4 AI Mistakes that Will Hurt Your Career

[music] Welcome to the Mental Offload Podcast, where we talk about women balancing work and life. It's the podcast that combines leadership, feminism and coaching tools, so you can tackle it all with more confidence and less stress. Here's your host, Ivy League MBA, Certified Feminist Coach, and Corporate Warrior, Shana Samuel. Hello, offloaders. I want to start today with a true cautionary tale. I was speaking to the VP of Analytics in an organization recently, and the thing is, on paper, she had done everything right. Her organization was really promoting the use of AI, and she wanted to be seen as a leader, so she championed AI tools. She figured out where they might be able to offload some reporting to AI, got the buy-in, and did this all in a way that freed up to FTE on her team to be able to focus on other things. This looked like a huge win. Then, she was in a QBR meeting, a quarterly business review that went sideways. Someone noticed a quirk in the data asked a question, and as she started looking into it, she realized the reporting was unraveling. As she looked deeper into it after the meeting, it became clear that there were three consecutive quarters of key business analytics, the stuff that they were using to make business judgments at the C-suite, three consecutive quarters that were infected by hallucinations. AI hallucinations. The data was just wrong. So three quarters of decisions made on bad data. Her bad data. Now she was left not just having to explain the errors, but also the judgment that got them into this place, in the first place. When I spoke to her, she had gotten beyond the initial panic, and now is just coming to terms with the reality. When she said to me, I was so focused on being seen as a leader on AI that I skipped over some of the due diligence that I should have done. I personally think we're going to hear more and more stories like this in the coming years. There is an AI reckoning that is coming because there is huge potential in it and also some pitfalls. Almost every client and potential new client that I'm talking to right now, every single one of them are grappling with AI in some form. For a few of my clients, they are truly excited about AI. They enjoy it. They're early adopters. They're having fun with it. Others are less so. I would say that the vast bulk of people that I talk to on a daily basis feel a lot of pressure around AI. I think the pressure really comes in two distinct flavors. There's the pressure to just keep up, to show that you're on top of the technology by learning to use it well and then leveraging it in the ways that your organization wants it used. In some organizations, you might be working in one that has a mandate. They want to see people using it a certain amount or they're tracking how many queries you're putting in. Other places are maybe not that organized in terms of how they're thinking about AI. I've definitely heard some cases where bosses are really championing AI and they're asking everyone to just run everything through AI, whether it makes sense or not. There's also though the pressure to keep ahead. So AI has already remade the employment landscape and in some fields, I'm thinking from software engineering to analytics to copywriting. Some of these fields are being decimated or completely remade because AI is able to perform a lot of the low level tasks or the entry level tasks quicker and cheaper than a human being. So now in addition to worrying about whether your job could be at risk due to offshoring or outsourcing, now you need to worry about whether AI could be coming for your job too. So I think there's a lot of pressure right now to show that your work is still relevant in the age of AI or they're trying to find some kind of safe job that's protected from AI encroachment. But today's episode, I really want to talk about what that pressure is actually making us do because one of the things that I see as a coach, I see the same mistakes showing up over and over whether you're in a job search or navigating AI within your current role. There are four mistakes that I see frequently. These aren't the only four, but these are the most frequent four that I see that are really hurting smart women's careers. So let's talk today about the four mistakes and how to very importantly avoid the pitfalls. Okay, so mistake number one. Probably one of the top questions that I get from women who are job searching right now is should I take some kind of AI course or get this AI certificate so that I have something AI related on my resume in the certifications. My honest answer is no. And at some companies it can even work against you. So mistake number one is thinking that you need an AI certificate on your resume in order to be competitive. Let me talk about why I feel so strongly that this is a mistake. First, hang on. I think the instinct here really makes sense. I understand what you're trying to do if you're a job searcher. You're like, I haven't maybe worked directly with AI in my role. So I need something on my resume that's going to help show that I'm keeping up, right? I understand the technology that I'm current that I get it, right? So you want to show that you're not behind, but here's the thing. A certificate does not do that. The hiring leaders that I'm seeing are not looking for your coursework, right? They want to see evidence. They want to see where have you used AI, what kind of business problem did it solve, what were you able to change and drive as a result of that? In many tech organizations, organizations that see themselves as tech forward, certificate doubly backfires because it sort of raises a question that you don't necessarily want to have asked about you, which is like, oh, does she need help to figure out AI? There is this perception, rightly or wrongly, there is a perception in many organizations that the people who are really leading on AI are figuring it all out themselves. They're getting in their own up their sleeves and trying stuff out, right? That they're so genuinely curious and clever that they don't need teaching. Again, I'm not saying this is right. I am saying it is a perception that's out there in a number of organizations. When they see an AI certificate on your resume, what it tends to signal is that you are catching up, not leading in their eyes. There is one really important exception to this. If you are doing PhD level research in machine learning or AI topics, this is often highly, highly valuable and these credentials are sought after. You often have some very specialized spheres of knowledge that can make you quite sought after on the job market. But if that's not you, right? If you're not in a PhD program writing your dissertation right now, then I want you to heed this advice. Take the AI course if you are genuinely interested and if you feel like this is something that you want to do. But don't invest a bunch of money thinking that this is a credential that's going to help you on your resume. What can you do instead? I'm doing right now with clients looking at one really clear data. defensible use case. We build it, we track it, we turn it into a resume bullet. For example, I had a client who was working in an organization that had a mandate and wanted everyone using AI. And what she noticed in her group was that it was chaotic. The results were inconsistent. People were all over the place in terms of their comfort level and using things. And it just felt like everyone was trying to reinvent the wheel with very different levels of success. So she was not an AI expert, but she was a leader in the company. So she started to standardize some processes for the team around AI adoption, around prompting, around the kinds of outputs that they were looking for, and very quickly the quality of the products went up. The stress of the team went down because now the people who were less comfortable using it have very clear direction. And leadership started to notice that morale was up, quality was up, and adoption was up. This became a resume bullet and a story that could be used in interviews. So the winning formula here is really showing that you're not learning AI, that you are leading with it. Okay, let's talk about mistake number two. This is a big one that I see with job seekers and oh my goodness. If you've come to any of my job seeker workshops, you've probably heard me plead with you. Please do not make this mistake. The mistake, handing your resume over to chat GPT to write or rewrite. I know, I know the logic here, it's relatable. Your resume needs an update. It's painful to do. Chat GPT seems like it can just make it so much quicker and easier, right? Isn't writing supposed to be what AI is good at after all? I get it. On top of that, ATS systems, those application tracking systems that determine whose resume even gets looked at by a human. These are brutal. So you know that you need to get a bunch of keywords into your resume and if AI can help you get past the filters, well why not use it? I get it. I get the impetus, but there are a few reasons why this is a mistake. First and probably foremost, chat GPT, in my opinion, having looked at a lot of resumes, chat GPT is simply not there yet when it comes to resumes at the mid to senior level. Now, for your high schoolers first activities resume, chat GPT is absolutely fine, right? It can definitely get that high schoolers activity resume off the ground. Use it for that. But for more senior levels, having looked at the output, it's lackluster. If you know a little bit about how chat GPT and other large language models are designed, they're really made to help predict probable words that people would use. So the thing is when you're using something like chat GPT and asking it to write a resume bullet, you're often getting generic interchangeable texts. Usually not quite right for the specifics of your industry, your target role, or really importantly the level of value that you need to convey at a mid to senior level. So yes, you do need to tailor your resume to get past the ATS systems. I don't argue that at all, but you also need really high impact bullets that can concisely convey the value that you bring. So what can you do instead? Here's where I really like to use chat GPT when it comes to resumes. Use it as a proofreader, not as a ghostwriter, right? So you will need to put in a little bit of work in terms of writing the substance of your bullets. This is something I spend a lot of time doing with clients kind of thinking about how we structure the bullet, how we frame it, how we really bring the impact out, and then you can use chat GPT to catch typos, flag phrasing that's not clear, or review the wording and formatting. This can be a great way of using AI. For some of you, you'll remember back in the day when you were redoing your resume back in the day, meaning just a couple years ago, you would hand your resume over to a friend who would, if they were good, spend half an hour just combing through your resume for typos and formatting issues. AI can really save you time on that. So that can be a great way to use AI. There are some other AI tools that are resume specific that I do recommend to clients, but even there we're always applying a human filter to make bullets stand out and to make your resume distinctive. Stand out resumes, be generic resumes every time. All right, let's get into mistake number three. This is faking AI enthusiasm when you have some real concerns. A client of mine was a senior manager in her company's tech division. She was early 40s and was raising some thoughtful concerns about her company's AI implementation plan. Her delivery may have been a little bit clumsy, but she was expressing some legitimate concerns about the gap between what the tools were promising to do and what they were actually delivering. And her boss's response, you need to get on board because the train is already moving. I mean, she got the message loud and clear. Like she better look like she could quote unquote keep up. This message is super loaded because you know if you are a 40 something woman in a tech focused area, you're up against not just sexist stereotypes, but also agist stereotypes that you must be behind, right? I mean, Tim Cook, as I'm recording this has just announced his retirement from Apple, but I've never heard anyone suggest that he as a 65 year old male wasn't capable of keeping up with the technology. But can you imagine a female CEO getting the same benefit of the doubt that rarely happens? So this senior manager, she did what a lot of us do started nodding along, suppressing the questions that actually were quite critical to the company's success. The research on gender and leadership really backs this up in frankly a depressing way. And it's something that I see playing out in real time in many companies. Men who raise concerns about AI or any new technology, they get read as seasoned, strategic discerning. Women who raise the same questions get labeled as resistant, risk averse, or the most maddening one, not able to keep up. This is systemic bias in workplaces that still tend to read women's caution as limitation rather than leadership. And so what do we do to try to counter that? We perform. We nod. We volunteer to lead that AI working group even though inside we're feeling wary and skeptical. We put our own internal judgment on the back burner to try to win the external approval. And that is exactly the kind of thing that led to the VP of analytics I mentioned at the start of the episode led to that reckoning in the QBR. The thing that I think it's all too easy to forget is that it's really difficult to make your best business decisions from an inauthentic place. When you're trying to fake enthusiasm that you don't actually feel that ends up showing through. And it also tends to build up a lot of anxiety and worry because you're spending so much time in energy suppressing the real skepticism and questions and doubts that you have to try to paste on a smile and show up in rooms pretending everything's hunky-dory. That requires a lot of energy. So what do you do if you're in an organization where you feel like you need to get on board with whatever the vision is? Well I want to remind you there are multiple ways to lead on AM. in a current environment. So one thing I'm doing a lot of work with clients on right now is really establishing their brand around AI leadership for the current moment. So I'll give you three ways that I think work in a number of organizations, not every organization, but these are three of the most common ways that I'm currently working with clients on this right now. The first way of being a leader in AI right now is the visionary. This is probably what everyone thinks of when you think of leadership right now. This is someone who sees the potential in AI, spots it early, moves fast, makes bold moves, and if this is authentically your lane, if you are the visionary, and I know some clients who are in this space, own it, right? You don't need to walk away from that, but if it's not, I want to reassure you, you don't need to fake it. There are other ways to lead. So one of these is what I call the guardian. The guardian is really good at seeing the gap between the promise of AI and its current reality. So she understands AI really well. She understands what it can do and she understands its limits. She is the one who probably would have caught the potential for AI to hallucinate some numbers before those reports ever went in front of the C-suite. The guardian is not a skeptic. She is just a really good risk manager for the organization. She thinks ahead and can spot potential issues before they become an embarrassing mistake. And I think the guardian is worth her weight in gold in almost every organization right now, especially if you're working under a visionary leader. She's the one who has their back and makes sure that it's protected. A third way of leading right now that I think it can be enormously effective is what I call the Sherpa. The Sherpa understands that behind all the AI adoption, we have a human workforce that has a lot of adaptation to do. She is an expert at helping people move along the change curve and get where they need to go faster. And she's also able to bring along the people who are probably most at risk of falling behind when it comes to AI. So the Sherpa really focuses on the human dimension of AI in the workforce. And that is a super skill right now. But here's the thing. As you're thinking about leading in the age of AI, you need your organization to understand and value the role that you're playing. If no one knows what you're doing, right, then if you're the guardian, like my client who had some legitimate questions, the guardian will tend to get labeled as negative or not on board, right? The Sherpa can just get purely overlooked. People think this is just happening by magic, all that glue work and labor that she's putting in don't get recognized. And there are also risks to being the visionary. The visionary gets a lot of the credit, but the visionary can also end up holding all the blame. So I want to be clear as you're thinking about how to position yourself as a leader in the age of AI, these are just some thought starters for you. This is not going to be a one and done conversation with your boss to be like, here's what I'm doing. This is a series of steps to really hone your personal brand in the age of AI and start to shape the narrative of how you're perceived within the culture that you're working in. Super important. All right, let's turn to our final mistake. Well, it's not the final, final mistake, but it's the final one for this episode, the fourth that we're going to talk about today. And that's not having a clear personal playbook for how to use AI. A lot of people are just using AI reactively without a lot of intentional thought or structure. And frankly, there are some organizations that are complicit in this, right? They just want people using it as much as possible. And there are some really interesting new research out that shows that without a clear structure, AI tools don't actually reduce your workload. They intensify it, right? So the promise of AI of making us all more productive, more efficient, giving us hours back in our day, that's not what's happening on the ground. What researchers are finding is that people are ending up multitasking more, losing their breaks, and taking on a bigger scope of work. And this is such a big issue that I'm going to devote a whole separate episode to this. So two episodes for now, I'm going to drop an episode that's all around creating this playbook. I was actually invited to talk about pressure and burnout in the age of AI recently at a summit. So after my talk is published there, I will publish it here for you as well. So you'll get that in a couple of weeks. Because there are some real costs here and they're not getting talked about when you're perpetually multitasking and overloaded. It creates decision fatigue. Your judgment gets foggy. Instead of feeling better and more productive, you're feeling worse, more burned out, potentially not catching mistakes that you otherwise would have caught. And that is not how your best work and best decisions get done. So when I talk about a playbook, and again, I'll talk about this in much more specific detail in a couple of episodes, it's not about using AI less. It is about thinking about how you can use AI in a way that keeps you sharp, keeps you sane, and keeps your business judgment intact. Which in these times is super critical. Okay, so today we talked about four mistakes. And all really boiled down to the same root cause. It's reacting to and trying to use AI out of a sense of anxiety instead of approaching it with clear understanding and strategy. The person out there trying to buy an AI certificate, she's trying to signal something that she's afraid is going to hold her back on the job market. The resume outsourcer trying to shortcut something that actually really needs her input and thinking. The enthusiasm faker, she's trying to protect herself from a label she's afraid of. And the woman without the playbook is just trying to keep up, but ends up paying for it with her bandwidth and burnout. The pressure is real, but when fear is in the driver's seat, it's your career that ends up eating the costs. But when you're clear on the pitfalls and understand how you can avoid them, I hope that working with AI becomes so much less scary. So here are two things that I want you to think about coming out of this episode. First, are you on the verge of any of these mistakes? If so, just note what's happening and take these tips as a little advanced warning to shift course. And second, if mistake number three that trying to fake enthusiasm is the one that comes up for you, I invite you to really just ask yourself, "Hmm, am I visionary, a guardian, a Sherpa, something else?" Because if you have a sense of who you are, but your leadership doesn't have a clue what role you're playing, you're not the problem. It's just a positioning problem, and that is fixable. So offloaders, let this be the call you need to start leading in the age of AI. Are you ready to step into a life where you success at work and success at home, go hand in hand? Then it's time for the mental offloads to step down ritual. It's a proven, practical method to help you log off and work behind. You can own your evenings and be present to people you love, and the step down ritual makes it easy. Deem the power to truly walk away from work, and be present with the people who matter when those two. It's just what you need if you wanted to achieve big things in the world without losing your mind. Ready to reclaim your time and your peace of mind? Go to www.thementaloffload.com/shutdown and get your free download of the shutdown ritual. That's www.thementaloffload.com/shutdown. and joining next week for the next episode of the Mental Offload Podcast.