How learning skills in artificial intelligence can help you gain the edge over others in the job market.

<div class="block">In order to stay competitive in the job market, adapting to constant changes is paramount. Jordan Marlatt, lead tech industry analyst at Morning Consult, joined &#39;Stretching Your Dollar&#39; to talk about how learning skills in artificial intelligence can help gain an edge over the very crowded field in the hunt for a new job.</div>

Stretching Your Dollar

Stretching Your Dollar: How Developing A.I. Skills Can Make You A Standout in the Job Market

All right. Well, artificial intelligence is predicted to transform the nature of work in the coming years, eliminating some jobs, creating new ones and completely remaking millions of others. According to the World Economic Forum, almost a quarter of all jobs worldwide to change in just the next five years. While some employers like counting giant Pricewaterhouse Coopers, they're already using A I training for their workers. And if you want to compete in the job market of the future, knowing how to use A I could give you the upper hand no matter what industry you're in. So for more on how to get skills that are in demand, I'm joined by Jordan Marlo, lead tech industry analyst at Morning Consult Jordan. I know your company morning just released a new report on how workers roles are changing. What did it find? Yes, thanks. Uh And thank you for having me here. Um So we found a lot of, uh you know, very uh very interesting points in this recent survey that we conducted among tech workers in the United States. Um There's also some other surveys that we've been doing around the topic of, of A I different applications uh within different industries and how it's bound to change those people's trust in A I. Um like you mentioned as well. And among tech workers, what we're seeing is a lot of excitement around A I and it has to do with uh two factors. One is where to work. So a lot of tech workers are very interested in working in A I applications um which was very interesting because it's such an emerging field right now and it's not quote unquote like a legacy tech field yet because it's, it's it's new in a sense, the general A I aspect. And so to see so many tech workers who are excited to work in this field was very interesting to us. Um And the other is tech workers are looking forward to using A I tools in their jobs. And that makes sense because a lot of the tools that are available to people um to use or are being rolled out and quickly iterated on have to do with work has to do with also some more technical skills that are required like software development, you know, coding, things like that. So we talked about a lot of that technology there, obviously maybe no surprise that those in the technology field are open and willing and even adopting it in certain cases, what other industries are leading the way when it comes to A I adoption. Yeah, great question. So I just a few uh you know, to start off is um looking at, you know, finance, retail, uh media and entertainment. Uh one that I think is particularly interesting to keep an eye on is health care. Um And so, you know, thinking about uh health care as a potentially exciting area where generative A I applications are taking place, um potentially to help personalize care, identify trends based off of people's uh unique medical histories of these advanced models are already being used to help identify things like um genetic markers or genetic mutations. Um The other side to that though is that there's almost nothing more personal than your health and your medical data. Um And we're not seeing a lot of comfort right now in our recent surveys with uh different applications of generative A I within health care. Um And a lot of people, uh 70% of us adults say they have concerns with those types of applications in this setting. So there's, we see pretty consistently is this tension of A I is something that's exciting, it's the future, but maybe we're not ready yet. So I know you mentioned there are obviously some of the very advanced use cases right in certain fields like medicine technology, obviously, where this is being deployed, are there certain just, you know, kind of basic functions that A I is being used to perform maybe at more commonplace jobs out there? Totally. Um I I see gen of A I um similar to online search in a way when we're thinking about people's skills in the workplace where 20 years ago, maybe the expectation was not that you were fantastic at searching for things online and finding answers and things like that. Um Increasingly, I think generative a is uh in, in interacting with these models, uh people solving problems using them finding answers is going to become an expectation um for office workers um as these models become more advanced. And so, you know, in your everyday job, you don't have to be, you know, like this very uh advanced degree technical worker and everything, but um to help write memos, write emails. Um and these skills, uh I think can certainly be self taught. Um I think it's exciting that companies are looking at how to train employees with this too because you have to have the right prompts, you have the right to have the right queries. Um and also know how to course correct the models because sometimes they don't always give you the right answer and knowing when you don't have the right answer and correcting along that path is gonna be an important skill. So talk to me about a use case um Jordan if you can as to a company using this to train their workforce in a way that it can be used actually for good. Sure. Um So uh I, I think uh I think about software developers um for this because that is definitely one area where a lot of focus is being put in tools that are being rolled out. Um Microsoft for example, um is has already announced uh pricing models for uh its co-pilot um tools which uh are um uh available for developers and people who are born in that coding practice, but also everyday office workers because it's plugging into the 3 65 suite. Um And so, so having these be very formally rolled out um as part of existing suites that people are using their everyday job, you know, that uh that provides its own training and of itself because it's tied to these tools that people are in software, people are already using every single day. Um But it's also uh these tools also have the potential to really increase people's productivity um if used correctly. And so that's obviously very enticing for companies. I think it's enticing for a lot of employees too. Um because is that they can remain competitive um in, you know, what is still a competitive job market, especially for tech workers. Um And so, you know, we're seeing a lot of companies who uh are looking at uh how do we roll out these models in a way that is uh uniform but also reliable because we're not even at version 1.0 alternative A I right now, there's still a lot of, you know, issues to work out, especially around reliability um of the answers that are provided. So um adaptability is gonna be key interesting. That's a big takeaway too, right? Not even at the iteration of 1.0. And you're right, a lot of errors there are, I think, very easy to kind of detect in some cases to what has actually been used A I four to actually generate there. So Jordan, we appreciate your time. Jordan is a tech analyst at morning.