Virtual Book Launch with Margaret Spence 8/19

All right. Well, hello everyone, how are you? Oh my God, this is so exciting. I am so happy we're here tonight. Um, I am thrilled that we are here tonight. So hi, Paula. How are you, Melissa? Inigo. Inigo is my co-host. William.

Oh my God!

Thank you, Bill, for coming. Oh my God! It's so amazing to have you here. I'm like honored that you're here. You're an amazing friend. So thank you. And Paula. Melissa, how are you? And for everyone, Paula was my editor. So I'm super psyched that she's here to share in us launching the book tonight. Oh my God, I am so psyched. So the book! The book, at least this is a galley copy of the book. So But it is live on Amazon and ready to go. All right, everyone. Well, thank you. We are live streaming to LinkedIn, YouTube, Facebook, and Substack at the same time. So I think it's all working. I have no clue that it's— if it's all working or not, but I am super psyched about today. And for those of you joining on YouTube, Who are joining on Facebook, joining on Substack, welcome and thank you for being here tonight. So When AI Breaks the Law is a brainchild that started because of the Association for Training and Development. That is the reason why it started. So Inigo, my partner, my office husband, as he calls himself, and I were working on putting in a submission for ATD. And in the process of putting in the submission, I already had the Workday case sitting on my desk. And I decided, let me start unpacking this Workday, Mo Levi Workday case. So, and you can stay on camera if you want to come on camera, please do. If you want to stay off camera, it's fine too. I'm good. I love that you're on camera, so it's all good. All right, so let's talk about the origin of the book. I think that's super important. For those of you who have no clue who I am, my name is Margaret Spence. I am the author of When AI Breaks the Law, AI Governance for Talent Leaders. And the reason why I wrote the book is pretty simple and broader than just writing the book. In 2024, I saw the Mobley v. Workday lawsuit. And when I saw the Mobley v. Workday lawsuit, welcome, welcome, Barbara. Thank you for being here. When I saw the Mobley lawsuit, come across my feed, I thought, oh my God, this is a big deal. This case is a big deal. And I don't know that anybody's talking about it. So what we're talking about is the origin story of the book. What happened? How did I— what made me decide to write this book? How did that happen? So, We were working on a submission for the Association of Training and Development. Inigo and I both speak for the association every year, and every year we are challenged to come up with a title, to come up with a new program that we're going to put forward. And we were going back and forth, and I said to him, I'm going to do some research. I think this is something that is major. They worked a case was the first certified class action involving AI and HR. Like, oh my God. And so, it wasn't enough for me to leave that case behind. So, in researching it, pulling the court documents and so on, I thought this is a risk management issue. And so, for all of you who have no idea who I am, Let me give you a little backstory. Before I came to HR, I was a risk manager. For 20 years, I've run a risk and HR management company. So we do risk management and HR for organizations globally. And so in that process, my risk management brain kicked in. Are employers insured for this kind of risk? How do they insure themselves for this kind of risk? What is the risk to nonprofits, to board of directors, to organizations? What happens if the AI breaks the law? That was my question. What happens if AI breaks the law? That was the whole premise. Oh my God, I'm glad you're here too. Welcome. So the— as we were putting out the session for the Association for Training and Development, I said to Indigo that HR needs a plan to manage AI in HR. And I did not see anyone talking about it. Honestly, no one. No one was talking about Workday. No one was talking about Mr. Mobley. No one was talking about the fact that 1.1 billion applicants had been affected by the Workday software. And again, I'm not blaming Workday, um, I'm just telling you what the court records showed. So out of that came my wanting to get the word out about the exposure to people. So that's how it started. And so we're talking about When AI Breaks the Law, my book. My book that is really a textbook. It feels like a textbook. I know Paula, my editor, was here. And when— I'm sure when she was going through this, she's like, oh my God, like, how many pages is it? It's like 400 and— let me see. It's 461 pages, I think, or 462. The book— Was the origin of the book was what should HR do if AI breaks the law? That was the whole origin of the book. What do we do? How do you rein AI in? And so I went back to my risk management experience and my experience in governance, not AI governance, but governance. Around risk that employers face every day. We think AI is the only risk. No, no, no. We have lots of other risks. We have people falling down. We have things that can happen on your workplace. We have drivers out there on the road. We have all kinds of risks that occur inside of employment. But AI is a unique risk. AI can take a single incident and multiply it 1,000 times, right? It can multiply it 1,000 times. And so when Inigo and I were working on ATD— I come back to that— I wrote up an entire policy and procedure for managing AI in HR. I literally built an operating process, an organizational process, what I call the failure web. How does AI fail inside of organizations? What does that look like? How does organizations put their arms around AI? It's not about prompting. It's not about teaching people how to use the software. AI is the only risk that organizations have that can quadruple, multiply a billion times And nobody catch it until it's too late. There's nothing else. You can have a fire and the place burns down. It's one incident. It burned to the ground. You can have an accident. One incident. Somebody had an accident. With AI, you can have one issue and the issue turns into a billion occurrences overnight. And honestly, HR people are not talking about this. I was on a chat yesterday with a gentleman in Switzerland and he's also doing AI governance in Switzerland. And he says he's beating his head up against the wall literally because HR leaders keep saying the risk in HR is an IT problem. It is not an HR problem. It's an IT problem. The reality is it's not. It is an HR issue. So the Mobley v. Workday case drove the book, right? And I started writing the book in August last year. So August 1st, I quietly started writing the book. And I wanna give you all the whole bit, 'cause maybe many of you are on here thinking, how do you write a book? How do I write a book? Why should I write a book? So let me tell you, August 1st, I started writing the book, and every night I would take my laptop and I would write another chapter, and I was doing chapter drafts. In September, I was a little frustrated with where the book was going, and I said, you know what, the best thing I can do is get the COVID done. So for all of you who want to write a book and you're out there thinking, I want to write a book, I want to write a book, I want to write a book, The only thing that motivates you to write a book is when you have a cover, because now the book is alive and well. So the When AI Breaks the Law was quite an interesting thing. I was on ChatGPT. There's a woman by the name of Sabrina Romanoff. She is an AI genius. She does a lot of AI training, and she had a GPT that, um, that she put out, and the GPT helps you make titles for virtual or viral videos. And so I went into the thing and I said, I want to do a viral video on AI governance. And ChatGPT said, when AI breaks the law, governance in the talent cycle, and when AI breaks the law, let's connect it to something else. And I thought Wait, hold up. That is a title. That is a title. Now the back half of the title wasn't done. All I had was When I Breaks the Law, and I had described the Mobley case, and it sounded like When I Breaks the Law. So that's that's how the title came. I'm being transparent and totally honest, right? So the title came When I Breaks the Law. The rest of the title is all me. So the basis of it. Anyway, so. I started writing every night. By October 15th, I had the COVID done. And so when the COVID was done, the book was alive. It was now officially alive. It was ready to go. Um, I showed it to my husband, um, who is deciding he's staying off camera. He's over there. He's my photographer tonight. So I said to him, I'm gonna write a book. And and I and I eventually said to Inigo, Inigo was the second person I told. Um, I'm gonna write. I'm writing a book. And Inigo was like, "What? You're writing a book?" I said, "Yeah." And I'm like, "Fourteen chapters in." And he's like, "What the hell? Fourteen chapters? What are you writing?" I said, "Well, I came up with this framework called Simply Focus." Now let me give you the Simply Focused story so that sometimes things happen and we don't know why they happen. I purchase domains, I always have, just because I own hundreds of domains, literally hundreds of domains. Um, it seems a little psychologically warped to do that, but literally 10 years ago, I purchased simplyfocus.com. And so when I started putting the, the framework together that's in the book, which is called Simply Focus, I said to myself, wait a minute, I have a domain. That domain would be the perfect thing for this framework. Can't make this stuff up. So I went and I got the SimplyFocus. I went to GoDaddy, I looked it up. I had SimplyFocus. It was spelled with a Y and I wanted an I, so I purchased the SimplyFocus with an I. And so here we are. So that is the origin and backstory about the book. So let me fast forward a little bit, um, a little bit more about the origin of the book, and then I'm going to tell you why I wrote it. Okay. The real reason why I wrote the book. So fast forward, December, I am done writing the book. I call Inigo and I say, Inigo, I'm done writing the book. The book is done. Yay, everything's great. And I sent it to an editor. And the editor, I found someone on Upwork. And 'cause I'm actually describing the publishing process to all of you now, which is quite interesting. So I went to Upwork, I found a person. I have a regular editor, just for all of you to know. This is my 4th book. It's not my first one. I have an editor that did book 2 and book 3 with me. However, she went to work for one of the major publishing houses, and they do not allow her to work freelance. So I didn't have an editor for this book. And when I reached out to her, she said, I can't work with you. Have a good life. It's been great talking to you, Margaret, but I can't do this. So I went to Upwork, I found an editor, I sent the book to the person, they quickly edited it and sent it back to me over Christmas. And I got it back over Christmas and I thought the second week in December, the second week of December, my mind wasn't good with where the book was. And by the middle of December-ish, I went ahead and started rereading it, and I didn't like it. And by the first week in January, I hated the book. I'm gonna be honest with all of you, I hated it. I'm very proud of the work, but I hated the book, right? So I did a complete rewrite. Imagine that. I did a complete rewrite of the book in January. I threw out almost everything I had written before, and I threw out almost everything and started all over again. Yeah, imagine that. And I put— I printed some cards, and I gave a publish date of May 15th. And we went to ATD and I handed the cards out. The book was supposed to come out in May and I was hoping the book would be ready and it wasn't ready. And then Paula and I ran into each other at her mom's house down the street from me. And she said, I can, I'm an editor. And I thought, what?

You're an editor?

When did you become an editor? She said, I've been an editor forever. I ended up with a brand new editor. And The book came to life because I got a brand new editor, and we did a complete rewrite of the book. There are 17 chapters. I'm going to read for all of you the dedication for the book because I think that the dedication for the book. is what drives the book. So now that all of you have heard— hey, Karen, how are you? Good to see you. Um, um, yeah, so here's the— here's the story. Like, I was telling the story of the book and how I wrote the book and how we ended up throwing the book out in January and starting the book all over again. So the book that is here now is not what I had finished in December. So in December, I hated every part of it. It wasn't detailed enough. It didn't give enough information. It didn't say what I needed it to say. And so I wrote the dedication and then rewrote the book. So I want to read the dedication to everyone. The dedication. For every candidate who applied for a job and got no response, to every professional who endured the heartbreak of job loss without explanation, without closure, who was terminated by email, by turning off the computer, by all the evil things we've done to people in HR.

And termination.

To every HR leader who still believes that people matter more than process, that dignity is not optional, that no algorithm can replace the human that is required in human resources, this book is for you. That dedication is what drives this book. This book is about everybody who has been terminated, who has been fired, who has been let go in the god-awful ways that we are letting people go. And I dedicate this book To all of you. Even as a consultant, I had a client who I worked with for 21 years who sent me an email to terminate my contract this year. For 21 years, I have saved them millions of dollars, and they could not pick up the phone and call me and say, we are terminating your contract. They sent me an email. I don't know when we decided that that was a society we want to be a part of. And so that's why this book is important. It is here to say, if we allow AI into the workplace, if we allow it in, then we also have to make sure that we maintain the human dignity around work. And we have to govern AI accordingly. We have to govern AI so that there is human dignity for people. And so that's the basis for this book. And that's the reason why I want to try to get this into every HR leader's hands, because that is what started this. Derek Mobley, for all of you who don't know the Derek Mobley story, he is an African American software engineer who applied for 100 positions and was rejected at 3:00 AM in the morning. I'm a part of a bunch of groups and people are still getting 3:00 AM rejections when they apply for jobs. They're still getting those 3 AM rejections. They're still getting them. And even though this lawsuit has the potential to put Workday out of operation, it is estimated at almost $400 million. Is what it's estimated at that it could possibly cost them. We are still getting and giving and issuing 3 AM and 2 AM rejections of candidates. So we haven't learned, even though this lawsuit is out there. We haven't learned. We're not learning. So that's the reason why I wrote the book. That's the reason why I wanted to celebrate the book, because I have literally written the process to govern AI so that it does not eliminate people. And people who are on board of directors, who are a part of corporate governance, they need to understand that if we suddenly decide that human dignity is not important, that we can say, oh my gosh, we're going to get rid of work and human dignity is not important. Then we miss an opportunity to create opportunity, to create a place for the next generation. I have a 4-year-old grandson. I don't know what work is going to look like for him. The second part of the reason why I wrote this book is because of him. I hope that organizations read the book, that they say to themselves, we cannot do this. We have to do something different. No one is stopping technology. I am a power user of AI, power user of AI. We want technology, great, but we also need human dignity. So that's my reason for writing the book. I'm gonna open up the chat. Anybody wanna— want to ask any questions? Ask any questions whatsoever about how I wrote the book, how I got to write the book, how did I get about writing the book? Any of those questions, any question you want to ask, feel free to Ask the questions about the book and I'll be happy to answer them. Or if you wanna write a book, you want motivation, I'm happy to help you there too. So yeah, and thank you. My cousin Steven is joining from Jamaica. Hello, Steven, how are you?

Hi, Margaret.

Yeah, so any questions on the book? Any questions on the content? Any questions on—

So Margaret, I have a question for you. What was the pivotal moment in December? So you said, I want to rewrite this whole thing because I want to make it— what was the deep, deep reason of redoing the book?

Yeah. That's a great question, Ingo. So, so for those of you who just joined, I told a story that I started the book August 1st. In December, the book was finished. I sent the book to the editor and I hired someone on Upwork. For those of you in the US, it's Upwork. I don't know if Upwork is everywhere, but it's here. And I hired someone on Upwork Gave them the book, they edited the book, and then I got it back. So two things happened: I put the entire book into ChatGPT. Actually, I put it into Gemini, right? And I know everybody says, "Oh my God, AI!" Ah! I literally put the whole book into Gemini, and let me explain why I did that. Let me give you the reason, and this is something that's important for all of you who are thinking about writing a book. I didn't put it into AI for AI to write the book. When you are writing a book, you are almost by yourself.

You're alone.

You do not have a person that you can go to and say, am I writing crap or am I writing something good? You don't have that person. There's no human that you can go, read this and tell me if it's crap. And if you send it to your friends, they're going to read it and say, it sounds great. And so I took the book and put it into Gemini, and I said to Gemini, I want you to be my book reviewer. I want you to act as if I had submitted this book to you to publish it, and I want you to review it for me and give me honest, unfiltered feedback about the book. And there's my grandson. There's Douglas. Douglas has joined us.

Hi, Didi. Hi.

Hi, Douglas. How are you?

Good.

Wonderful. You are too cute. Well, let me finish. Let me not disrupt my. So anyway, I put it into Gemini, and Gemini trashed the book. I'm gonna be honest with all of you. I told you this is this is a book launch, but this is also a place. I like to give information. That's just who I am. I'm an information conduit, right? So it trashed it. It said this was the most horrible book it had ever seen in life. It literally did. It said this thing is not ready for anybody. And it really— I mean, I asked it to be brutal and the AI was brutal. I mean, it was brutal. I, I got— I asked it, I said, review the book as if you're a reviewer. I've sent this book to you and you are reviewing the book as if you're going to accept the proposal from me to publish this book. What would you publish this book? And Gemini said, it's a load of garbage, you need to start over. And it gave me like 50 things that were missing from the book, right? Um, and I'll be honest with you, I had— and this is, this was my own blind spot, and I'm gonna tell you, this is just honesty here, right? Um, I had a framework. I have a full framework in the book. And my lizard brain said, don't put the framework out because someone will steal it. So don't put the framework in the book, just go high level without the framework, right? So I wrote a high-level book without the framework, right? Because I didn't want to put the framework in because I figured, oh, somebody's going to steal that framework, so I'm not going to put it in. And the one consistent thing that Gemini said was You have no framework. There's nothing for anyone to follow. So as much as we hate AI, as I said to you, I'm a power user, right? I like AI. I don't have a problem with it. I just don't want it to be discriminatory, right? And it is, it has loaded with bias. So to answer your question, Indigo, my auditor, my book, My book reviewer said start over, right?

I love the comments of the audience because it says Gemini was rude. I agree, Steven. Now we have a second better question, Margaret. What was your greatest lesson you learned while you were writing the book?

The biggest lesson was deadlines mean nothing. You and I both know I had the book ready to go out in May. I wanted the book to be published in May. I had a cover, as I— for those of you who joined a little bit later, I did the COVID before I even finished the second chapter. One of the things that I say to everyone, if you want to write a book, do the COVID first. The COVID is not written in granite, but spend the money and do a cover, because once you spend the money and do the COVID you gotta write the book, 'cause you're not gonna blow $300 or $400 on a cover and not write the book. At least you wouldn't do that normally, right? So I did the COVID first, which is always the way that I write. When I did my first book, I did— I wrote everything, edited everything, and then spent 5 months trying to get the COVID done. After that, I learned do the COVID first because it's the hardest part of the whole book. It's a cover, right?

Yeah.

So anyway, I— so after I had the COVID done, everything was good. Then I went down the road of writing the book. So the biggest thing I learned is there's no deadline. The second biggest thing I learned is when obstacles come up, don't let that stop you. I had 3 editors before Paula took the book. 3 people.

Now let me ask you a quick— let me interject a question in there. Yeah, this is related to the process. How did you manage perfectionism? Because we all tend to be perfectionists, right? Especially if you're writing a book. So how do you manage not falling into perfectionism?

Great question. So I am not— there's one thing that I learned, and I tell you, I learned this, um, with the first book. The— when I wrote the first book, From Workers' Comp Claimant to Valued Employee, So I actually have it right here. 'Cause I went and dug them all out the other day and took a picture. So this was my first book, From Workers' Comp Claimant to Valued Employee. Injured employees can return to work. And this was a book for HR to implement disability management in the workplace. So this is a space I've always been in. This was my first book. I wrote this book in 2008. So I could not let the contents of this book go. The editor and I fought like a cat and a dog for almost 6 months. Every time he fixed something, I undid it because I felt he was taking away my voice. And we went back and forth and back and forth and back and forth for 6 freaking months on this book.

Wow.

Um, and I find the lady that did the COVID um, she said to me, you're a perfectionist and you gotta let it go, right? And I didn't like being called out that I was a perfectionist.

Mm-hmm.

And she said to me, the book will never come to fruition if you don't stop being a perfectionist. I love that.

So thank you, Barbara, for the question. I have 2 more questions, really great questions. Please keep putting questions in there. This is your time. Uh, what Karen asked, what aspect of writing this book was the biggest challenge? The first question.

Um, I think the biggest challenge was verifying all the sources. That was the biggest challenge, verifying all the sources. I have about 300 sources for the book. I had to verify them, double-check them, verify them again, make sure they weren't wrong, verify them again. I'll give you an interesting story. We were at ATD in May, And there's a gentleman by the name of Jimbo Clark, and he does the box. And we met him in the lobby of the exhibit hall, and Jimbo introduced me to a lady, and she said, I want to have a one-on-one with you. And I said, sure, yay, let's have a one-on-one. So right after I got back from ATD in May, we were in LA, I had a one-on-one with her. And in the conference, in the conversation of the one-on-one, I said to her, you know, I'm writing a new book. And she says, really? And I said, and oh my gosh, I have a whole chapter on change management. And the principle that I love about change management is ADKAR. And ADKAR is my favorite change management principle. And she said, You don't have permission to use that. And I said, what? What? What are you talking about? If you want to use it, you have to style it correctly. I did not know because I've been using Adcarve for many, many, many, many, many years that Adcarve had been sold to Prosci. And Prosci published a new book. I was not using the new version of Adcar. I was using the ancient version that all of us in L&D have been using for 100 years, right? So I had to go into the book, restyle it, put in the quote, and it just so happened that I'm talking to her. So when you think of quoting and using things inside of the book. For example, I have a whole chapter on system thinking because I don't think that HR thinks in systems. So I use Peter Senge's system thinking and I've had to quote it and reference it and document it. So that became the hardest part because the The indexing and the permission structure doesn't get done until the book is done editing. Now you've used this thing on 400 pages and you have to go back and find everywhere that you used it and quote it and put it in the back of the book and so on. That was the hardest part for me.

There's a second question from Karen, really very interesting, which is about the future because this is a book on AI. And AI is changing every 2 weeks. So how will you handle the constantly changing aspect of AI as we know it?

Yeah, it's a great question. Absolutely great question. So the original title of the book was, um, The First Book That Updates Itself. That was my original— the top, the top thing up here said The first book written that will automatically update itself. That was my intention when I when I started writing the book, was that people would buy the book and then as updates came up, things would get put into the book. What I've done instead is I took all of the book and I put it on our learning platform. So it's on the learning platform. I actually use Claude to build out a whole lesson plan for the book. It has worksheets and so on, and it's all done, designed using Claude code and Claude co-work. What we will do is continuously plug in information into the book. Let me give you an example. There's a lawsuit called Eightfold. Eightfolds is the second Mobley lawsuit. Let me tell you about Eightfolds because this is all educational here because we're all going to be subjected to a lot of this. The Mobley v. Workday was— the case was, um, you know, Derek Mobley applied for jobs and he got rejected. The Eightfolds is there's a box of information on every single person who's applying for a job. There's a black box sitting out there, and every time you apply for the job, your information is put into this supercomputer. And every time you apply, every company that you are applying to goes to the supercomputer and pulls out your information. And when they pull out your information, it's held for 303 days like a credit report. So if you got rejected down the street, you're probably going to get rejected down the next street because everybody's going to this one central repository to pull Margaret out of the box and pull her out, shake her around and go, Oh no, she was rejected before and let her go reject her again. That's the second lawsuit that's going on right now as it relates to when AI breaks the law. They are being accused of creating a credit report for people in employment without getting permission to create a credit report for you. So that case came out in February. That case is in here. We stopped the press and added it because I couldn't publish it without adding it. Since the book came out, let me tell you a couple other things that happened. Connecticut passed the first comprehensive AI law. If you're in the US, Connecticut passed the first very comprehensive. It goes into effect in October and parts of it in 2027. Those laws are going to significantly impact HR and talent development. We have to start disclosing where we use AI if the person lives in Connecticut. Colorado has its own law. Texas has TRIGA. Illinois has its own law. New York City has its own law, right? New York State. So everyone— California. Right now, when the state legislatures come back online, there are 11,000 bills in the United States legislative process that could go into law between now and 2027. 11,000 individual legal bills on how we govern AI in HR and talent development. We just can't get this thing right. Europe has the EU AI Act. The part that governs HR is not going to go into effect until December 2027. The part that is currently in effect It's for the tech producers, right? It's for the people who are in tech primarily, except as you all know, Claude decided to put these markers inside of everything that's being produced by Claude now as a marker to say this was produced by AI, even if you don't write that it's been produced by AI. Right? But every single thing we write is being touched by AI, whether you're putting it in there to get it written or you're taking it out. If you use Grammarly to edit a document, it is being touched by AI. So do we have to disclose every single time we, we have a document touching AI? If you can't have this cake and eat it too, You want us to use AI, you want us to put it in place, you want us to implement it, you want— but now you're saying disclose that you've used it and how you use it. I don't think writing with AI should be disclosed. I just think it's— I'm writing, I'm writing an article with AI. Okay, fine. But I do think that if I'm using it to make an employment decision, I need to tell people what I'm doing. If I'm using it for videos, I need to tell people what I'm doing. So we will constantly have to update this book. I can see my writing another edition in January or February, right? And this one in a year being obsolete. And then the framework that is— which is why I built the book around the framework— the framework will continue to stay. As is. The framework won't change at all.

Which answers this— another question that we have from Paula. Thank you, Paula, for the question. Is what is the status of the Mobley lawsuit and how will this decision affect the book, right? So I think it's very linked.

Yeah, so hopefully, Paula, the day the Mobley case comes out, the book will be flying off the shelf and people will be buying the book and they'll go, what the hell? So hopefully that's what will happen, right? Um, as of right now, it does not look like Workday wants to settle this case. There are too many people who have joined the class action. So just to give everyone an update on Derek Mobley v. Workday, so I have my AI Every Friday afternoon, it goes out to 10 to the court website and FindLaw. And when it goes out there, it looks for new things that's happening with the Derek Mobley case. And then I write an article for the update. It is the most read article on my Substack, AI Governance for HR. It is literally the most read article. I get about 11,000 hits a week on this Mobley case. So people are interested in it. Okay. So where the case is right now is it's in this— it's still in discovery, but it's— I think it goes to trial early next year. And I think that's when people are going to wake up and go, wait, this thing's been going on since 2023, '23, '24, '25, '26. Oh yeah, 27. Wait, the trial starts now. Workday— there's some rumblings about Workday being sold. Their stock prices haven't been doing so great. Um, there's some rumblings about that. I don't know anything about that. I don't go into it, but I think once that case gets decided, I think that's going to be the wake-up call. Because right now, and here's the big thing that I think everybody needs to know, Workday is protecting the employers. They have done every maneuver known to man to make sure that they don't have to deliver the list of employers who are using their software. The second they have to deliver the list of employers who are using that software is when every single employer who's using that software gets joined to this class action, and that's when the building has burned to the ground. And that is the risk. And it's not just here. Workday is in Europe, they're in South America, they're in Southeast Asia, they're in Australia. They're being used in parts of the world. It's not just America. But America is the only place with the class action lawsuit. So my hope is the case will go to trial and then the book will fly off the shelf. That's my goal, because people will go, wait, there's only one book written for AI and HR. There isn't another one. There's only one. This is it. There's lots of AI governance books, but there is not one book written about AI in HR. None.

Zero.

This is the first book. Just like this book, my first book that I wrote, From Workers' Comp Claimant to Valued Employee. This was the first book written about workers' compensation and HR. There has never been another book written. It's out of print because I don't have bandwidth to update it. But there hasn't been another one that connects the two. Yeah. So any more questions? More questions?

Margaret, there was another— I read probably a couple of weeks ago, there was a couple of cases in China already who sued their company because they were forced to train um, AI for their role, and then they were offered, you know, a demotion or you're out. And there's a couple of cases also. So China is also going ahead with lawsuits, right, in terms of employees. How do you see that?

Yeah, globally, um, the, the— China has put a law in place that says You can't use AI to eliminate jobs. Kind of, I'm paraphrasing it, but that's that's their thing, right? Today I was looking at a gentleman that did a video about an AI that is being used with cameras inside of a department store. And the cameras are overhead and the AI is monitoring facial recognition for the employee, the number of times the employee smiles or doesn't smile when they're walking around in the store, the number of interactions they have with people and whether they're having those interactions in a harsh way or a great way or a sad way. And Apparently they did this to an employee whose mother was in ICU. So imagine this, this is, this one is going to be the next lawsuit, right? It's coming. The, the, the leader wrote her up because the AI rated her a 3 for 4 days in a row even though her mother was in ICU, and they use facial recognition To rate her, and she had been a five. So it's a scale of one to five, and it's based on facial recognition. And they said for four days she didn't smile at all. And then she wrote a note to her manager to say, I guess she put it out on social media. She wrote a note to her manager to say, "You know that my mother is in ICU, and she's been in ICU in the hospital for the last." X number of weeks. Why would you rate me this way? And the manager apparently said, "I can't override it. It's the cameras above you." So just smile, even though you don't want to smile. Just smile. Right now, we were at South by Southwest last year. Inigo and I, we spoke at South by Southwest last year. And there was a gentleman there who was developing a software, and apparently he got funding to use facial recognition to decide if an employee was a flight risk, if they wanted to leave the company. And he was presenting this as a piece of AI software that he was building. To use facial recognition, and then he was going to use voice to determine if the employee was a suitable employee or not. And they were going to use facial recognition and voice. So I asked him, um, what happens if the person's neurodiverse? What happens if the person has a speech impairment? What happens if the person had a stroke? What happens if the person has some kind of facial disfiguration? How is your AI going to determine that I'm a flight risk from an employment software that you have gotten funding for? Somebody in this funding triangle decided to give you money to develop something that is useless. And you will go out now and try to sell this to some employer and some twisted employer will buy this Nonsense from you, without thinking that there are known disabilities, known issues that a person can have with their face and their voice that prevents them from speaking fully. And somebody was going to fund him to develop this software. He presented it. What problem do we have that he's trying to solve? And so those are the things that we as HR and talent leaders need to start asking. When people come to the table with AI-type software, what problem are they trying to solve for us?

Margaret, we have a question of— a practical question about purchasing the book. Is there a better way to purchase the book than on Amazon?

Um, I will— the person who asked can send me an email. I'll send you my Ingram link, which is not Amazon, and you can purchase it directly from Ingram, which is my publisher.

So Margaret, it was Bill Whitehead. I, uh, asked because I'm looking at the book, but before I buy it on Amazon, I want to know if I can buy it directly from either your website or some other place, um, and be able to get it. And the answer to the question that you just asked— and I'm, I'm sorry, I'm off camera right now.

Okay.

Um, here, I'll, I'll turn my camera on. So the answer to the question that you just asked, and I love, you know, what you're saying, is, um, because there is a segment of the leadership in corporations that want to control every aspect of what their employees are doing because they believe that they're taking advantage and not that they are valuable assets. And that's the reason why they want to monitor and control and watch everything that is going on.

Yes.

And I love the fact that you've written this book. You know what a big supporter I am of you. So, but, you know, uh, you know, I love it and I'm sure I'm sharing it with folks that I know and particularly multiple people in the HR business space. So congratulations again on your launch.

Yeah, thank you, Bill. Thank you, Bill. So I have to tell everyone, ooh, Bill Whitehead is. If I did not—

oh no, no, no, you don't need to tell them.

No, I'm gonna give them the little tiny story, little tiny story. So Bill is, um, Bill mentors me on business. That's what Bill's role is. And we met during the pandemic, and Bill asked me, and I have to say this, the most significant question I've ever been asked in my life. Which is what was my exit strategy from the business? And I've never forgotten that. And he has been an amazing supporter. We may not talk for months and months, but Bill is always there in the back of my mind. And everything I do in my business is because of what Bill— today is because of what Bill said to me. In 2021, literally.

What is grateful for you, Margaret?

And that just shaped everything I do. And and I tell you, sometimes we we don't think about things. He put a check. I was on a webinar, and he put a little message in the chat and said, "I want to talk to you because there's something you haven't thought about." And I said, "Sure, let's talk." See, typically people would be like, "Oh my God!" No, I sent him my email and my phone number, and we ended up talking like 2 days later, and it was the most impactful conversation I've ever had from the day I opened my doors.

Aww.

So I appreciate you, Bill.

So everybody's wondering, what did I pay you in order to do that?

And I'm the one supposed to be paying him. No, I— you know what, he didn't. I, I Bill has been generous with his time always and been a huge supporter of me and giving me direction when as a woman, and I say this to all of you because most of you are women and Inigo is also running his business, we often don't think because we're working in the business what we have to do with the business. grace of Bill. So I always appreciate it.

So I will send you an email. And yes, you know, I can't wait to get my copy, and you better sign it personally.

I will, I will get you a copy, Bill. Absolutely, you will get a copy. So I don't want you going out and buying anything. I'm gonna send you a copy.

Oh no, no, no, I'm gonna buy a copy because it validates the fact that it has value. So But I do want you to sign the copy that I buy, so I will let you know. Okay.

All right. All right. Sounds like a plan. Sounds like—

And I hate to do this, but I've got to go and I've got another meeting that I've got to go to. But I am so thrilled for you and I am thrilled not only for this book, but for the success that you're having with the things that you're doing and the impact that you're making in business.

Yeah, thank you. Thank you so much.

You bet.

Always appreciate you. Thank you.

You bet.

Yeah.

Cheers.

Cheers.

Yeah, we have to appreciate the, the power of mentors and the power of people that life puts in our, in our way. So we have a great comment from Samantha. Margaret, we can't live in a Disney fantasy world all the time. There's no way to control people during work hours. What is your suggestion for ensuring people have a better experience at work using AI to their advantage instead of worrying about it?

Yeah, so, um, I was recording videos, um, earlier today, and one of the words that, um, came to me, and it's actually in the book, um, Was the fact that we have to create space for people to learn, and we also have to create space for people to challenge AI. Right? It's twofold, and it's not just about making rules. And this is what I want us to understand about the book When AI Breaks the Law. This book is not about writing a policy for no use of AI. There is nothing in here that talks about that. It's not a policy use. Here's the scenario that I want every one of you to understand. Last week, OpenAI had a test AI in a box It was in a box and it was, um, being tested. It made a decision on its own to escape the box, make a left, make a right, make a left, make a right, jump out, get onto the internet, go down the street, jump into a company's software front door, right? And it went in there and hacked this company, and it hacked the company and tried to shut them down. The company couldn't turn it off. They had to go to China and get a Chinese AI and use a Chinese LLM to stop OpenAI. Now imagine that you have created a You've created an agent, which is what we are doing now, right? It's no longer just chat. We're going to create an agent. All right. And the agent is out there doing things. You've given it autonomy to go out and do a bunch of things. The agent is running rampant inside of your organization, and you have no idea that the agent is there or what the agent is doing. All right, great.

How does you—

how or when did you teach your employee to spot what is going wrong with the software? When did we teach them that the output, the information they're getting from the LLM is wrong? See, we don't do that. What we do is we write, don't put this into the AI. Into the AI. Governing AI is not about what you put into the AI. It's what comes out of the AI. Let me give you another example. You're using the AI to determine succession planning, right? And you're doing succession planning with the AI. Okay, great. And it's going to go out and it's going to pick out 10 or 20 people that it feels you can promote them, but it's picking out a particular set of people. All right, you have no idea how the AI was trained to select the people that it's picking. You're using it to tell you who your high performers are. You're using it to tell you who your flight risk is. You're using it to tell you all of these things. But what we haven't done is trained anybody on the output. Governance is the output. Governance is the guardrails of the output, right? It's not the input. And so when we focus only on writing the policies to stop people from using the AI, Then what ends up happening is they actually don't learn when the AI has gone wrong. They have no idea that something has gone wrong with the AI. I'll tell you, I facilitate the AI instructional design for ATD. And I will— people will come to the class. In fact, I'm teaching it next week, I think. And people will come to the class and they'll ask for prompting help, and we'll give them lots of prompting help. Great. Then after we give them the prompting help, I say, are you going to go back to your office and teach everybody how to prompt properly and how to look at the output properly so that they know that what they've given the AI and the AI has given back to them is correct? And they all look at me like a deer in the headlights. Why would I want to do that? Because you came and learned the right way. So the critical part of this is making sure that we don't just write policies, that we teach people about governance. And let me, let me find it so I can, I can, um, I can tell you. In the book, I write out what I call a maturity model, right? And inside of the maturity model, we— there are people that are at different levels of the maturity model. And one of the critical things that we have to do is make sure that when we build the governance architecture, That we know where people are, that we give them the ability to escalate problems that they see. Do you think that nobody saw that Workday was eliminating people over 40? Everybody saw it. Everyone saw that people were being eliminated who were over age 40, right? But no one stopped And said, "Wait, hold up. There's a problem." Right? So I think what I inside of the book, I invented a new role for HR. Right? I literally went all the way there. Like we need to become something, right? And we're not where we are, where we're supposed to be, right? So. The role is called the Chief People Intelligence Officer, right? And let me give you what the CPIO is. I've written a role and job description and what it is. And this is who we have to evolve to become as HR people, as talent Talent development. I would even argue that we could do talent development information officer. We could do a TDIO, right? Or as well as a CPIO, right? The CPIO is an architect of ethical people systems. And this answers the question, Samantha. I think it— this will probably sum it up. The CPIO is the architect of ethical people systems. Equal parts strategist, system thinker, risk mitigator, data translator, and equity guardian. We don't use technology. We're not users of the technology. We govern it. We lead at the intersection of workforce planning, algorithmic accountability, and human-centered design. So what we are doing now and who we have to become is this different role. This is where HR and talent development needs to go. We have to have the people system and the intelligence system combined in our roles now. We have to become translators. In 2025, I spoke at ATD and I was on the main stage and I said, there's a new role. The role is talent development translator, which means that we take what people are doing in the organization as in terms of their role, their job. We figure out how the AI would integrate with that, and then we figure out what it looks like on the other side. And so it's a threefold job, but when it comes to HR. We are supposed to go to this system thinking, understanding how small decisions in AI ripple across our complex ecosystem. If the AI makes a mistake about all your 40-year-olds, or it doesn't give you applicants who are 22-year-old, Right? It's giving you people who are 30 only, right? What's the ripple consequence? Then we have to take people to AI literacy. It's part of the role now. We have to make sure that people are AI literate. AI literacy is not using the AI. It's understanding all the various parts of it, knowing what the AI does, what it doesn't do, and what it should never do. Without human intervention. That's the definition of AI literacy. What the definition we have now about AI literacy is, let's help them use the AI, help them prompt it, make work better. No, AI literacy is knowing what the AI is doing, what it's doing, when it's doing it, and what data it's using to make those And then risk and ethics, building frameworks that go beyond legal compliance to include dignity, fairness, and transparency. And then courageous leadership, which is challenging the automation when it conflicts with people-centered decisions. It's not about us becoming data scientists, right, or coders. We are becoming ethical translators between the people and And the machine. And in between there is where talent development, human resources, employee relations, all the roles that involve people sit in that middle between ethical translation between the people and the machine. And if we don't get that right, then the next generation is not going to have jobs because the people who are designing this are designing this to eliminate us. I don't know what they plan to do with us once they eliminate us. I don't know what the plan is, right? Because they can't shoot us all to Mars. So I'm not sure what the plan is. But at the end of the day, we have to analyze and predict and govern AI. And those are the critical pieces.

Yeah.

Robin, how are you? Good to see you.

Margaret, any other skills? You said analyze, predict, govern. What else? What new skills do we have to develop as a talent development, as an HR professional? To govern, to really Yeah.

So we have to learn risk. What is the worst thing that can happen in our organization with AI? What's the best thing that can happen and what's the worst thing? Because it's not always bad. I don't want people to think that it's all bad. It's not all bad. What's the best thing that can happen? What's the worst thing that can happen? The best things are people become fluent in AI. They're able to have autonomy. They're able to build things. I could tell you in our talent development group, I get in there and I've built something with Claude, and I drop it in there and say, "Look at what I built," right? And I'm so excited about having built that, right? It's the same thing with the AI process. I'll give you a funny joke. I built an HR software. One weekend, I started on Friday afternoon. I took all day Saturday and all day Sunday, and Monday morning I had a running operational AI software. I mean literally running. I had logins, manager logins. All this stuff was there. I was solving a problem, right? I literally had a problem that I was solving, and in solving that problem, I built a software. And I built it in Lovable, and I was able to code it all weekend and get it operational, up and running, and had people demoing it Monday morning because I had a problem. I had an HR problem that I needed to fix, and there wasn't an HR software for a tiny, minuscule little company with 6 employees. Every one of the software companies wanted 20 or 30 or 40 employees, and so I built this thing, gave it to a client, and now it's up and running and working. I would love to sell that to a million people, but I don't have time to do that yet, right? So you want employees to get excited about that, to take their job roles and use the AI to build a solution. And the solution is working and it can work for everybody in the company. That's utopia, right? What is not utopia, and that's where we as Practitioners have to learn to use the AI at a higher level. I haven't taken an AI course. I've been going to YouTube University, and Inigo will tell you. I'll call him, and I'm like, "Wait, hold on! I got something. Let me let me give you all another thing, right?" And Karen and our group and Inigo and a bunch of us will know. Every year when it's time for conference submissions. Right? I get— my phone burns. Inigo will tell you, I have at least 50 phone calls, and he will say, why are you doing that? Every year you do the same thing. What is wrong with you? Right? This one's calling you. I get people calling me going, how did you get on the ATD stage? What did you do? How did you get there? These are attendees that are attending the conference who've taken my name. And they decided they want to speak at ATD, right? And then they start sending me emails and I will get on the phone with them and generously help them submit. Inigo will tell you, last year I did 22 people that I helped last year submit. 4 of them got in. So I sat here, Inigo said to me, I want you to, Get on a call with me for hour or two, right? And help me with my submission. This is what and this is every year we've been doing this for I don't know four or five years now, right? And he says to me, "I want you to get on phone for like two three hours with me and help me with my submission." And I'm also doing a submission for John Brown down the street. Really? Okay. And we will get on the phone and we will spend days going back and forth, back and forth with this.

So let me stop you right there. And she would become the Claude that told her that her book was crap. Okay, continue, right? Sorry.

Yeah, so, um, some— somebody's got— yeah, so we, so we, um, we would go back and forth and I'd say to him, that's a crap title. How dare you write that title? That is a horrible title. That you're up in your head, you're thinking about that. Why are you doing that? And we will have yelling matches back and forth, and he will be over me completely, hang up and like, I gotta get rid of her, I'm gonna go to the gym and run it, run on the treadmill, right? Literally every year we do this. So this year I sat down and I researched 1,000 conferences. Literally, he sent me, he sent me a, he put a calendar I knew what was coming. He put a calendar invite on my calendar to come and talk to me about his title for ATD, and I knew what was coming. And I sat here and I built a speaker proposal app inside of, um, inside of, of, uh, Karen's going thumbs up. I built a speaker proposal app a customer, and she's blowing me kisses inside of ChatGPT to help people submit their proposal. And I, and I said to my son, I'm gonna, um, sell this thing for $20. And he's like, $20? That seems like you should charge $100. I said, no, it's not a $100 thing, it's a $20 thing, right? It's just to help speakers do submissions better, right? So I built a whole landing page. I need to record a video and, and start selling that product. But this is what we want our people to be doing. This is how we innovate with AI. None of us should be users of AI. We should be innovating with AI. And so where we have to go as HR leaders is to become innovators. We should be building things with AI every single day and getting our employees and challenging them to build things to make their work easier. Right? We should be doing that. I'll give you an example. So, Nalva is on the on the program here. Nalva is joining us from Brazil, right? And I'm heading to Brazil in September to do some workshops in Brazil. And we Nalva did a program two two weekends two Wednesdays ago. I spoke at the program for her, and I built within an hour a complete piece, a small piece of software that I built with Claude in a couple of hours to get the the people who were using who came to watch the video. We converted what would have been a worksheet into a working document that they could then. Print. And I gave Claude just the video transcript and said, I want to create a worksheet for them to work on. And it built it for me. I put it into the LMS and I had a working— and here's the kicker. I had Claude translate it from English to Portuguese and it created a workboard that the student could switch between English or Portuguese and fill out the worksheet and print it at the end. And they got a printed worksheet that was helping them to identify where their blockage, what was blocking them from moving forward as women. And it was like a journal entry that they had to do. And they worked through this journal entry and then printed it and had it. And we had, 11 students, 12 students out of our 50 fill that out, come to the website and fill it out and print it. That's what we need to be doing with AI. What can we do that's gonna make things better? And we have to make sure that when our IT department puts guardrails on employees, that the guardrail doesn't prevent them from being innovative. That when you say to them, don't do this, don't do this, don't do this, when you say that to them, that they are— we're not stopping them from being innovative. We have to still allow people to be— to innovate with AI. And it's not about giving them the long list of things that they cannot do. Yes, the long list of things are necessary, but it is not what we should be doing.

So basically, it's a dance between having some guardrails and also continue being innovative, right?

Yes, it's a dance between both of those. And it's also about figuring out where your employees are in terms of governance. So let me, let me show you. I did a— you can't see it really well here, but All of us in HR are familiar with the 9-box, right? We have the 9-box where we do 9-box reviews. I built a similar concept off of the 9-box theory that helps us understand where our people are. So, there are 9 spots that people can be in your organization. They can be a risky innovator where they just want to take risk with AI. And we need to rein some of those people, risky, risky people in. We have to figure out who they are. We can't write the policy and say, oh, everybody's a risk innovator. No, we have people who are risk innovators, but we have people who want policy, who want stewardship, right? We have people who are compliance-driven, who want compliance. We have people who are averse to AI. I'm scared to death of it. I don't want to touch it. Right? And then we have people who want to do governance, who want to put guardrails in. And then we have people in the middle who are unstructured explorers. Literally, that is a category, right? An unstructured explorer. You want to make sure that your unstructured explorers have some little guardrails. Oh, they want to put the whole company's information into AI? Right? No, that's not what we're doing. Okay? Those— but we have to identify where people are before we write all these rules. And the people who are leaning towards governance are the ones that we help rein in the ones who want to put everything into AI. But here's what I know. Even if you write a policy, there's a manager who's going to have his cell phone. Who's gonna punch in? I don't like Sally, and I want to write her up, and give me the text to write her up. And what is happening right now? Employment lawyers will tell you what is happening right now is when employment litigation happens, which is where my lens comes from. I, in my career, handled about four hundred and ninety-five million dollars in. Workplace litigation, meaning I settled or cut checks to people for $495 million, right? When I started my career, I handled workplace injuries. A person would fall down, then the manager would fire them, and then we would have an age discrimination, a race discrimination, a this discrimination from the one case. So I could see the big picture, right? So what I'm saying is that if we don't rein people in, and especially our managers, I think our biggest culprit for AI is your leaders, your executives, your executive leadership team, because they're the ones who are going to pull their phone out and do something on their phone because they want to hide what they're doing from everybody else. Your employees might plug things into the AI or they might be scared to death because you gave them a use policy and they won't put it in because they want their job. But your managers are risk takers because they figure I bring the bacon in, nobody's going to fire me. But when there's litigation, what they're asking for now is the manager's cell phone and their use of ChatGPT and everything else, because there is a case in New York where that case came out and it said if you use AI as your lawyer, quasi-lawyer, help me write this person up, and you do that and then you write them up, they're going to ask, did the manager use AI at any point to, to determine the write-up? And if they did Please preserve what they put into their phone, right? So our biggest issue is not the employees. Honestly, it's our managers. The employees kind of know. I don't think I want to put that in there. The managers? No, not so much. They're doing the risk of the absolute. Risk untethered exploration with their personal cell phone and AI. And we're often afraid to tell them that they're being risky.

Yeah.

Any other questions about the book? And I thank all of you for hanging out with me. Oh my God, this is so amazing. So somebody got me a bottle of vino. My husband did. He bought me a bottle of passion fruit tropical Moscato. So I'm gonna pour me a glass of this Moscato that he got me. Um, so We will toast. I know everybody doesn't have a glass, but whatever you got, we'll toast to it. Um, water bottles included. Karen has her bottle. Karen is running to get her bottle.

Oh my God, I should get my wine. Hold on, let me go and get and grab a glass of wine. Give me one.

All right, we're gonna go get a glass of wine, and it goes off to get a glass of wine. Oh my gosh. But I want to thank all of you for supporting me, for being here for me, and for getting the word out about the book. Please share it. I want to thank you all. Karen, oh my gosh. Yeah, and who else did I miss in the chat? Kay, oh my God, Kay is here. Miss K, how are you? Um, Melissa, my BFF, um, and K, my BFF. Robin. So Robin, I have to tell you this. I was recording videos today, Robin, and your name is in the video, right? I recorded this whole video and the whole thing was on microlearning. And I said, you're gonna come into the platform and you're gonna do microlearning. And my good friend Robin D. Felice Microlearning is micro bits of information that you just give everybody and they get it immediately. So you're in my video. So thank you, Robin and Karen and Yvette. Thank you, thank you. And Wendy and Jalicia. Oh my gosh, Jalicia. Oh my gosh! Julissa is dialing in from Jamaica too. Hi, hi, hi! Hello, how are you? I'm doing well.

How are you?

I'm good, good. Oh my gosh! Husband showed up with his wife.

Oh my God!

As he's he's running off. Andrea, thank you. Giovanna, Heather. Oh my God, Heather! Heather, how are you, Heather? Yeah, yeah. Oh my gosh, good to see you, Heather. Yvette, yeah. Patricia, thank you, thank you for all of you being here. So I want to— before we close out, we were gonna go a little bit longer, but that's fine. I think I wanna read the end of the book for all of you. And I think that is really where I feel that we— We need to think through where we end up. And so I want to read the end of the book to you. And at the end of the book, I wrote a manifesto. It's called The Future of AI Governance for HR: The Futurist Manifesto. The age of AI governance as optional compliance has ended. I stand at the threshold of 2026, and I see an age of consequences. We're entering a reality where regulatory authority finally meets enforcement power. Many of you may not know that Brazil was the first country to enact AI laws. The EU AI Act came out of Brazil. Brazil wrote the first laws. European Union took it and expanded it. Where technology vendors— it is where technology vendors face liability alongside the organizations that deploy them, where every decision we make about how we implement artificial intelligence echoes across the lives of entire categories of workers. This is not a tech problem. This is a human problem with technology that dimensions. The next 5 years will determine whether AI becomes an instrument of workforce displacement and inequity, or a catalyst for reimagining work and dignity. That outcome is not predetermined. It depends on the choices we make today. We can decide how AI looks, For all of us. And let us name the hard truths that are often unspoken. Automation of repetitive cognitive tasks, the very tasks McKinsey predicts will be 70% automated by 2030, disproportionately affect roles traditionally held by women. And I really want us to hear this. 70% of the roles occupied by women have the capability of being automated. That includes us in HR, which is why I feel strongly about the work that I've done to write this book. The primary people who are going to be at the end of this AI, um, quadrant is going to be Black women. We are currently experiencing the brunt of this today. I was on Instagram a couple days ago, and there's a gentleman in Jamaica, my home country, who put up a thing about the fact that Jamaica has lost 20,000 customer BPO jobs inside of Jamaica. 20,000 jobs have been gone. In Jamaica because of BPOs. So BPOs are customer service call centers, which is the large— one of the largest employers outside of tourism in Jamaica. And some consultant in Jamaica said that is not because of AI. That is the biggest lie known to man. And so I said to him, in 2024, I did a speech saying that the BPO sector was going to be disrupted by at least 60% because the more that we can automate call answering, the more it is going to affect the fact that we don't need call centers. So the consultant is now saying that's not the— AI is not the issue. The call centers will continue to hire people. That's not true. AI is targeted. So what I wrote in the book is administrative support, frontline customer service, and middle management are being aggressively targeted by agentic systems. If we are not intentional, the efficiency of AI will become the tool for the quiet erosion of female leadership pipelines and women of color. As HR leaders, our governance must be an inclusion strategy. We must ask, are we automating roles or are we automating out the women who hold them? When we automate roles that women occupy, we affect entire ecosystems. The Global South will bleed from the decisions that the Global North makes.

Okay.

The collapse of the career on-ramp. I'm deeply concerned for the young talent. Between 2026 and 2030, we will see a junior crisis. Entry-level positions have historically been on-ramp for early career workers. These are the roles where automation most aggressively operates today. When we automate the junior roles, We compress the career ladder permanently, precisely at the moment when workers need to see where they're going. A 25-year-old facing a market where entry points have collapsed face not just temporary disruption, but a fundamental reordering of the career path. We must ask ourselves: If we remove the bottom rung of the ladder, how do we grow the leaders of tomorrow? 2040. The shift to agentic everything. We're moving beyond algorithms that recommend. We're entering an era of agents that act. Agentic AI doesn't wait for prompts. It plans, it executes, it hires. And if we do not govern these digital co-workers, we lose the thread of human culture. Transparency is no longer a It is a foundational requirement of trust. An AI system that affects a human being must be explicit to that human. The black box is no longer a luxury that we can have. So in this moment, it is imperative that HR leaders step up. We cannot just implement AI. There are 4 critical points we have to say to ourselves. What will we not automate? What decisions in our organization should never be fully automated? Have you articulated the list to yourself, your board, your department? The junior ladder— if 80% of the entry-level roles are automated by 2027, which is a prediction, what is your new The skills mortgage. If skills now expire every 2 years, and this is for talent development, are you funding reskilling as a core infrastructure cost or as a discretionary perk? Are we still treating learning as a perk? The transparency gate. Can you explain how you're measuring the impact of your A rejection decision made by your AI to a candidate's face, or are you hiding behind the technical complexity? And the moral balance sheet: is your AI strategy creating more value for the shareholder than it's taking away from the dignity of the workforce? So I am not sparing anybody in this. The age of consequences has begun, and the choice We are not at the mercy of AI. The AI is a tool that enhances what we do, but it cannot be a driver of us being eliminated. And so what I would say to all of you is you have to learn AI. You cannot learn it by just putting stuff in the chat box. You've got to get in there and dive in and see what can I do with AI in my workplace and outside of my workplace. What can I do with AI that's going to enhance my work and make it better? What can I do with AI that's going to make my entire process better? I'll give you a semi-shameless plug. My good friend and my one of my longest friends, Kay Richardson, is on here, and Kay was an educator. She worked for one of the universities here in Florida, and she left the university, I think, 2 years ago to start her own tech startup as a Black woman. And she's running Next of Kin Plan, which is a plan where you help your family make a next of kin decision. But she came out of education and went into tech. That is what we have to do as HR leaders. We can't sit and say our job description requires us to just sit in one place. Our job description has to become very fluid now. And in that fluidity, we have to figure out how do we use AI to become more resilient for the future of work? Because it will not look the same way 5 years from now. So everybody got their drink? Drinks all in hand? My husband ran off again. He came in with a drink and then he ran off. Like, okay, sir. So I toast all of you, um, who have supported me, who have been my friends, who have been impactful in my life. Many of you are mentioned in the acknowledgement of the book, and I want to thank you for supporting me. And so if you all want to come on camera, I think we lost Margaret for a second.

She'll be back.

Hang in there.

She'll be able to reconnect. She's back. Uh, unmute, unmute, unmute, unmute, Margaret. There you go.

Okay, all right, I'm back. Yay, that was a little dicey. Um, all right, well, toast! Thank you all for coming tonight. Thank you for supporting me, and thank you. All right, Inigo, you got the picture. You gotta do a screenshot, Inigo. Who's coming on camera?

Nick. Hold on, hold on. I can multitask. Okay. All right. One, two, three.

Oh, Nick. Nick has Nick has left here. Nick is still in the office. Um, Nick is still in the office. Thank you, Dwayne, with the Pepsi.

Um, I'll take more. Come on, everybody. Anybody else? Let me see if I can do it, if I can hold it. There we go. All right, cheers for your impact, for creating impact, and for always supporting everyone.

Thank you, thank you. Anybody who has some final words? Anybody want to ask any questions? Come off mute. This is your chance. We love you, Margaret. This is amazing. Thank you, Melissa. Oh my God, Melissa, my BFF. I'm telling you, my hangout partner. Yeah. So there's a couple of things. If you purchase the book, you get the online access to the online course, which will go online on Friday. And then I have a collab where you can join the collab. It's $49 per month, and you can work directly with me on building your governance, or you can join one of our sprints, which is $399 per, and it's a 5-day sprint to build governance. So we have a couple different ways to build governance, or the book is very self-contained. You can easily take the book and build out your entire governance program from within the book. So yeah. Well, I thank all of you. Oh my gosh, I'm so excited. This is like— I have to— so, so So where is it? Hold on, hold on one quick second. So this is okay. Here we go. So my. In the black blue sea. Shake a Maggie to the vibe, charms in your life. Wherever you go, please remember, eat your grain, be good, be careful, be joyful. Yes, we have come a long way.

Shake it.

Yay! So that's our music rendition for the end of the book launch party. So any of you want to write a book, let me know. I'm happy to be a good guide for you. Yeah, well, thank you all so much for being here, for staying. Inigo, thank you for being my co-host. You are amazing. And for all of you that stayed the whole time, I cannot— tears almost. I'm grateful and happy, and I can't wait to see where this book goes. And I'm happy to have all of you in my ear. Thank you. Inner circle. So thank you. Yeah. All right, well, good night everybody. See you soon. And for those of you who live close by, I'll see you soon. Thank you. Take care.

Good night.

Bye-bye. Bye-bye. Thank you. Thank you, Nova. I can't wait to see you in a couple weeks. Robin! Hi, I had to get parked. I couldn't, I couldn't talk because I was driving. That's all good. It's all good. It's all good.

Yeah.

Oh my gosh, thank you so much because I know you're driving. Yeah, I stopped, I stopped to get gas and I was like, yeah, I can finally say hello.

You've made—

this has been enjoyable. Thank you. Yeah, thank you. And Giovanna, thank you for staying the whole time. Oh my God, it's so good to see you. Bye bye. Yeah. Oh my gosh, Robin, I so love you. How far you got to drive? I'm staying with Alana tonight, so I have about an hour more. Okay. Yeah. Yeah. So it's.