AI and Women: Breaking the Next Glass Ceiling 🚨
In this ATD conference presentation, Margaret Spence argues that artificial intelligence will become the next glass ceiling for women and other marginalized workers unless talent‑development leaders act now. She frames the discussion around three core ideas: (1) the current state of women in the workforce – high representation in entry‑level and low‑visibility roles, low representation in senior leadership, and a learning ecosystem that is 99 % gated for women; (2) the rapid, global AI disruption that threatens 79 % of women’s jobs (administrative, clerical, service, medical imaging, etc.) and disproportionately impacts Black, Latino, and offshore workers; and (3) a concrete, talent‑development‑centric solution set. Spence proposes that TD professionals become “AI translators,” build baseline digital and AI literacy, create gender‑inclusive AI governance, develop avatar‑based learning pathways, embed AI up‑skilling into existing programs (carve‑in), use gamified lunch‑and‑learns, and champion equitable hiring, mentorship, and reverse‑mentorship. Throughout, she interweaves personal anecdotes, audience polls, and Q&A to illustrate fear, cultural considerations, and the need for immediate action. The talk ends with a 40‑question toolkit, resources, and a call for TD leaders to shape AI rather than be shaped by it.
Chapters
and is equipped and ready to achieve it. Please help me welcoming Margaret to the stage. Woo-hoo! Woo-hoo!
So as we think about women's and women leadership development, let's talk for a moment about the impact of AI. When you think about the work that you do in talent development, oftentimes you're thinking about the exact women who are in your audience, in your organization, a part of your teams. But today I wanna challenge you to think differently. Today, as talent development leaders, we are going to disrupt what we think we know and really reengage around AI. This session is not about prompting, it's not about the software, it's about the disruption. And I think we need to talk about it. So the work that we do starting today is not for the individuals in your organization today. The work that you are doing is for the little baby that was born a minute ago. It is for the child who is a day old. It's for the child that is a week old. Because if we get this right and if we do what we are supposed to do correctly, then that child will enter a better world of work. Imagine that if you're born today, 20 years from now, you will enter a world that will probably be 100% driven by AI. And so while we think that we're planning for today, we are really planning for the child that is in kindergarten. Your future workforce. And if we don't think effectively about our future workforce, the decisions we make around artificial intelligence in our organizations today will not be effective for those who are coming next. So I'm challenging us to think differently, to think 100% differently about what we see. And how we see it. So where are we right now in terms of women? 48% of women are in entry-level roles in organizations globally. 29% are in C-suite leadership roles, meaning they may not be the C-suite executive, meaning the CEO, but they are in some kind of a CEO role. Women of color are 7%. White women are at 22%. So what's left from that is the 1% divide between all the other categories of women. But women hold 59% of the bachelor's degrees that are being issued globally. Men are not getting the degrees. Women hold 90— almost 90— 80, 90% of the master's level programs. And we outpace men at the PhD level for non-STEM degrees. When it comes to STEM degrees, men outpace us by hundreds of percentages. When you think about these numbers, it should help us think very differently about what we do. So the question is, Where are the invisible women in your organization? Where are the women who are totally invisible right now? Let me tell you where they are. They're on your factory floors. They're in your manufacturing plants. They're in your clerical positions. They are in the low-level roles that we expect the work to be done, but we never see the individual who is inside of those roles. So one of the first questions that I want you to think about as we go through the process today is where are the invisible women? And that is the first question. The bigger question that I want you to really contemplate when it comes to women and women's leadership development and women's impact in the workforce is, is learning gated or is it open access? And this is a critical question. 99% of learning for women is gated.
99%.
There's only 1% of learning that's not gated for women. It is the things that you say, okay, you need to have PowerPoint or you need to learn how to use Microsoft or you need to learn how to be a good customer service rep or you need to be able to handle you know, bad customers. But when it comes to the development process, we still ask women to go to a leader who in themselves may not be connected, who may be a lousy leader, and we ask that individual to make a decision about a woman's future based on their current dysfunction. And 9 out of 10 times, a woman gets told no. For development. I'll give you an example. We run an external leadership development program, and we were running those programs internally for many, many years. And I started to see the, the level of women that were coming to the program were not the ones that needed the program. And so we opened it up outside, and we made it at such a price that any woman could purchase it for developing herself. And what I found is that the women who showed up for that program would tell me stories like, I've applied for our internal program 15 times and I've been told no. I've asked my manager if I could do X, Y, or Z and I've been told no. And so what we end up getting are the women that have been told no, and they're so scarred from being told no that the entire thing you do in a program that's supposed to develop them is rebuild their confidence. So this is where we're thinking and this is where we're starting. So when you think about this, I want you all to just sit for a second with AI. So let's talk about AI. When Facebook came onto the scenes, it took Facebook 10 months to get 1 million users. It took Netflix almost— to get a million users, it took them years. To get 1 million users. When ChatGPT jumped onto the scene, within 5 days they had 1 million users. I was watching something on C-SPAN last night and the former president of Google was there saying, "AI needs so much electricity and it needs so much of this, that, that, and the other to run it." that we need to start building mega nuclear plants every hour on the hour to cover the AI that's coming. And I thought to myself, okay, what are we doing as a world? Not even as a country. Let's just talk about on a world standpoint. But when you think about it, in every 3 to 6 months, the AI improves. So there's been a 170% increase in jobs that require AI. And this is from Indeed in March. I spoke on this subject at South by Southwest, and I pulled the data in March for that presentation. And so what we are seeing is there are new roles that are being created that are built around AI. There are new processes that are being created that are built around generative AI, but these roles did not exist before 2022. So that's another critical piece. So this is what I wanna say to all of you. How many of you went to an AI-driven class since you've been at the conference? How many of you? And how many of you went to a program that was built around prompting, writing prompts, talking about the software? How many of you visited a vendor in the exhibit hall where you looked at an AI software that you were thinking about using in your organization? All the hands went up. Almost all. Okay. Here's what I want to tell you. A prompt won't fix what's wrong with us, and the software won't help us either. So I'm gonna go through some datasets and I want you to listen to the data, and then I'm gonna ask you some questions at the end, and we're gonna do 3 mentees. And I want to ask you just to participate because this is not about me talking and standing here talking. This is about me meeting all of you where you are and challenging you to think differently about what you're doing. So here are the numbers. 79% of working women are in occupations that are susceptible to disruption by AI. That is 80% of women working today, almost. Where did I get this number? The World Economic Forum, Randstad, Udemy also put out a report on this. And this is recent. These reports came out in February of 2025. So this is not old data. The study by Goldman Sachs said 79% of working women compared to 58% of working men are in jobs that could be impacted by generative AI. Research by the Keenan Institute says 8 out of 10 women, 79% of the US workforce, will not have a, a recognizable job by 2030. So the decisions that you all are making in the exhibit hall and in the programs have to include who is going to be disrupted. And your voice has to hit the disruption. So let's keep talking about the numbers. What jobs are going to be disrupted? It is administrative roles, because right now many of us can use ChatGPT to write an article. So it's administrative roles, legal support, it's medical documentation, it's language services, it's medical imaging. I'll give you a funny, funny joke. I was scrolling through Instagram this morning, and there's a doctor who's a— he's a radiologist, and he was looking at an X-ray for somebody that had pneumonia. And he says, I spent 25 years learning how to read this X-ray. The AI did it in 2 minutes. So basically what the hospital is doing is using the AI to first read the X-ray before the doctor gets it. And he says 100% of the time, the AI is correct. So he's thinking about getting a job at McDonald's. That's what he said. He says, I see myself being obsolete in 5 years. And that's a physician. So medical imaging is a big deal. Customer service, content creation, financial analysts, marketing research, recruitment, talent, we are all on the AI menu. Every single one of us is on the AI menu. So it's up to us to now say, how do we do this ethically? How do we do this consciously? And how do we raise our voices in the arena so that we are saying what needs to be said and we are advocating in all areas of the AI process? Let's keep going. So disruption. How many of you know what the definition of disruption is before I change the screen? How many of you knew that? Well, you knew because I told you. Disruption is defined by having more than 25% of the occupational task potentially automated. That means the 75% that's left is not a full-time job. I was at South by Southwest in March, and I spoke about the radical economics of upskilling women for an AI future. And there was a gentleman there that he wrote a book, The Future of No Work. It's an excellent book, and I was going to put it in here, but I'll put it on one of our pages. It's called The Future of No Work, and it was an excellent book. So will women be included in the stakeholder discussions on automation? Let me keep going through the data because I really want to get to talk to all of you about what you're thinking. Globally, women are less likely than men to have opportunities for upskilling. Globally, 35% of women report that they've never been provided AI training, but globally, women have a a digital gap, meaning most women don't have a computer. They don't have access to the level of sophistication that we might have in the global north, meaning the G8 countries. So if you're living in the global south, you do not have access to this. But I'm gonna explain why this is important, why this is super important. So I wanna talk about the impact for Black professionals first. 24% of Black workers are in jobs with over 75% automation potential. 53% of Black workers worry that AI will replace them. 45 million jobs held by Black Americans are at risk of automation and displacement by 2030. This should scare all of us. So it's not just women, and I want us to see that the numbers are not just women. This is a $43 billion economic impact to the Black community. But we're gonna talk about all of it. I'm not focusing on any one group. I want us to see this big impact of what we're doing. When you think about Latino workers, 52% of Latino workers are in automated jobs, and in California, 38% of the state workforce is at risk of being disrupted, right? 2.3 million Latino workers alone in California are in roles with high automation risk. So here's the question. Let me, let me pose the question for you to think. I remember when my kids were young. I have a 40-year-old and a 32-year-old. My 40-year-old started at the supermarket as a cashier. He was in high school. It was a weekend job, and he started in that role. And it was my way of helping him understand what work was all about, creating the foundation. You go to work, you get a paycheck. Oh, you save the paycheck.
You—
so, you know, as parents, we go through this whole process. My younger son didn't work until after high school because he ran track. So because he was running track, he didn't have a job. But when he graduated from high school and he started college, he went to work at Macy's in the shoe department. That's an entry-level role. If we automate every single entry-level role, how do people get their start in life? If we do that, how does that happen? I wrote an article. I posted it on LinkedIn. If you follow me on LinkedIn, you'll see the article I wrote about the fact that, um, Shopify said no humans will be hired, only AI. Grammarly just came out and said no humans will be hired, only AI. In fact, Grammarly took it one step further. They laid off their entire entry-level and clerical support roles. All of them gone in one afternoon a few weeks ago. They said they don't need them. They only need AI. So if that's what we're going to do to the workforce, what is going to be left? And that's why I'm on this stage and that's why I'm having this discussion, because I want us as talent development to drive this discussion and not let the discussions drive us. How many of you are working for global organizations where you have outside of the US? Great. So let me give you some categories because many of you may not know these categories, so I will explain them. There is what's called internal, external, and cross-functional roles. There is what is called nearshore and offshore and outsourced roles. Nearshore, for those of you in the US, means we outsource customer service roles to the Caribbean. We outsource our business processes to the Caribbean or to the Philippines or to India. If we're in Australia, we're sending it over to maybe the Philippines or to South Africa. If we're in Europe, we're sending it to India. That is considered offshore. And then there is outsourcing where we take entire internal processes and we send them outside. And then they're cross-functional. So if you decide to go into the exhibit hall and get an automated process and you plug that into your system at work, there might be a vendor that's at the other end of that that is now displaced and no longer has that business from you because you've plugged in the AI. So when we think about AI, we have to think about it in multiple lens— the nearshore, offshore, the external workforce and the cross-functional workforce. Which are the people that we hire to help us. So here's a global impact to the South, meaning everybody that is not a G8 country, everybody that's not the US, Canada, Germany, England, um, all the big ones, France, all the countries, everybody else in the world. So the continent of Africa, the Caribbean, South America, Southeast Asia, and everybody else. 40% of the global employment is exposed to AI disruption, meaning in the US you will make a decision that will completely drastically impact a country, not just an individual. And in India, the major employer in the business process outsourcing world— so here's what we did back in the '80s and '90s. We said, let's send things offshore. We don't need that many call centers. Let's just ship them overseas. So these countries have built their entire economies around offshoring. But the primary people who got those jobs were women because they were the ones that had the college education in countries that didn't have a lot of opportunity. So now you come to AI and you're now saying, oh, wait a minute. Hey, we're gonna implement something and we don't need you anymore. What are they supposed to do? They built their entire economy around what we— the decision we made 30 years ago, and now we're making a different decision. So let me give it to you in numbers. The call centers in the Caribbean and the developing nations, their gross domestic product Their GDP, their ability to be survive— to survive as a country is dependent on what we have already outsourced to them. There are whole companies. I'll give you an example. I had a problem with my Xfinity the other day, and I couldn't get a human on the phone. There was no human. The bot said, you have internet. I said, no, I don't. It said, you have internet. I checked the internet, literally. And I'm screaming at this bot, and it's on the phone, and it says, you have internet, I've checked. Do you have anything else you need? And I said, yes, I need to talk to a human. And it said, no. It literally said, no, you have internet. Is there anything else I can help you with? Because they hadn't trained it for I want to talk to a customer service rep, because they've gotten rid of the customer service reps on the other end. So after 4 times of doing that, it said, There's nothing else I can help you with. Goodbye. Now, the little robot-y thing was actually right. It was me that had the problem. But I actually wanted a human being to tell me that I had a problem. I didn't want the little robot to tell me that I had a problem. I wanted it to say, go plug the router out, wait a few minutes, plug it back in. I wanted that interaction, but they didn't give it to me. So what happened is virtual chatbots have already displaced 25 to 30% of tier 1 customer service roles in India and the Caribbean and the Philippines. And we're only 2 years in to ChatGPT. This is the seriousness of this process. So as I keep going, The economic impact for women is $17.2 trillion globally. If we are displaced, if we lose our jobs, many of us as women are the primary earners or the higher earner in our households taking care of our families. And if we make decisions in talent development that does not look at upskilling and reskilling effectively, then this is the economic impact that can happen for women. And you've already seen the numbers for people of color. You've seen the numbers for our Latino population. I could keep going through every single subgroup and you would see the same numbers. So what is it that you are supposed to be doing? We are bridge makers. We are not order takers. This is a one time that talent development needs to say, I will not take your orders. I need to understand the bridge we're building. We are bridge makers. So companies face a skills gap. We have on one side the skills gap. We have on one side they want to operationalize AI. We have to be the thing in the middle. So right now, this is ATD's Trends Report. We have companies with a skills gap. We have employees looking for work. We have AI competency shortfalls. And then we have organizations planning development. And we are sitting in the middle of it. Right. This is the shock factor and this is the truth. So this is what we're really dealing with. We have the skills gap, which is what every single one of us talks about. Oh my God, we have a skills gap. We need a skills economy. We're going to do skills-based hiring. But what we have is workforce displacement, technological advancement, lack of talent opportunities, and inadequate talent development. And underneath the ground is a volcano. I could have used an iceberg, but it ain't no iceberg. We're not going to run a ship into it. This is not the Titanic, y'all. This is literally a volcano. And somebody in here must be from Hawaii where a volcano might erupt, right? That's what we're talking about. This is what we're talking about. And I'm going to get to solutions, so don't worry. You're walking out of here with some things to go do immediately. So here's a critical question. Who gets reskilled? Who gets left behind? How do you equitably allocate training and development to meet the AI future? These are the questions. This is what we need to be asking. This is it. And it's not gender-based, it's across the board. And I'm going to give you a tool with 40 questions You will be able to download it. You will never have to hear from me again if you don't want to, but I'm gonna give it to you at the end and I'm gonna give you 40 questions that I need you to take into your organizations and start asking people, right? However you feel like finagling that into the conversation. All right, so this is the bigger question. Is AI the next glass ceiling for women? And what do we want next? And we as talent development, not HR— HR gets to do all kinds of things. I was looking on LinkedIn last week and some HR director was trying to have a fight with the planet around why HR needed to lead AI implementation. And I'm like, are you Freaking kidding me right now. No, no. TD needs to lead it. TD needs to be in it. And how do we do that? So here's where I'm going to try to crowdsource. I want you all to participate in the Menti. You're going to have to scan 3 times because we can't bop back and forth with Menti on this stage. So scan the Menti. And the first question I want to know from you, because I want to personalize this session. I have slides, great, but I want to personalize this both here for our audience who's in the room, our audience who's watching through the app, and our audience that is on Zoom on the virtual ATD platform. I want to hear from all of you, what is, what are you thinking about? And so we were testing this earlier. I left this here because this would be a great thing for all of us to think about. One of our tech support folks put in lunch. So we left lunch there. It's a good icebreaker for all of that tough content I laid into before. So tell me, what are you thinking a lot about? I love summer plans. That's a good one. I should be actually thinking about summer plans. My business partner, Inigo, tells me all the time, you need to make time for vacation. So I need to put summer plans on there. But yeah. And these are great things to be thinking about. The AI, the opportunity, women, family, opportunities, leadership, efficiency, careers, opportunity, efficiency, impact, the future, growth, money. Money keeps coming up. Right? I did a program yesterday called Stalled to Stellar, 25 career-defining questions. For TD leaders, career catalyst questions for TD leaders, and that was a part of the process. How do I lead my TD career forward in the age of disruption and everything going on? So thank you for participating in this. We're gonna do one more mentee. Let me fast forward. Keep going in that one if you're still in there. Scan this one and let's do the next one. What would you love to learn more about? How to use AI responsibly. Solutions to keep my role when AI takes over.
Yeah.
Breaking the glass ceiling. Sales mentoring. How to leverage AI, the benefit of humanity. Applications of AI to help me be more efficient at my work. Mindset. Sustainable career paths. How to develop my TD career. Yeah, these are all great things that we want to learn more about. These are all great things. And so when— and I'm asking these questions because I really want you to take these questions back. So when people are having discussions and we don't always address the fear, we want to ask, what would you like to learn more about? Don't assume that we know what they want. I don't ever assume that I know what you all want. I want to be able to answer questions for you. And these are great, and thank you for responding. So the last one, the last mentee we have, we have one more, and then I'm gonna go on to solutions, and I'm gonna take some questions. So let's do this last one, and thank you so much for participating with this. So we were trying to solve Menti earlier, so we left Menti there. It's a joke. So if you see that there, it's a joke. Resistance to AI. Yeah. World peace. Fabulous. Lack of resources. If AI is a right tool for the company, developing the women on my team, onboarding, training for the current skills gap, how to support my kids. Great question. Getting team members to complete assigned training. Yes, because if we build things to develop women and they're not completing it, it doesn't help that it's not being completed. So keep filling this out. I'm gonna post this on the app and I'm gonna post it on LinkedIn as well so everyone can see what we're thinking about from this standpoint. Thank you for participating in the mentee. So I wanna pause for a second and ask, do you have any questions and what surprised you about the data that I shared? Anybody want to answer or just shout out loud?
Yes.
So my question is, so you said that You talked about this at South by Southwest. Yes. Right, well, a lot of Silicon Valley folks show up.
Yes.
Present.
Yes.
So I'm curious, right, the environmental impact is so great.
Yes.
The human impact is so great.
Yes.
And there is this race to keep evolving technology.
Yes.
But were you able to talk to people, or was there discussion around how can we do this in a responsible way with the planet and for our humans?
Yes.
So I'm going to repeat your question. I might not get it completely. The question was, I spoke at South by Southwest on this. There's a lot of people from Silicon Valley that come to South by Southwest. Did anybody really talk about bringing this all together, meaning the people, the planet, and the process? It seems that everybody's racing to implement AI. And build AI, did anyone want to talk about it? And to answer your question, no. I was kind of disappointed. They gave me a huge room, a huge stage. I probably had a room that was fit for maybe 400 people, and maybe 180 showed up. And the people who were engaging with this were not the Americans. It was the Brazilians, the people in South America, the countries that were being impacted. A few people from India and so on that were really coming up to me and saying, oh my God, this is serious. But what I got from the development team, the UI/UX team, because I do speak the language, and just to let you all know, I've been doing diversity, equity, and inclusion for years. I've been a consultant for 25 years, so I'm not new to the game. I have been— my son who is 32 now, started a tech startup when he was 20. And when he started his tech startup, one of the things that happened was, well, the short and the long and short of it, he was at University of Central Florida and he decided to quit and start his tech startup. And so I supported that move. And when he did that, I realized that getting people to demo your software was not easy. GTP. So I joined a demo community for, for software. So I've actually been working in AI for a long time, being a guinea pig, I guess, for startups that were working on the early technology. And then I used Jasper before there was, um, was ChatGPT. So there were other iterations of a ChatGPT before ChatGPT existed. And so I've been in space looking at this. And I'm really— every time the World Economic Forum puts out a report, and I would recommend that all of you do this, the World Economic Forum puts out report on talent and the future of talent about every 8 to 9 months. Most HR and talent development leaders don't read that report. So when I started seeing this on the World Economic Forum, my light bulb went, oh wait, Hey, somebody needs to be talking about this because they're putting it out. They had whole discussions at Davos about this, but nobody came to the table. We are not there as talent, as HR. It's mostly the Silicon Valley folks who are making the decisions about our future, which is why I'm so empowered that ATD not only gave me this discussion but also gave me a stage to have the discussion. And is broadcasting it across the entire ecosystem of ATD. All right, so let's keep going because I really want to talk about solutions. What do we need to do? What do we do as talent development? And this is our solutions time now. For TD, we are here to remove the silos of communication. So your number one role is to make sure there are no silos of communication. Communication. How many of you in the room are at the director or VP level or thereabouts in your organization? Great. Thank you for coming. And so what we need to be doing is making sure that there are no silo communications, that the end users are represented, that the AI designers and developers are represented, that HR and talent has a seat at the table. At the table, that organizational leaders are there as well, and that we are talking about AI governance, not AI gatekeeping, but AI governance. How do we want as an organization to roll this out? What does it really mean for people and impact? And how does that look on the ground? So that's the first thing. We are— the role and the title is AI translators. This is actually a job, believe it or not. It is a talent development role called AI translator. I attended a couple sessions at South by and this was the role. And what they're asking talent development to do is take— be the in-between. This is what our talent has right now. This is what our talent needs. And right here in the middle is what you're you're trying to do in terms of AI and having realistic discussions about where people are. Let me give you the example. When COVID happened, we sent people home who didn't know how to use a computer because it was turned on every morning when they walked into the office, and many of them didn't know how to use Zoom. So the first thing that we have to do if we are AI translators is we have to say, what is the baseline for everybody in our organization. It's not us going out and building more development tools. We need to have leadership discussions, and I'm so glad that the executive level is here, is to say, what is our baseline? We have 400 people who do not know how to use a computer. We have 200 people who don't have internet access at home. We have folks who are only using smart devices. So you have to become this translator voice. So yes, you wanna implement that. Let me show you how this is gonna work and what it looks like in reality. So that's the first role. The second thing that we have to do is define what I call the role of talent development. So ATD asked me to speak at Core 4, which is primarily the newer folks coming into the industry. And I designed this program for the Core Four audience, and I'm bringing it here to you, and I want to explain it to you in a short synopsis. No one really explains to us as TD leaders what our role is. So I came up with sort of a bucket of the role. We are visionary cultivators, meaning we are able to envision potential in other people. We are empowering coaches because all day long we coach people, whether it's leaders, employees, our stakeholders, our external stakeholders. We are constantly coaching people to unlock motivation and foster ownership because they send us the order, but we try to help them own it so they can give us the right direction. So we are empowering coaches. We are collaborative builder because we builders, we can't build anything in talent development without collaboration. So we are the architects of collaboration in the organization. Even when the sales team is not talking to the marketing team, is not talking to the customer service team, or we have institutional silos, we still have to figure out ways to collaborate so we can develop learning. So we are connecting individuals to amplify impact. That is the role that we do. So I've boilerplated this down into 5 things. We are boundary pushers. They give us stuff, it ain't gonna happen. We're pushing against the boundaries that they've given us. Let me give you a boundary. We had an organization say to us, we want to do inclusive leadership training, and our managers only have a 7-minute capacity. So you need to teach them inclusive leadership in 7 minutes, and you need to make it quick, and you need to put 4 slides. And Inigo's shaking his head because this actually happened. And oh, by the way, we only have $2,000 to do this in. And I know 2 weeks later, um, the laws changed. Take all the inclusivity language out of it, remove the word bias call this something else and we're not paying you any more money. We only had the $2,000. So we are miracle workers, should actually be on here, right? But in the middle, we are inclusive innovation catalysts, meaning we ignite inclusion across boundaries. That's what we're doing as talent development. So what we need to do as AI implementation happens, The first thing is we need to build an avatar for the women in the organization. Who are they? Young professionals, people who've just had their families, women who are mid-career, women who are 5 years out the door. We need to build individual avatars for the categories of women we have in our organization and then develop AI leadership learning options within those categories. We cannot forget about our people who are working frontline, meaning our plant operations, our people that are not in our corporate office, maybe our truck drivers. We have to think about everyone. But before we can do all of that, we have to address fear. AI elicits fear even for us. So if you run around in your organization saying, "AI," the person's thinking, All right, they're going to take my job. Do I leave now or do I leave later? Right. We have to create psychological safety, meaning we're not going to do away with humans. We are going to enhance the human experience with the AI. We have to build trust and enable inclusivity, but we have to speak the truth to empower. This cannot be done the way that you want it. Just because the vendor comes with the shiny red ball doesn't mean that we buy the shiny red ball. And as talent development leaders, we need to unpack the red ball. Don't get sucked into the sales message of what's being sold to us and unpack it and be realistic about how it will work inside of our organization and with the people at the level that the people currently exist. We have to build baseline digital literacy. Baseline. When I moved from a PC to a Mac, my son got more phone calls from me about what is this button? I don't know what that button is. Why did this button look like that? But oh, Mom, you really needed to leave the PC world, right? So even I, and I consider myself fairly tech savvy, I am struggling with some things, right? So we need that, and then we need to democratize learning. In addition, we need to recognize these critical levers of talent development: digital, digital tools, AI literacy, leadership opportunities, fair compensation when we add AI to someone's role, diverse representation— who's missing from the table? Digital literacy is not AI literacy. Digital literacy and AI literacy are not the same things, right? Role-specific AI mentorship so that if people are struggling, they have someone who is maybe a little bit more skilled. Reverse mentorship would work amazingly here where we have somebody who's really skilled in AI, put them with somebody who's not skilled in AI, and don't say, oh, you're just too old to be doing this, right? Because we say that, we think it, we may not say it like fully out loud, but we think it, right? Oh, this person didn't even want to use a computer, now I'm going to ask them to do AI too. Okay, great, right? So, um, learning pathways, really be clear about learning pathways and ethical governance. And then we have to ask a couple critical questions. Who in our organization is making the AI decisions? What is the risk of automation for women in our industry? And I didn't say in talent development. I want you all to look at your industry, get really tapped in as talent development into your industry. We come to the big talent development conference, but we need to now silo down down into our industry conferences. If you're in healthcare or education or manufacturing, go to those conferences and see what is being said about AI within your own industry. This is our safe space within talent development, but to get out of our safe space, we've got to go to our uncomfortable place, which is our industry-specific roles. And then how can AI be used to upskill women rather than replacing them? Critical question. So here's— and I'm going to, at the end, I'm going to give you a QR code, and if you send it to me, I'm going to send most of these slides out to you so you will have them, because I think this information is critical and crucial for you to have in your hands. And I will have some links. I'm going to build a page that really has some links to the research that went into this so that folks, when you start telling people, they don't go, "Oh, that didn't happen." Yeah, yeah, you can pull the research and go to page 41 and give it to them so they know that this is real, this is really happening. So here's some go-back-to-the-office strategies. Implement an upskilling program now. Give everyone baseline access. We have a client that actually sent out a memo telling their whole organization to never use ChatGPT. And it's an insurance company. And their CEO sent out the memo and I'm going, are you kidding? All your competitors around you are using AI. You're going to be the only one left behind. So it's not forward thinking. So you have to also know if your organization is forward thinking or not. Assess and track AI skills gap. What do they know? What do they need to know? Where are they in the middle? Ensure women are in AI decision-making roles. Create committees that people can participate on and talk through this. Create mentorship programs for AI leadership. If you find out who's doing the AI, you can have that leadership advocate for policies that protect jobs while integrating AI. And really be solid on our numbers and then review transferable skills. Part of my background is I come out of the workers' compensation industry and we always had to do transferable skills. If somebody had a job, had an injury on the job, we would have to take all the skills they had and figure out how to get them a new job. So, for example, a nurse with a back injury, Maybe I would make her an office nurse versus a bedside nurse. Somebody who's a rad tech, maybe I would make them a salesperson rather than a radiology tech. Right. So it's transferable skills. Redesign your job descriptions to focus on skills rather than just hiring with a narrow technical experience. Ensure hiring and promotion is equitable and train managers to recognize non-traditional career pathways for AI roles. Don't just post, we want an AI role because maybe somebody has a degree, an adjacent degree that could do the job internally and we could actually build more of an internal workforce to champion AI. And the 5 powerful questions. How is AI reshaping the skills needed for our workforce and who's being unintended potentially left behind? What biases might exist in AI hiring and training? Are we evaluating transferable skills? Who in our organization is making the AI decision? And what concrete actions can we take today? When we work with clients, these are the questions that we are asking them, because at the end of the day, while we may not be able to do diversity equity and inclusion, we can still advocate for inclusive voices in the disruption. And so I want you to know that we can still say what needs to be said within the boundaries. So let's wrap up, and then I'm going to open it up for you to ask questions. As I have the Invisible Woman right here, I want you to know that there are hundreds if not thousands of invisible women out there. When I walk into the bathroom here at the conference and I see one of the cleaning people in the bathroom, I always say to them, "Hi, how are you doing? How's your day today? My mother was a cleaner. She did that job so I could do this." And so everyone who we think is invisible, the cleaning person in your company, There is a woman that is invisible, but she has a daughter at home that she's working really hard to make sure that her daughter has a better experience. If we forget about her, then we forget about our impact. No one should be left behind in the AI revolution. Every woman needs to be pulled up, moved up, and enhanced to make sure that she is continuing to contribute, because 90% of your workforce is the breadwinner, the earner. And if we AI them out the workforce, what is going to happen to the next generation? Remember that we are here for the next generation. I speak on stage, and for those of you that have heard me speak on stage, you'll know that the reason I do this now at a higher level is because of my 3-year-old grandson. That's why I do this. That's why I'm not doing the normal. I'm doing the challenging discussion. So this is the, um, the document that I created with the questions that you can go back to your organization and ask. If you scan it, fill out the form, I will send it to you as soon as I get back, and you will have that with the PowerPoint presentations. If you opt out of my mailing, I'm okay with that, but I want to at least get things into your hands to start the AI discussion. Now, any questions from all of you? Questions? What are you thinking about? Tell me.
Yes.
Living in the state of Florida, having conversations around with DeeDee and I, and even talking about how we focus on development programs for women and women of color. So do you have any strategies for how to have those conversations in a space where we can have them without being silenced? Yeah. I know you just briefly touched on it a bit, but any strategy would be so helpful for navigating those kind of conversations and making sure we're still having them.
Yeah. So the question was for all of you so that you hear. Tell me your name. Jamie. Jamie said, how do I navigate having the discussion? I live in Florida. How do I navigate the having the discussion and knowing that if we say DEI, it's a bad word, and how do we continue to advocate for women and how do we do that effectively? So I happen to live in the state of Florida. I live in West Palm Beach. So yes, I'm very familiar. We've been there. So yeah, so it's like I had the instant trigger when you said Florida. I was like, ah, yeah, we're sunshine and a lot of things. Anyway, so here's what we do. We work within the parameters. If you have an employee resource group, plug it in there. Okay, if you have a new, let's say you have an onboarding program. You plug it in there. Hide this, bury it, camouflage it, put it in camo if you have to, but put it into existing programs. If we cannot do carve out, we can do carve in. And let me say that again. If we cannot do carve out, we can do carve in. There's a program that's already been established for career growth. I'm going to go into that program, I'm going to add 5 modules in that program that are designed for women specifically. Nobody can say I'm doing something separate, I'm doing it in. So what I'm recommending that we all do in all the states, and it doesn't matter where we are, we carve in, right? And any programs you've built— so one of the things that I would recommend that you go back to your organizations and do is look at places that you can plug AI in and plug development into your existing content. We are always in a rush to develop new, and we want to have the new shiny bell and roll out the new thing. Everything is iteration. So we are iterating from one thing to the next thing. So we take— rather than building new, we need to just repurpose and empower, right? Repurpose it, add the AI in, add the development in, add in the things that block women right now. So imagine you may have a program on imposter syndrome. Plug AI into that, right? So I'm already talking about imposter syndrome. You don't have to be a woman to have imposter syndrome. Men have it too. Young people have it. People with less experience When you promote a leader from level 1 to level 2, they have imposter syndrome, right? So in that data, in that classroom, plug in, and oh, by the way, we're gonna talk about AI, and we're gonna talk about how to overcome imposter syndrome, and we're gonna focus. If you're a woman, this is what might happen. If you're a man, this is what might happen. And then describe your avatar. If we get good at our avatar, meaning who is in our organization, we can build more effectively the things that we need to design. Our avatar is where we should really start. I hope that helps.
And we have some questions online.
Yes, go ahead.
Awesome. So Gary asks, so how do I even begin to try to survive the tsunami of job loss that is coming up?
So if we start and The tsunami of job loss. 2030 is our number, which is why I think that we need to raise this now. We need to look at our organization and say, do we need to develop people internally or externally? What are the skills that they're gonna need for the future, whether they stay with us or not? We are investing in the digital future as a whole. So if a role has to be eliminated, then we are still making an investment in the digital future, right? So when you get to bringing people to baseline of AI literacy, you actually empower them to take on any role anywhere. If we don't get them to baseline AI literacy, then they can't take on a role anywhere. So it's like a, you know, it's a gift that gives or takes. Takes away. I hope that helps. Yeah, thank you.
And, um, I have two more questions. Sure. Megan asks, how is AI integrating with culture when it comes to service in pink-collar jobs?
Yeah, so that's a great question. Absolutely great question. The culture of the organization is what we are here to maintain. At the end of the day, Women have greater emotional intelligence than men. Nothing negative against the men here in the room. We are tapped in. That's why you do something to us and we start crying, right? We are tapped into our emotions. Men tend to not want to show the emotion and have this machismo, right? Okay, great. That emotional intelligence is also the cultural intelligence in the organization, and it's the human intelligence in the organization. So if we are advocating for women to be there, then we advocate for the cultural intelligence and the cultural dynamics of the organization. So if the organization is currently toxic, we try to work on that before we implement AI. If the organization doesn't value women, we also plug in information on helping them value women so that AI doesn't become a Oh, we're getting rid of all the women because I don't value them anyway. So we have to go back and look at our cultural roots. Who are we as an organization? What is the organization and what is it at its core? And how do we maintain culture and human and have automation at the same time?
Thank you. Yeah. And one final question from Shelley. Sure. Who's asking, how do you recommend framing the conversation with grassroots member in the organization to engage employees in taking advantage of the upskilling opportunities?
Yeah, that's a great question. So one of our clients has a large manufacturing operation, and so what they've done is lunch and learns, meaning they have these lunch and learn events in the break room. They have TV screens up that people are normally not watching, but they use it as an opportunity to show people how to gamify with AI. So we can't just go to the technical part of it. We have to tap into things like if people like sports, are there some sports things that we could plug into? Are there things that maybe you give an assignment for people to use ChatGPT to make a recipe or a vacation plan or something like that? So they're using it at levels that's safe, that's safe to fail but also fun, and they could see the benefit of it and not have the fear driven by it. So we have to think outside the box. And I would say, if you're, if you're thinking it through, we go back to an elementary level and we say, what is it that made our kids' eyes get wide when something happened? You know, you, you taught them how to, you know, tie their shoelaces. Oh my God, they got excited. How do we take that excitement now into our frontline employees, our lower-level employees that may not have any exposure to AI? And how do we create that, maybe that gamification there so that they start using the tool and they're growing from it? And I hope that helps. Yeah. So we are wrapping up completely. Our time is up. I want to— I've given you the Q&A. QR code to scan. Um, if you have the TD magazine with the turtle— I am the turtle— the article at the front of the TD magazine is my article. Um, "Are You Stuck or Feeling Stuck?" is my article. Read it. I have lots of resources there for TD leaders. My book, Leadership Self-Transformation, is in the bookstore, and you can connect with me on LinkedIn. I'm very active. I have a Substack that I, I've called The Undisruptible Woman, and I'm building that out and really talking about the disruption of women in AI. And I publish a LinkedIn newsletter called Possibilities and Purpose, and sometimes 2 to 3 times a week I put out articles on AI. So that's how you get in touch with me. All right, and last but not least, If you enjoyed this session, please fill out the feedback. And I appreciate and honor all of you that stayed till 5 o'clock and came to this session. And I want to empower you to know that we are not at the mercy of AI. We are the shapers of AI. We are shaping the future. We are not at the mercy of the future. So thank you again. Enjoy the rest of the conference.
Woo-hoo! Thank you, Margaret Spence.
And see you next year in LA. Take care.
