to each other. We've got different rooms where they can go in. So if they have a different theme or a different need, they can go to, to the, um, it's like a give get where they can say, hey, I really need a good book recommendation. And like here are my book recommendations. Or it could be I need a connection to someone in this company. Does anyone have one? It could be anything from I need ideas for healthy dinners, you know, that are easy to cook in under 30 minutes, which I've seen all the way to. I have an interview with the CEO. Can someone jump on a call and just run through these questions with me or tell me if I'm not here thinking of something real quick. And so it ranges from all over the place, but a lot of it occurs in the app for the most part. That's where we communicate, go back and forth. But the real connection moments are absolutely inside, uh, those live coaching calls.
Speaker A: So the AI Gap isn't your first book and I can imagine that the glass ceiling work that you've done and yourself. Breaking the Glass Ceiling lays a strong foundation for members to be able to show up and be vulnerable and be brave. Can you walk us through the highlights of your first book?
Speaker B: Oh, my gosh. So what's so interesting between the first book and the second book is that first book, I was still very much in the work. I was a fully employed chief people officer. I was still in tech. It did not come out until one month after I quit my job. So. And, um, I just want that context to be there. I was still very much in that public facing role, acting as an officer of this company. I go into my personal life a lot, but I still had to stay a little guarded just because of where I was at in my career. But I dive into things that, you know, impacted me along the way. Uh, imposter syndrome, perfectionism, fear. The burnout was real, right? Alcohol and addiction is in there. Like, I go deep into those things. And every woman that I talk with is like, yes, that lands. Something lands. I only ever talked with one woman who said she didn't have any sticky floors. And I was like, girl, I think you have missed the memo here. Yeah, thank you very much. But allows people to open up and be real. And what I will say is all those years I spent climbing the ladder, feeling inadequate, questioning my worth, drinking too much to hide the stress and all of that, hearing other people's stories is really what got me through. It's what made me feel not so alone. And so when I talk to people, I talk about all the ugly stuff that's in that book. Because, you know, being open about those things is what reduces the stigma as well.
Speaker A: I could not agree more. It's like you're holding up a microphone and a mirror and you're saying, I want to hear your story. Here's mine. And I see you. And you can move past this. I can also see how this is really impactful for those who work with you in the coaching capacity. And what does coaching with you look like?
Speaker B: So I'm really trying to direct most of my people inside her collective just because that is. That community piece is so big. Uh, but for when women need that one on one time, there are a couple different ways they can do it. They can truly sign up for a three month package where we dive in, we talk about what are their values. Because I need to understand, understand that from a very human level what drives them. And I think a lot of people give these values exercises, kind of like a raised eyebrow, maybe like a Rolling of the eyes, like, what do you mean? Values, Erica? Like, that's what we put on these corporate walls. Come on, girl. And I'm like, no, that's where you have to start. Because that's where you can start to identify your boundaries and your goals and what you're after. And so we really start with that. And we start with, what do you want to do? And what's interesting is when you start diving in there, a lot of people think they know the answer, but they haven't done the deep work, validate those answers, you know. And so then we start going, girl, I will sign someone up who's trying to go through a CEO coaching role. And like, they're gung ho about it. And by the end of that role, they're like, I never wanted to be CEO. I just did it because I quote, should.
Speaker A: Yeah, we sometimes follow those paths. I think I should do this. Or this is the natural next step. I'm an AI girly through and through. I'm, um, spending hours each day. AI cannot replicate what a human coach gives you. Where a human coach will step in and say, tell me why? Because AI has, um, sycophancy. Right? It's trained. Let's go back to the original story. The LLMs are built to tell us what we want to hear, to keep us engaged, and you're interrupting that pattern. I want to go back to the AI gap. If an organization is asking, how do we help our teams consider AI gaps that they're growing, where would you tell them to start?
Speaker B: Gosh, access. Access for everyone involved. Because right now what we're seeing is that men in the workplace are being encouraged to use and experiment with AI at, uh, greater rates than women are. And it doesn't sound like a big deal, but that's where the gaps start to compound because their skill gaps start to close and ours start to widen, and we get left behind. They have this reason to say, we don't need to close the pay gap because, uh, this group is skilled in AI, but you're not so much. But not only that. It's like we have to get our hands dirty and in the machine so that we can start to correct the way the machine is developing before it really just codes into existence. And I know that sounds dramatic, y', ah, all, but, like, let's just think about how history has evolved over the hundreds and hundreds of years. Things get set in stone very easily. And once that happens, it is hard to break. And with AI, I mean, it can scale businesses and ideas and create wealth so easily that if we aren't involved in it, when I say we, I mean all minorities, women, people of color, lgbtq, neurodivergent, all of those groups. We're going to get shut out with the access gap.
Speaker A: We cannot wait for our organizations, say, here, I'm giving you access. You have to be professionally annoying. You have to continue to raise your hand and say, hey, I want in. Or, uh, even trying this on your own outside of the workplace and in groups like Her Collective, where you have opportunities for those point and click experiences. Because nobody's coming to save us, y'. All. Winning season community, you know, we gotta get in there and do it on our own. Erica, um, we have to have a part two, but I know you have two podcasts.
Speaker B: Yes.
Speaker A: Can you give us an overview of each podcast? Because I want people to be able to go deep with you.
Speaker B: Yes. I mean, that's the best part, right? If you're listening to podcasts, love them. Glass Ceilings and Sticky Floors was the OG podcast. It's what I started that led to the book. It's had some incredible guests like Hala Taha, Kim Scott, who wrote Radical Candor, Incredible AI Women Builders. Gosh, that show's been going on for years. It's got over 300 episodes. But that is where we really talk about. I, uh, know.
Speaker A: Right.
Speaker B: You know, achievement Girl. You want to talk about imposter syndrome, all things. Oh, I only have five episodes. I'm never going to have, you know, all that BS talk we give ourselves. But now here we are and the podcast is thriving and it is such an incredible opportunity that I get to do every week with, you know, different amazing women like you. I mean, I know you get it, you run a podcast, too. But we talk about the Sticky Floors and what it takes to overcome that because for so many people, it's different. And I think sharing those stories, just like I said earlier, is such a big piece. And my second podcast I'm a co host of, so I actually co host this with Greg Boone, who was that tall black man I was telling you about earlier. AI Serious. And we really wanted people to understand that, like, are you going to use AI as a voice or are you going to become a victim of it? And it's a little harsh of a title sometimes, but we dive in and I mean, it actually won a silver telly award this year. So I'm pretty pumped about how it's. Yeah. How it's turning out, but we've got to get those conversations out there. We talk with different leaders and, uh, in season two, we're even starting to break down into smaller steps, like some of the frameworks that we teach when we go out. Because part of what I do also is go out to Fortune 500 companies and, you know, well known brands and I help them learn how to use AI as well.
Speaker A: Erica, I cannot wait to have a coffee with you in person. Are you coffee or tea girly girl?
Speaker B: I'm a tea girly. Um, believe it or not, I hate coffee.
Speaker A: Okay, not a problem. Next time you're in New York, we're gonna go to Morgan's library, the J.P. morgan Libra, and have tea. Is incredible. This work is phenomenal. And I love that your commitment to people extended beyond the title that you held. You were not just a chief people officer for one organization, you are chief people officer for the community. Bringing us together and pulling these different nodes. And ah, I so appreciate your work.
Speaker B: You know who said that? Because I think one of the perks that I undersell is the fact that I have this chief people officer background. You know, like, I know the ins and outs of how these organization makes decisions, whether it's ethically or not. I've worked at a lot of different companies and so you need someone who's got that knowledge in their back pocket who can say, oh my gosh, you are facing a riff like, what just happened? Let's talk through your options. Let's go from there. Rather than someone who's just like, what?
Speaker A: That brings me to another point. A call out for the winning season Community. I know a lot of y' all personally and, uh, you've worked in the HR function and people ops. So Erica is someone you definitely want to connect with on LinkedIn. Get her books, get the podcast, add it in your rotation. And yes, I'm doing a heavy sale of Erica because I believe in her work and the message that she's delivering. It is something we all should be paying attention to. So, Erica, I kind of took the thunder away. I usually say, tell people how to connect with you. Hey, girl.
Speaker B: Uh, I love it. I love it. I'm gonna have you be my hype girl every time I go somewhere. Somewhere. Now
Speaker A: I got you. What's a parting piece of advice you would like to leave with the community?
Speaker B: You're never stuck. And what is hilarious about that for me is that was what I always said with my first book, because it's all about getting unstuck. But now you've got this power of AI. You are truly never stuck because. And, y', all, if you didn't hear anything else today, if you get stuck, what do you do? You ask the machine, and it's gonna give you an answer. And stuck.
Speaker A: Until next time, continue to emulate excellence and eliminate excuses.
Speaker B: Oh.
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