I Use AI Every Day. And I'm Not Sure How I Feel About That.

Welcome to Suits and Pajamas, where grace meets grit and ambition learns how to breathe. Well. Hello my suited and booted friends. This is TJ Albert Calm coming to you with another episode of Suits and Pajamas, the podcast where we talk about that tension between showing up as our professional selves and our personal selves. And sometimes those worlds collide. Today I want to actually kick this off by first thanking those of you who have bought my book, Suits and Pajamas, a memoir of grace, grit and becoming. I have not been as consistent with my podcast for the last few weeks because I have been really leaning in heavy with my book launch. And you know, I still have my job that I love, of course, but I still have that I have to do. So I've really been burning the night oil just trying to get out there with my book. So if you've bought my book again, thank you. If you haven't, you can buy it on my website, suitsandpyjamas, or you can buy it on Barnes and Noble, Amazon, ingramspark, you name it, it's out there. Apple, I believe you can buy it there as well. And you can, if you have an e reader, definitely can download it as as well. Okay, with that done, I want to talk about today's episode. I think it's very timely. I don't know about you, but I use AI every day and I'm not sure how I feel about that. So I want to unpack this conversation because I don't think I'm alone out here and feeling conflicted. So let's talk about what the situation is. Right? You work in tech. Your company has mandated AI adoption with KPIs attached to it. You use AI tools yourself. They make your work sharper, faster, free up times for you, time for you to be more strategic. Right? Which is, I think, a good thing. And you are watching the same technology being used to justify cutting the human capital that built the companies that are now deploying it. So here's the conundrum. You are both a beneficiary and a witness. That is an uncomfortable place to stand. Now there's the suit side that says AI is a force multiplier. It eliminates low value tasks and frees humans for higher order thinking. The companies that don't adopt it will fall behind. The net job creation from AI exceeds displacement. That is a fact. This is not the first technology wave that felt existential. And it wasn't. I always say that wrong. That word wrong. I just realized existential. I think we all have that word. That must be my word. Anyway, on the pajama side, the net job creation argument is real, and it doesn't help the 41% of employers who plan to reduce headcount using AI in the next five years. And in addition to that, AI hiring tools have been documented to prefer white associated names 85% of the time over black associated names or Latino Latina associated names. I guess I'm screwed because my name is not white associated. And then there's the environmental impact. The carbon footprint of AI in 2025 is comparable to New York City's annual emissions. The people building this technology and the people absorbing its consequences are not the same people. That asymmetry matters. And so let's talk about the lived truth. You don't get to opt out. Your company has already decided that KPIs are real. So the question is not whether to use AI, it's how to use it without losing the thing that made you irreplaceable before it arrived. Who Hope you're ready, because I think this is going to be a very powerful episode. Grab your coffee, tea or wine or whatever suits your fancy and let's get into it. I want to tell you something I don't say out loud enough. I use AI every single day in my work, in my personal brand. In the research behind this podcast, it truly has made me faster, sharper, and more strategic. It has compressed hours of work into minutes. It has given me the capabilities that I didn't have before. I don't think I could produce the podcast, write the book, pay my bills, run a household for the most part, in so many ways, without it. I just. It's tough because I have very ambitious goals. But I am conflicted about it in ways that I have not fully resolved. Not because I don't understand the technology. I work in tech. I've spent 25 years in environments where new tools arrive, and the question is never whether to adopt them. It's how fast and at what cost. But folks, this one is different. And I think the people who tell you it isn't different are either not paying close enough attention or have too much invested in the answer to be honest about the question. Today, I want to have an honest conversation about artificial intelligence AI. Not as a hype conversation, not as a doom conversation. I just want to have an honest one. With receipts, with my own conflict on the table, and with something hopefully you find useful at the end. Because here's what I know about you. Your company may have already mandated AI adoption. You may already have KPIs attached to demonstrating efficiency gains. And you may be sitting in a meeting watching leadership celebrate what AI can do while you are quietly wondering what it means for you. That tension is real. And so we're going to just talk about that now. I want to talk about my specific conflict and look, let me be precise about my conflict because I think imprecision is where a lot of AI conversations go wrong. People talk about AI as if it's one thing. It isn't. It's many things with many different implications and trying to collapse them into one reaction misses what's actually happening. Here's what I use AI for research, impression content drafting, pattern recognition across large amounts of data as I'm rolling out like our AI adoption at the company that I work at. Yes, I'm using it for pattern recognition and use cases that we have currently under review. And then I use it as strategic thinking support, not as a replacement. I've seen some people actually use AI as a replacement and it really should be a supporting tool. And so it has made my work product better. It's not perfect and that's where the human in the loop becomes really important. But I am not going to pretend that it's not otherwise helping me. It is a genuine force multiplier and I experience that every day. Here's what I watch AI do in the broader environment that I work in. Justify headcount reductions, replace potentially entry level functions that used to be in the training ground for the next generation of mid level talent. I've watched it get deployed by companies, not necessarily the company I'm at, but I've seen it deployed by companies that are simultaneously telling their remaining employees to demonstrate efficiency gains. Which is a sophisticated, kind of a sophisticated way I guess of asking people to build a case for their own redundancy. And again, I'm not specifically speaking to my company, but I do see it happening and there is a pattern. I think we all read the news and so I'm on both sides of that line and that is really uncomfortable. I am choosing to say this out loud because I think a lot of people in professional environments are living that same discomfort and not naming it or not comfortable talking about it. And so I'm going to give you the data that sits with me. The IMF's 2024 assessment found that approximately 40% of jobs globally face meaningful exposure to AI capabilities. In high income countries, the ones where most of you listening are probably working, that number rises to 60%. And the World's Economic Forum's 2025 Future of Jobs report projected 92 million roles displaced by 2030 alongside 170 million new roles created net positive technically, but those numbers do not live in the same bodies. So the person displaced from a mid level administrative role is not automatically going to be the person who fills the new AI oversight position. So that transition is going to require retraining, time, access and often it's going to require a different educational background than the person being Displaced. Currently has 41% of employers globally plan to reduce their workforce in areas where AI can automate tasks within the next five years. As I shared earlier, and it's not eventually in the next five years. This is not a projection about your grandchildren's job market, right? That is your next performance review cycle extended and the entry level numbers, by the way, are the sharpest. Big tech companies reduced new graduate hiring by 25% in 2024 compared to 2023 Anthropic CEO has stated publicly that AI could eliminate half of all entry level white collar jobs within five years. Sit with that. This is that is not a conspiracy theory. That is the CEO of an AI company telling you what his technology is designed to do. And I'll just throw in a little side comment here of I respect higher education, but I do think that depending on what you choose to study, you're going to spend a whole lot of money on something that it's going to be tough to get a job, an entry level job, unless you're pursuing a career in AI or AI adjacent, but neither here nor there at this point. So I want to talk about how there are two receipts that I want to put on the table that I really think deserve a little bit of airtime than they're currently getting. First, one that's like really near and dear to my heart is AI bias in hiring. A University of Washington study in 2024 gave three AI models identical job applications, same qualifications, same experience, with only the name changed. AI models preferred white associated names in 85% of those cases. Black associated names led in 8.6%. In 2025, a class action lawsuit against Workday was certified in federal court alleging its AI screening systematically discriminated by race, age, disability, and let me be direct about what that means. The same technology being deployed to make hiring more efficient is documented to be making it more discriminatory for the communities that have historically had to work twice as hard for half the access. AI is not a neutral tool. It has absorbed the biases of the data it was trained on and is now applying them at scale with the speed and authority of an algorithm. Second point I want to talk about that is near and dear as well is the environmental cost. As I said earlier, AI's carbon footprint in 2025 is estimated to be comparable to New York City's annual emissions. Think about that. Its water footprint could reach the equivalent of all bottled water consumed globally in a year. A single ChatGPT search uses nearly 10 times the electricity of a Google search. Shout out Google for those of you who are anti AI, but seriously, creating one AI generated image uses as much electricity as charging your phone. That is crazy to me. The tech companies that are deploying this infrastructure are largely not disclosing their specific AI environmental data. Google stated in a recent environmental report that it did not wish to report indirect water use because it does not fully control water consumption at power plants. We are being asked today to adopt technology whose environmental costs are being actively concealed by the companies that are profiting from its deployment. And so now I'm going to go into the suit side, right, button up my suit here and have a conversation around the fact that AI is a force multiplier that eliminates low value tasks. And as I said before, it frees humans for higher order thinking. So here are the full defenses for the suit side because it deserves one and because I personally hold parts of it. Okay, so I'm just full disclosure and I know this and hence the conflict. For me, the productivity argument is real. AI genuinely compresses work that used to take hours into minute, turns them into minutes, turns it around in minutes. It handles pattern recognition at scale and speed no human can match. It frees people from low value, repetitive, low value repetitive tasks when it's deployed thoughtfully. And it elevates the quality of the human, the work that humans can focus on. I've experienced this directly. My work in certain areas is better because of AI, not all areas. Okay, that's just a fact. And that. But that's not a talking point. That is my lived reality. The net job creation argument is also real, even if it's a bit complicated. In 2024, AI related hiring, as I shared earlier, reached approximately 119,000 jobs, while confirmed AI driven job losses were around 12,700. Again, this was 2024, not 2025 or 2026. We know those numbers have jumped exponentially, but that data at the time was centering around the build out that was required for AI infrastructure, which created 110 construction jobs in 2024 alone. So think about the data center build outs it created 110,000 construction jobs. The thing about that is that's a one time kind of build. Where those 110 construction jobs in 2024 that came from building the data centers. I am curious and I'll have to research this and I'll try to follow up with you guys on how many of those 110 construction jobs led to permanent long term jobs versus once they built it, those jobs were eliminated. I have to check into that. In any event, the historical argument has weight. Every major technological disruption, mechanization, electrification, the Internet, mobile computing, they all produce displacement anxiety that was legitimate in the short term and proved less catastrophic than predicted in the long term. The typewriter killed certain jobs, it created others. The ATM did not eliminate bank tellers, it just changed what they did. The pattern has precedent. And so the suit side also has a direct message for the employee being asked to demonstrate AI efficiency gains. Quote, learn the tool, end quote. Right. Control the narrative of your own adoption. The employee who understands AI well enough to direct it is more valuable than the employee who resists it. That is just a fact. So your expertise is not replaceable, but your resistance to the tool may make you appear replaceable. That argument is not wrong. Maybe a little uncomfortable, but it's not wrong. Now let's flip to the strong what I think is the strongest suit argument that I find genuinely compelling and I want to sit with before I complicate it. AI does not replace human judgment. It replaces human tasks and the professionals who understand the difference. Who knows which of their tasks are automatable and which require the lived experience, the contextual wisdom, the relationships, the ethical navigation that no model can replicate. Those professionals are not threatened by AI, they are amplified by it. So my. My 25 years of receipts cannot be trained into a model. And my specific pattern recognition built from two and a half decades of navigating environments that were not designed for me. That is not a data set. That's me. And AI can't be me. All that knowledge is mine. And so I'm going to pivot for a second and I'm going to come back to the suits versus pajamas reconciliation. But on the pajamas side, I want to talk about the truth. Plainly stated, the historical comparison to previous technology waves that I mentioned before is partially correct and strategically incomplete. Yes, mechanization created new jobs. It also produced decades of economic dislocation for specific communities that did not benefit from the net positive. The aggregate numbers were fine. The individual experience was not, and the people who bore the cost of that transition were not the people who designed the technology or owned the companies that were deploying it. That is a fact. That asymmetry is repeating. AI biased data is not a bug. It is a documented feature of systems trained on historical data that contains historical discrimination. When an AI hiring tool prefers white associated names in 85% of cases, it is not malfunctioning. It is functioning exactly as as trained on data produced by a hiring system that already had those preferences. The algorithm is literally a mirror. And we are now scaling what the mirror reflects for women of color in professional environments who have already documented that they must outperform to stay in place, who have already navigated systems not designed for them, who have already watched others fail up while they built the presentation to prove that their com, what their what their company already knew. AI hiring bias is not an abstract concern. It is an additional filter for us in a system that already has way too many. And I want to pivot a little bit to talk about the KPI conversation. Right? Because that's what we're all hearing and talking about. So I want to address directly the employee who has been given an AI efficiency KPI because I think this is one of the most under examined dynamics in the current AI adoptive adoption wave. When a company asks its employees to demonstrate efficiency gains through AI adoption, it is doing something very specific. It is outsourcing the proof of concept work to the people most at risk from the technology. You are being asked or it feels like you're being asked. I won't speak for everyone. It feels like you're being asked to build the business case for your own displacement. I've had conversations with people that are feeling this way. And the implicit contract is demonstrate how much faster this can be done with AI and we will reward you with continued employment. That's kind of how it's feeling for some people. And not all companies are doing this. But I've been having a lot of conversations with a lot of friends and peers and at different conferences and things like that. And until people are being made to feel that, until we don't need you to demonstrate it anymore, or we don't need you to demonstrate it anymore, I guess is the better way of saying that because we have the actual tools to do the demonstration. Does that make sense? Yeah, that's really kind of what I was saying, I think. Sorry, I got distracted for a second anyway. And I don't want to lose track here. I'm not saying that this is every company's intention again. Right. But what I am saying it is the logical endpoint of the efficiency gains mandated and the people handling that are handing out the KPIs have not always thought through the human implication of what they are asking. Some do, some we know are just ready to just, you know, cut off their nose to spite their face. Because some companies, as we know that it did this, are regretting that decision and are trying to hire some of those folks back. But yeah, it's very real. Again, that conflict. I'm not sure how I feel about it and I do want to dig in a little bit about the environmental silence. It's amazing to me after giving you all those numbers and stat statistics and whatnot, it's very concerning for me that most people are not aware of the impact. I think what I often hear is people saying they don't understand why there would be an environmental impact using AI. So that tells me that it's not being discussed very much. People are just understanding like the power of AI, but they're not understanding like yes, there is a direct correlation to the environment. And look, I think the AI companies are not going to highlight that. So I think that's on purpose that the environmental impact is silent. And so the environmental data is part of this conversation that I find the most morally uncomfortable. Not because I'm about to stop using AI or because I'm not, so I'm not going to be a hypocrite here, but it's because the companies profiting from deployment are actively concealing the cost and, or they're not doing their part to give back to the environment that they are destroying, they probably can't keep pace. Right? Because as I shared before, it's amazingly devastating the impact of AI. But there it doesn't seem from my perspective, I haven't seen a whole lot of effort to minimize that impact. So when Google states in a corporate environmental report that it does not wish to disclose indirect water use because it does not fully control water consumption at power plants, to me that's just a company choosing opacity over accountability on a question with global implications. This is not some small thing. This is this. These have global implications, people. And so the people whose water supply is affected by AI data centers that are being built out in their communities, they did not consent to that trade off. They were not in the room where it was decided. And for those of you I know, Texas right now has a significant number of freaking data centers that are being built and I believe there's one outside of where my dad lives in, outside of Amarillo, Texas. And the impact to the communities is going to be devastating. They just don't know that yet. And to me, that is the freeway problem applied to a new domain. The infrastructure was not designed with everyone's interests in mind. And the people absorbing the cost are not the people making the decision. And so when you're, you hear about local leaders having town halls and council, city council meetings, the average person doesn't go. But trust me, people, that's where a lot of these approvals are happening. Because these companies need land to build these data centers and those lands are procured and approved by your local government. So don't want to get too political on this, but just letting you guys know, like there are consequences to not attending those meetings where those decisions are being made. And frankly, in today's climate, politically, just as a sidebar, you can still show up and they're going to vote the way they want to vote because they probably have a financial interest in letting those data centers be built. So anyway, as for the lived truth, right? Here's, here's what I actually believe after sitting in this conflict, because I'm leading GUM gums, the company I'm at now, I'm leading our AI adoption and building it from scratch. And so after having sit with this conflict and after using the tool every day and watching its implications in the broader environment that I work in, I know AI is not going away. The mandate is real. Again, you can't argue with the efficiency gain and that competitive pressure is real. Companies are trying to figure out how to leverage AI to give them a step up on their competition. Right? So again, I get all of that. I also understand the employee who refuses to engage with the technology. But they're not going to slow AI's adoption. They're only going to slow their own positioning within the environment that is adopting it. So the question is not whether. The question is how. And how's it going to be? How are you going to choose to leverage it? Is it going to be on your terms or theirs? So here's how I think about navigating mandatory AI adoption without losing what makes you irreplaceable. First, identify which of your tasks are automatable and automate them yourself. Don't wait for your company to do it. The employee who proactively identifies what AI can handle and redirects their energy to what AI cannot, like judgment, relationships, contextual wisdom, ethical navigation is not at risk. They are demonstrating the value that can't be replaced. Second, and by the way, on the first point too, if you're concerned about the environment and some of the other things that I've kind of shared already. Then limit your use. Be very strategic about the high impact areas that you can use. AI that don't require a lot of AI consumption. Be strategic. Second, document what AI cannot replicate without you. Your lived experience, your specific pattern recognition, your relationships, your track record. Right? These are your receipts. In an environment where AI is demonstrating efficiency, you can demonstrate irreplaceable judgment. Those are different things. Make sure your leadership understands the difference. Third, who. This one's tough. Name the bias risk. Name it. If your company is using AI in hiring or performance evaluation, ask what bias audits have been conducted. You have the right to ask, especially if your performance is directly tied, your performance review, if it's directly tied to AI. That's a very fair question. The workday lawsuit was certified in federal court, as I mentioned earlier. And so employers now have documented legal exposure from AI bias. That is leverage. Use it. Fourth, I have just two more points. Fourth, build outside. The AI adoption mandate at your company does not define the ceiling of your professional identity. Your personal brand, your platform, your receipts, those live outside the company's control. So AI can help you build them. Use the tool to expand what belongs to you, not just what belongs to them, but make sure you know the difference. Right? You should not be using AI tools, especially personal tools, free tools that you've downloaded for yourself to use with company business. That's a big no. No. And that's another topic for another day because I want to talk about shadow AI and some of the other things later. But in any event, the fifth thing, consume AI intentionally, not reflexively. The environmental cost is real and corporate transparency around it is not. And so that does not mean you stop using it, right? It means you use it with intention rather than habit, as I kind of shared just a few minutes ago. And so remember, a ChatGPT prompt uses nearly 10 times the electricity of a Google search. So if you're able to use Google, use Google. And so I think you should just ask yourself before you reach for it, is this the right tool for this task or is it just the fastest one? That question, by the way, is not about guilt. It's about using the most powerful tool in your arsenal with the same strategic intention you bring to everything else that you do. You don't swing a sledgehammer to hang a picture frame. Use AI where it has genuine leverage. Don't run it idle just because it's there. And so I said at the beginning that I'm conflicted, right? And I want to be honest about where that conflict lives. For me personally, I'm not conflicted about using AI. I use it. It helps. The productivity gains are real and I'm not going to perform ambivalence that I don't feel. I am conflicted about the asymmetry, about who benefits from the efficiency and who absorbs the displacement. I am concerned about the bias being scaled. I am concerned about the environmental costs being hidden. I am concerned about employees being handed a mandate and told to prove its value while the people handing them the mandate have already decided what the answer will be. And so I hold both of these things simultaneously, right? The tool is useful, the deployment is not neutral. And pretending it is neutral because the tool is useful is a form of intellectual dishonesty. And I'm not willing to practice that. And you don't have to resolve the conflict to navigate it. You just have to be clear eyed about what it is. I don't have all this figured out and neither do you. And honestly, that's the point. We are navigating real situations with real stakes in real time, together. You are not alone in this tension and you don't have to resolve it to keep moving. Until next time, have a great week.