EP 132: Enterprise AI - Future Careers and How to Prepare
27 Oct 2023 · 39 min
Christian Hammer, CEO of Vala Inc., explains how generative AI will eliminate the translator role many white-collar workers play between humans and technology. He predicts widespread AI assistants, Microsoft 365 Copilot adoption, and continued demand for engineers doing higher-level work as routine tasks automate. His advice: keep learning and push AI toward human-centered outcomes.
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This is the Everyday AI show, the.
Everyday podcast where we simplify AI and bring its power to your fingertips. Listen daily for practical advice to boost your career, business and everyday life. What do future careers look like in the age of enterprise AI? Are we all just going to be extensions of robots? Are we gonna be answering to chat GPT all day as it's our supervisor? I don't know, but that's why I bring smart people on the show. So welcome to Everyday AI. My name is Jordan Wilson. I'm your host and thanks for joining us. This is your daily livestream podcast and free daily newsletter where we help everyday people like you and like me understand AI and how we can actually use generative AI to to grow our companies and grow our careers. There's always so much going on every day. So today we're going to be talking about future careers. What do they even look like, especially in and with enterprise AI. I'm fascinated to talk about this today. I'm super excited for our guests. If you're joining us live. Thank you. If you're joining us on the podcast, always know that you can come and join the live conversation. Ask questions and get your questions answered as well. That's something I love about the show. I joke around. It's the realest thing in AI. It's real people talking, hanging out and learning AI together. So before we get to that, let's talk about what's going on in the world of AI news. So first, how good is generative AI? Well, it's so good that even Amazon is surprised. In an earnings call just a couple hours ago, Amazon CEO Andy Jassy said he's been, quote, unquote, surprised by by the fast growth of the company's generative AI business. The company's cloud business as an example. AWS saw flat revenue growth compared to last quarter, but at the same time, overall profits tripled. So it's safe to say that generative AI, specifically Amazon's generative AI business, has been booming. I'm not surprised. But, you know, who am I? I'm just a guy talking. All right, next piece of AI news. Phishing emails are getting better thanks to ChatGPT. I don't know if they're getting better or worse. I guess people writing phishing emails are getting better at it. So a recent study by IBM showed that AI chatbots such as ChatGPT are becoming increasingly sophisticated and can create convincing content, specifically when it comes to phishing emails. So this study conducted by IBM showed that ChatGPT could generate a phishing email in a matter of minutes compared to 16 hours from a human team. And the human team kind of, they went head to head and the human team only had slightly higher success rates. But 16 hours versus a couple of minutes for, you know, pretty much similar performance. But then I also thought about this. I'm curious what took the team 16 hours to create the phishing email? I'm sure they can answer that. All right, our last piece of AI news for the day is OpenAI is bracing for catastrophic risks. So OpenAI has established a new preparedness team to address potential catastrophic risks associated with powerful AI models. So this new team will focus on capability assessments, evaluations, internal red teaming, and then develop a risk based development policy for accountability. OpenAI is also launching an AI preparedness challenge to prevent misuse, awarding API credits and seeking talented individuals for this team. Obviously, critics are questioning why OpenAI is kind of relying on an internal team and why there aren't kind of more outside or separate teams to do this. So I guess, you know, part of me is like, oh, okay, this is great. But also OpenAI is openly working toward artificial general intelligence or AGI, but at the same time creating a catastrophic or, you know, preparedness team for what they are probably going to help us discover. So kind of a brain teaser there. Right? But we didn't come to talk hypotheticals on OpenAI. We actually came to talk about enterprise AI and talking about future careers, what they are and how we can prepare. So, so let's, let's do that, shall we? Let's bring on our guest for today. I'm extremely excited to have on the show, Christian Hammer. And Christian is the CEO of Vala Inc. Christian, thank you for joining us.
Jordan. So glad to be here. I, I actually do have a hot take for you.
Oh, let's go. Can't wait. Let's start it out. Let's start out with a hot take.
Yeah. We are already puppets to the technology. Most of our careers. People listen to this show, my wife's career, which has nothing to do with technology. All she's doing is managing the, the, the various pieces of software and the best various technology that, that enables her to do her job, but her job is really managing the technology. So we're already puppets to it. It's so true.
Yeah. And, and, and there was, I see these, these news stories all the time, but there was another company, I think this time in Poland that appointed a robot AI CEO. I don't know if you saw that one, but you know, that one is is taking it quite literally, you know. But Christian, maybe let's start out. Tell us a little bit, you know, your background and a little bit of what you do at Vala.
Well, my background goes back quite a ways. I was involved in the free web, Internet doing like cgi, Perl application development for distance learning and document collaboration way, way, way back, but went through a series of startups, then went into large enterprises where I was doing this transformative executive coming in and giving them a digital DNA, helping them become, you know, innovative and applying modern technology. And most recently I decided to go back to my roots. I'm back in the startup game, focused on enterprise AI, Interestingly enough, right. Aval AI is trying to solve some of the most difficult problems in technology that large enterprises deal with. We're trying to actually get rid of the mundane, the grungy, gross things that many technology organizations struggle with and freeing the humans to actually do the fun parts. To do the parts. We actually went to school because we were passionate about to go and do. So getting rid of the tech debt, getting rid of all the, the nasty gross parts of the technology. Yeah, I love it.
So, and you know, I always like bringing on people that have extensive backgrounds in the industry because then when we talk about the, the, the, the future, you know, it's, it's important that you are, have a background and you have the chops to support it. And Christian definitely does, FYI. I'll vouch for him very, very.
Oh, thank you.
Clear in the space. So let's, let's maybe start at the end, let's start at the end here. Christian, what is the future of, of careers in enterprise AI? I kind of, you know, went on a little, you know, hypothetical in the opening of the show. I mean, are we going to be just working for robot like this company? But what's, what's the future career look like with, with AI now?
Well, I think that like I said, we, we are already doing that. It's not that we're working for an AI CTO or CEO today, but many people, especially large enterprises, are nothing but like meat puppet extensions of the technology. They're there taking the human desire, the human need, the human wants, and translating it into a form that the technology understands. And I'm not just talking about the programmers who do that. Right. The programmer takes a what we need the business to accomplish X and I'm going to translate that into code. The computer understands. But the, the HR rep who's taking the needs of the company, we need to hire somebody does this translates it into something an algorithm can understand, that they feed into LinkedIn or Indeed, or whatever platform they're using to do hiring. That's what a vast majority of white collar professionals in the United States and the rest of the developed world do today. What I think AI actually gives us is a freedom from that because now the technology actually understands us in our own language. We can chat with it and say, I'm looking for this, I want this, I need this. And so what it gives us the ability to do and what our future careers all look like is taking that humanness in the world around us and our own wants, needs, desires again and being able to radically accelerate our ability to solve for it and to, you know, get the results we desire without having to translate it into technology.
Are you still running in circles trying to figure out how to actually grow your business with AI? Maybe your company has been tinkering with large language models for a year or more, but can't really get traction to find ROI on gen AI. Hey, this is Jordan Wilson, host of this very podcast. Companies like Adobe, Microsoft and Nvidia have partnered with us because they trust our expertise in educating the masses around generative AI to get ahead. And some of the most innovative companies in the country hire us to help with their AI strategy and to train hundreds of their employees on how to use Gen AI. So whether you're looking for ChatGPT training for thousands or just need help building your front end AI strategy, you can partner with us too. Just like some of the biggest companies in the world do. Go to your everydayai.com partner to get in contact with our team or you can just click on the partner section of our website. We'll help you stop running in those AI circles and help get your team ahead and build a straight path to ROI on gen. Yeah, it's okay. That's reassuring. Okay, I'm glad I'm not going to be working for a robot at least, at least tomorrow, you know. And hey everyone, thank you for joining us live. You know, I, I always love to bring smart guests on like Christian so we can talk about these things. So, so make sure to get your questions in now and if, if you are listening on the podcast, always check the show notes. You can come back and join the conversation after the fact and join us for, you know, future, future live shows. You know, one thing I, I always try to liken AI to Christian is, is thinking back on how the, how the Internet's, you know, impacted, you know, the world, but also the workforce and careers. Are we going to see kind of a similar impact, how the Internet kind of changed roles, you know, from the C suite? From the C Suite, you know, down to entry level? Or is this going to be completely different when it comes to generative AI? How it impacts the workforce?
That is a fantastic question. I think it's one that we're all grasping to, to understand. Right. The Internet in particular was the real introduction of information as a, as a currency within the business. The data was not considered all that powerful or important prior to it. And now everybody is. You know, we all understand the value of data at any large company. So what, what does that change look like coming around this time? I think that's honestly almost impossible to really understand is how large it's going to be. But I do put this one on the order of like wheel fire, you know, this is a big change. Agriculture. This is one of the major, major ones. The Internet was probably exactly on the same scale. It fundamentally altered every business. Right. I don't know. I. My career started barely before the Internet, as we all understand the Web, as we all understand it, started to exist. So I have a inkling of what that world looked like, but I couldn't tell you. Like the, the huge change other than information became the currency and now information is so easily accessible. Our ability to automate against that information, that data is. Anybody can do it. Anybody can get themselves 10 times more productive. Anybody can accomplish at least 10 times as much. And that spreading out of that power where it used to be in the hands of people like myself, the technologists that could sit down and write code, now it's in everybody's hands. Who knows what that's actually going to do to society as a whole. The. Sorry, I could go off on this particular topic for about four hours and I'm trying to get the biggest.
Let's follow up there because I like what you said there, Christian. Like, this is like spreading out the power, you know, because I do think like early on, right. Like just as an example and you know, 10, 15 years ago, you know, the IT department, as an example, where thought of as, as wizards, you know, they still are, right. But, but now with, with generative AI, it's, it's not necessarily like that. You don't have to be a, you know, super dork like me in order to, to, to use and leverage kind of this next wave. And, and, and so, so maybe let's talk about this. And what does that mean? Like, does that mean every single role? Do we think almost Every single role is going to have a heavy generative AI components. Like are we all going to have, you know, AI assistants here in the coming months? What's, what's kind of your take on that?
No, I actually think that's exactly what's going to happen. I do think that there's still power in being a technologist because you can, you're, you're behind the curtain. You know, you're, you're still a wizard. You can do things that aren't necessarily easily addressed with generative AI, but the access you have with this technology to unblock yourself from whatever's hindering you to move forward is unparalleled. We just haven't had it in the past. So is everybody going to have technology that helps them? Yes. And there's some great, great new companies coming out that are trying to solve these problems for individual roles in the large organization. One of my favorites is a stealth startup called clearpath that is trying to figure out all the various ways that generative AI can be used within the large enterprise to solve like discrete problems that are repeat. I'll give you an example of one of the places that I've always found frustrating in the large writing job descriptions when you're trying to hire a large team. Because, you know, we do it all the time. We write hundreds. We've got a large org. You've got hundreds of jobs that are open and being open. Right. And there's a template for it. It's something that I just need to give it a little bit of detail and it should be able to, you know, it should be solvable, but you spend a ridiculous amount of time doing it. You spend a lot of time either going back and forth with the HR team, with a recruiting team, or somebody's proofreading your doc because you wrote some horrible first draft of it. But that's not necessary. Right? There are generative tools right now that you could sat down with like hey PI or chatgpt or anything like that and actually get a first draft that's probably better than anything you produce. And as those become more specialized for all the different parts of our of the Org, like hr, having a specialized tool that helps them with finding people and helps the, the hiring manager with writing the job description and all that, I think we'll see a lot of that in the very short term. In the longer term, I actually think it goes even further. And I like, I know that this is going to sound silly because anytime you mention a sci fi movie or Marvel universe, people just kind of scoff at it. But like the Jarvis like world where everybody has a personalized assistant that is helping them do what they care to do, what they want to do, what they're trying to accomplish, I think that's just around the corner. It's not necessarily AGI, but that assistant in the current form of AI that we have is doable.
Yeah. And I think that's literally around the corner in a couple of days. Right. Because one thing, even when we talk about enterprise, Microsoft 365 copilot is going to start being rolled out November 1st to enterprise companies. And I think you will see that first iteration. Right. So now kind of the big change. And anyone that listens to the show knows that I'm extremely excited about this, but maybe we can even talk about that. Like, do we think that Microsoft Copilot and the biggest change, if you haven't heard of it, this is with Generative AI being baked into the operating system of Windows machines or companies that enable kind of 365 copilot so you don't have to log into, you know, five, 10 different websites. Generative AI is going to be on your desktop essentially and working with all the programs. Is that going to be the first kind of big step that, that we see Enterprise making in gen AI, or do you think that's just going to be a blip on the radar?
I, I, I, that could actually be profound, that particular change. I've been using it already. We had early access to it at Vala and so we've been using it and it's, it's, it's amazing when it's just baked into your operating system, like how much impact it can have on you. I think it is. So I said it's going to be a profound change, but it is just that first piece. One of the parts of technology that I've always found frustrating was our interface with it. I don't think that when I was a kid growing up and we were talking about what would happen with computers and technologies in advance, I don't think any of us thought we'd still be sitting down at a computer with a keyboard, keyboard and a mouse in front of a monitor. I think that we all envision something a lot more like the Star Trek universe where we might be talking to the computer or we might, it might be embedded in our glasses or something like that, that it would be more attuned to us and not us sitting down with it. So I often wonder, and I'm hopeful for tools that were close, but just weren't quite there. Such as, like, Alexa, where the interface itself becomes something more comfortable for us to interface with something more. We're more human. And text works very, very well for. Or, sorry, text, Voice works very, very well for that. I just think that the technology that's been implemented as it is today is just missed the mark. It wasn't quite far enough in the direction of being a comfortable interface for us as humans. So. So I think that we start to go that way. I think what that starts. This. This goes to the topic of, like, what do jobs in the future look like? I think a lot of it stops being in front of the computer. I think a lot of it stops being in front of these monitors and keyboards. I think that we start to. I had a conversation with my grandfather shortly after he retired when my career started, and neither one of us understood each other. I was trying to understand what he did every day. He. You know, he worked in a world before computers were in the office, and I worked in a world where only everything was on the computer. And I couldn't understand how an executive at a large organization could possibly do their job if they didn't have a way to send out an email blast to be able to jump on a Zoom conference and chat with the whole team. And he couldn't understand how that worked at all and how you would interact, you know, how you could have human interactions with it. And I'm starting to really understand that now. And to say, like, it is about getting back to the human aspect of it. How do we motivate and inspire people to be the best version of themselves to accomplish the most that they can? And it doesn't happen well in front of a computer monitor. It happens in person. And so if our technology interface can become more like us, and I think chat's a step in that right direction, all of a sudden, we're free to go spend time with each other and to help each other out.
Interesting. Okay, I gotta follow up on this one. So you're. You're suggesting then, the future of work is maybe not. Like, probably me and you are right now, right? Like, I'm glued in front of my big two monitors every day, like, monitors follow me around like. Like, you know, the phone in my pocket, like, the wallet in my pocket. There's always monitors. So. So you're saying maybe the future of work is. Is. Is not glued to monitors?
No, it shouldn't be. I never. I mean, I don't think that we're. I think that it causes a lot of problems for our health, for our mental well being. I don't think we were meant to do this. And being freed to interact in a very human way in person. Collaboration and having the technology become almost background so that it's helping us. And we're not, you know, we're not just an extension of the technology, which is. I honestly think that's all we are today. Everybody listening to this is probably sitting at a computer and their job is probably sitting at a computer. That's not the best way to interface with the world around us. It's not the best way to accomplish anything. The technology requires it today. I don't think it does soon. I think that we're on the precipice. Wow, that was tough to say of that transformative moment when the technology becomes just. Just part of our world, not. Not the thing that we have to interact with.
Okay, so are we going full Iron man, then? Are we saying, like, maybe, maybe, maybe? I'm just like, very nervous, Christian, because I'm. I'm worried. I'm like, where are my monitors now?
Right?
Where am I seeing all my screens? So are you saying, like, more the future of work might be like wearables or you like, you know, like, oh, you know, Facebook or Meta, you know, has the. The Ray Ban glasses, you know, that have AI baked into them and, you know, in a display. And then you have the. Apple has their headset, which I don't know how that thing's gonna work when it's like $20,000, but is. So is that what you're saying? Are we talking more. Are we talking more wearables? Or is the future of work literally just two humans talking in a room and doing work? Because that sounds fun too.
The seamless interface between multiple different ways of interacting with the technology. So today I sit down, I'm like, Apple's actually not far away from this. When I sit down, if I have my iPad, my phone, or my laptop, I can share information between them. I can almost work between the different devices. This is very similar to the Jarvis view of he's got the helmet on and then he's sitting in his lab and he's creating something new. I don't think that that was far away from what we all desire is to have our data, our work, all that stuff come with us. And when we're in a place where all I have with me is an audio, something that can listen and say, oh, Christian said we should schedule a meeting for Tuesday. I'm going to look through his calend calendar. I'm going to connect up to Jordan's calendar. I'm going to find, you know, a time that works for both of us in the background seamlessly. I don't, I think that we're not far away from that type of reality and we already carry with us, all of us, I know, have a device with us that can listen to us. Now, I personally, I don't like it listening to me today, but I, but I think there's a, There's a trust issue there. I don't trust the providers to not, you know, sell my data to potentially a negative bad actor. But at the same time, I also don't trust the technology to do what I really want it to. If it was listening specifically to help me with things I want, I, you know, I do want it to listen and say, hey, Christian needs a meeting with Jordan, let's schedule it. But I don't want it to, like, listen to my conversation with my wife and make it, you know, and like, share that with the world. So it's often that desire and that need piece and then the protection of privacy and giving it the right levels of access to our world. And here's where I think we have a big gap. I think for that to work, you almost need your own AI agent that exists with you on your technology that can make that determination, that can say, oh, Christian actually would be okay with that because I gave it and understanding of that. And until we have that, my view of how the technology becomes seamless in the background still requires our input. We would still have to say, hey, turn on. Listen to me right now, because when I'm talking to this person, I need notes about the meeting, I need to, you know, follow up with a calendar invite, etc. Okay, good.
Like, so. So what I got out of this, which I'm extremely excited about, is I am going to turn into Iron man and just have my. Have my data follow me around everywhere. I've been waiting for this for a long time. So. So let's, let's actually peel it back, though, and get back to Enterprise AI, because Mike here has a great question. So, Mike, thanks for joining us. So Mike is asking Christian, how are the enterprise AI teams utilizing predictive AI? Because I think that that piece even goes to what we were kind of just talking about, right? Because if, you know, kind of, if the future, if our work is kind of following us everywhere we go on multiple devices, presumably it's going to know, right? Like, if me and you have A meeting, it's going to know what is required. So I guess how does predictive AI, specifically in enterprise teams come into play?
Well, most predictive AI today in the enterprise is not being used for that type of use case generally it's being used to do things like forward positioning of inventory so that when you do a I order something from Amazon, it shows up next day. Or it's used to determine your intent when you're clicking around on the web to show you what ad that you're going to see next. Right. That's typically where predictive systems are used today, where it starts to spill over into future world, where it starts to benefit us in more direct ways. And what companies are starting to look for is how do we. Somebody just wrote ambient Computing. I love that by the way, in the chat. That was a great statement. Where predictive systems are going to start to actually start to have impact in the very near future is more, I think, around. The company has its own KPIs that are usually put in place to track against how are we doing as a company. And the first place we're going to start to see it is most KPIs, most of the data that we're actually using to make decisions is lagging. And what we don't have is how does that look going into the future. And so some of the very basic things I've seen already are like sales figures, how are we doing, what do we need to do to improve, how do we need to, how are we tracking against our goals? And that's the first place we're starting to see it. You don't see a tremendous amount in a lot of the things that we're talking about right now because there's a large degree of distrust within the, especially in the very large enterprises around AI. And it's a combination of factors of like promises not kept in the past, like web3 was this huge thing. Everybody, everything's going to be crypto, everything is going to be edge compute, right? Like that didn't happen. And I think so. There's a, there's a standing amount of distrust that sits there. Plus we're all grappling with that same question of what does this mean for me individually, but also what does it mean for the organization? And there aren't a lot of great answers yet. So there's not a lot of predictive AI that's been implemented in anything outside of the traditional. I say traditional like this has been around forever, but in the places we've been traditionally using it for the last.
Decade, Christian, I think so many people probably listening are in the position where number one, like me when you talk about this, I'm like, this is awesome. I'm excited. I want this. Right? But I think there's a lot of people that work in enterprise companies and they're decision makers. They're, they're leaders in their department. So, you know, they may, they may not necessarily be able to make decisions on where the large company goes in terms of generative AI, but maybe they can help, you know, make policies or make recommendations on how to prepare. So as we look toward, you know, this, this future careers, how can we actually all prepare for them? You know, maybe if we can't make the final decision, how can we at least make sure that us, our coworkers, you know, when everyone else can prepare for, for these future careers?
I think it's true. No matter what, we're in a age of rapid change and the change itself is accelerating at a pace that's hard to keep up with. And so my old, My advice always is have a learning mindset. Look at what's, you know, look at what's happening and ask hard questions of yourself, like, don't take anything for granted on where you stand today. One, for example, one thing I've told a great many young people in my life, including my nephew, is there will always be software engineering jobs. There's always going to be more of them than more need than there is available people to do it. And I have to ask the question today, is that actually true? If all of a sudden the interface between the technology and ourselves isn't in code, it's in chat or something like that, is that still a true statement? So always be learning, always be asking questions. Scientific method is a wonderful thing that came out of the Renaissance, right? And it's been a huge power force. Apply it to everything. When you see a new technology come up, okay, what do I do today? How could I apply what I'm seeing to that? You. I can't give you specifics about any particular job because I don't know it. I don't know, you know, what you do today. I don't know what you do today. I don't know the specifics of your job. But I can say that if you look at the technologies as they come up and say, how would this benefit me? How would this make it easier for me to be successful? What you're also asking is, how is the company I work for going to apply this technology to what I'm doing. And if the, if the answer is it eliminates the need for me, then all you really were was an interface to the technology anyway. You were just translating from the company's needs to the technology's needs. And that means, you know, frankly, your, your role's at risk of this technology. But I don't think that's what usually happens. I think that we're all brought into a company for specific purpose. I'll use my wife's career as a great example. My wife's in environmental health and safety. She's been doing it for a very long time, has the Alphabet soup after name of all the certifications and degrees. Right. And her career is largely systems related because, you know, there's legislation around safety. So you've got policies written around legislation. So you create technology to enforce the policies. And then what does somebody in a large company do? Well, they manage the technology that enforces the policy that lets them meet the legislation that gives them the results they hope for. But it doesn't really do that because the desire is for the people not to get injured at work. It's for people to not lose their life because of a job. Right. That's why you're hired. But all you're doing is the technology. So if you get back to the how do we stop people from getting injured? And the technology just becomes background. It's just an enabling thing that I don't have to manage anymore. Great. And I think that's what's actually starting to happen. Will jobs disappear? There are certainly jobs that are going to be lost over it. I mean, the most obvious one to me is if autonomous driving ever actually happens. Truck drivers, forklift drivers, taxi drivers, like there are millions of careers that are just doing that. That type of job does disappear.
You know, one, one thing, Christian, in the beginning of that response there, you kind of talked about software engineering, which I'm fascinated by because it seems like, and I'm, I'm pretty sure you have a little background there as well. So it seems like there's a divide on that. Right, right. So either people are saying, oh, there's going to be way more software engineering jobs or on the very other side of the fence people are saying, oh those, those jobs are going to be gone. You know, look at, you know, GitHub, copilot and look at all these other, you know, great gen AI tools that can, you know, spit out code and you know, even self self heal or self improve self qa. Right. And then you have, I believe it was, you Know Google, Google CEO Sundar Pichai. I know I always get that name wrong. That said, software development and software engineering is, is going to become accessible to everyone. Is this maybe one of those things that maybe, maybe, just maybe careers are going to start to blend together and maybe, you know, you used to be in a very non technical role but now your role expands and you know you're doing some software engineering through the use of a, of a gen AI tool but maybe you're also kind of prompt engineering. Like are we going to see some blending where everyone, because of the accessibility and the lowered level of entry, where just about everyone is taking on some of these, these technical skills that maybe weren't part of their job description today or five years ago?
I, I, well yes, on both fronts. So my career's been about 30 years and at the beginning of it I would say that most companies needed a couple technologists, not soft necessarily software engineers, but they needed a couple. And over time that number's expanded to where almost every company needs. Any company having scale needs a lot of software engineers because they've got a custom automate or connect a bunch of different disparate systems. Most of those jobs though, if you look at how much time a software engineer at a large enterprise actually spends generating something new versus fixing broken old or you know, like dependency hell is something we're all familiar with. The average software engineer at a large Enterprise spends 17 hours per week doing nothing but dependency management. So now there are tools that are going to come along fix that. I'm currently working on one vol. AI is actually solving some of these problems. So hopefully the mundane minutia garbage jobs that a lot of us that have been in technology have been focused on can be handled for us. And a lot of the low hanging automation that a lot of the people that we serve in our businesses gets handled like think of like how many times you get asked to create a dashboard for a big data analytics system or somebody. I just think of my most recent role at tradelens and before that at Wayfair where we had large teams of people that were just managing containers of like ocean containers moving around the world, right. And how many times they just needed a different way of getting access to that data. And how many software engineers were spent, you know, hours and weeks doing that. I think a lot of that goes away. Does that diminish the number of software engineers that the large company needs? No, I most of them need 10 times, well a year ago needed 10 times as many as they had to really Catch up to where they wanted to be. So maybe now it's flattened out. Maybe now they can actually get to where they, where they wanted to be. Because some of this stuff gets lifted by the AI tools, enabling anybody to solve their own problems and some of the grunge work gets taken out of it for the software engineers that are in there, thus freeing up the nascent and the talent that they've already got there to go do valuable value creation. Valuable value creation. That was great. They could go actually start to do what they want to be doing too. I don't think anybody gets into software engineering and goes to school for all those years to sit down and worry about how dependencies interact and potentially break each other or to dig through old code and figure out what it's doing. I think they do it because they enjoy the value creation or the ability to create this. So it's a bit of both. I do think that there's a career still in software engineering, and I hope that it looks a lot more like why we got into it in the first place.
Yeah, and I, I do think, yeah, future. Yeah, I, I mean, Christian, you mentioned, yeah, there's definitely some jobs that AI is just going to negate the need for. But then I think there's, there's roles that maybe we think, oh yeah, this will be gone to AI and maybe it just changes completely. And, you know, that's, that's why I enjoyed having you on the show. And we've talked about so much right from, from what does the future look like? Are we going to have that Jarvis following us around to, you know, hardware, wearables, software engineering, you know, how we can automate things that maybe we don't want to do. So, so we've, we've talked about a lot here and I, I super appreciate your insights, but maybe what is that one takeaway that you want people to, to kind of have from this conversation as we look at future careers in the age of enterprise AI, what is that one takeaway point that, that, you know, can really help people be prepared for this and, and, and make the most of this in their careers and in their companies?
Yeah, I think that a lot of times we were presented by these changes, big or small, and we, we want to tackle it all at once. We want to try and say, like this profoundly changes everything and how am I going to adapt to it? And you don't have to do that. If every day you can make today a little bit better than yesterday, if every day you could do a little bit more. You can free yourself to be more creative if that's what you desire or you. You accomplish more. First of all, that means that every day is the best day of your life if it's a little bit better than the day before. Right. But second, it allows you to. You can eventually climb a mountain if you, if you plan each step and you take that step one at a time. We're at a moment where the dystopian future that can happen from AI or the utopian future that can happen from things like AI are both possible. And what eventually comes of it is going to come down to how we all respond to it. If we take a positive approach and look to solve the things that are painful and gross that we, you know, as humans, we don't really want to do, we get closer to that positive outcome. But if instead we look for what's in it solely for me, what is the, you know, how do I conquer the world with it? If that's what everybody's doing, then we end up in the opposite path. So the more of us that can be focused on positive outcomes, that can be trying to push in a good way to try to make the world a little bit better every day, even if it's just for us in a little way, the more likely we are to get that positive outcome. That's what I'd leave you with.
I love it. My gosh, I am so excited to sign up for Team Utopian Future. You got me excited there. So thank you, Christian. We really appreciate you sharing your insights on the future careers and enterprise AI. Thank you so much for joining the Everyday AI show.
Thank you so much for having me. Lovely experience as always. Jordan. Loved chatting with you. Great to be here.
All right. And hey, as a reminder, hey, you want to go sign up for Team Utopia with with me and Christian? Make sure to go to your everydayai.com Sign up for the free daily newsletter. We always recap and go into even more depth. You think this was depth? We're going to even dig in deeper. And we always send out not just what's happening in the world of AI news, but also breaking down our conversation each and every day, sharing with you more tips and more trends how we can be Team AI Utopia together. So thank you for joining us and hope to see you back on another episode of Everyday AI. Thanks, y'. All. And that's a wrap for today's edition of Everyday AI. Thanks for joining us. If you enjoyed this episode, please subscribe.
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