Alright. Welcome, everybody. My name is Julie Schmidt. I'm head of content for, Speakeasy Strategies based in San Francisco, and I am a former editor and reporter with, USA Today.Welcome to our Fireside Chat today, human plus AI wins. I'd like to introduce Courtney Maki, vice president of product and engineering at Andela. And Andela supplies top tier tech talent to companies around the world. Courtney, we've spoken before, and I know that you see AI as a complement to human abilities and not just a threat to jobs. Let's start this chat off by talking about how you see that unfolding today in your industry and others.

Thanks, Julie. That's a great question to kick off with. Yes. So I I definitely see AI already as a complement to human abilities, and I believe, that will continue as well. And I think the first kind of big area that we're all seeing and hearing about all the time, that's really been impacted is software development. Right? And so engineering, building products. And that, you know, obviously affects the talent. And, Ella, my company, works with daily. So been been definitely paying a lot of attention to this. And the thing that we're seeing, which I think everybody is too, is that AI is a huge productivity lever.

So because it makes people more productive, it helps to drive down the cost of building software. And so I think because of that, there will be kind of a proliferation of new problems to solve. Right? It's it's gonna generate some new jobs. And we're already seeing that, quite a bit of that, actually. And so there are net new job categories that just didn't exist even years ago, that we're seeing a lot of rules come in for now. So examples being, like, prompt engineers and LLM researchers. Those are some of kind of the more technical things. But we also are seeing an uptick in demand for, like, AI change managers, for example, or, gen AI consultants.

And I think that's because a lot of companies, they they hear about these wins and they hear about ROI, and they know that AI is a lever that they should be pulling more often. And they have outcomes they wanna drive and they have problems they wanna solve, but they're not a 100% sure how to apply AI to their road maps in order to get there. And so they're looking for folks with experience who can come in and help with that. So a lot of new jobs. We're also seeing a trend in an increase for more senior level engineers and senior level talent. And I think some of what's driving that is the fact that if you're more senior in your career, you've probably had experience managing more junior folks, mentoring folks, kind of orchestrating work. And that's a lot of kind of what you're doing when you're using AI. You're orchestrating agents.

You're managing kind of different threads that different AIs are are solving for kinda helping you solve for. And so people are looking increasingly for folks with more experience and also with more kind of foundational knowledge of things because, as we know, AI is not a 100% bulletproof right now. We need to bug it a lot. So another big trend there, and I think it's also worth noting that while, you know, we are seeing more jobs being created, AI is taking jobs too. Right? We know that. Entry level jobs, I think, make up right now about 18% of all job postings, versus something like 35% a couple years ago. So we are seeing that trend, and that's I think goes back to the fact that AI helps to eliminate a lot of this, like, mundane task, these jobs that are more focused on kind of the mundane, repeatable tasks.

And so what I always say and what I increasingly believe is that AI is not gonna take your job, but somebody who can use AI really well might. So I think it's the responsibility of all of us to figure out how to use it for our specific rules, how it can kind of 10 x our workflows. This should be a big focus for everybody now and and moving forward. So net net, some jobs will disappear. Some jobs will evolve and change, but we will ultimately have more jobs and I think more productive workers, which is a win.

Yeah. Thank you, Courtney. That is really the full circle. As you mentioned, as, it's exciting to think of all of the problems that software could help solve that have just been too expensive. And if AI can can increase that, there's all kinds of things that where humans will really benefit by, better, smarter, faster software. And, so you're kind of on the front lines now watching companies try to, deploy AI, experiment, etcetera. What are we seeing right now in terms of them getting a good ROI, or are we still in the in the experimental phase?

Yeah. I I think it's it's a mix. So you hear, again, a lot about the success stories. Right? I just saw yesterday, Klarna reported that they now get a million dollars in revenue per employee, thanks to gains in productivity from implementing AI. And they've been in the news a lot, you know, talking about their AI usage. General Mills, I saw a couple weeks ago, says they saved 20,000,000, in supply chain by implementing AI to become more more efficient. And so you do hear a lot of stories about the ROI, and, they're out there, and I I see it too. But it's a it's a spectrum. Right? It's a mixed landscape. Some companies are a little bit more slow to adopt, typically enterprises. Right?

But, certainly, we're shifting kind of out of the speculation phase and into the adoption phase. The question is definitely no longer, should we do it? It's, how do we do it effectively? And I mean, with any new technology and when you're kinda trying to figure out how to where it fits, you have to experiment a lot. And so we hear a lot about the the positive ROI and the successes. We don't hear as much about the failures. And I think you're gonna be failing a lot too, or else you're not really trying enough. Mhmm.

And what about, what about productivity in core product development in terms of, you know, like, productivity tools that, you know, Endela's focused on? Do are people sort of feeling like they have superpowers and unlocking strategic focus? Or it's you know?

Yes. I've I've I've actually had, folks on my team comment to me that they feel like they have special powers now with the amount of, productivity and time they've been able to unlock, by leveraging AI. And and so I think, again, that is kind of the most obvious use case and the most obvious application for AI at the moment. We use, you know, we use WinSurf internally. We use code completion tools and, a lot of other tools. And, those that software will give you kind of estimates for hours saved coding based on, you know, the value that they provide. And so we do see that people are able to get prototypes out more quickly.

We see that we're able to get to kind of ideation more easily because of some of the prototyping tools that we're using. And so, generally, yes, I'm seeing that people are able to collaborate, more quickly and that things are getting done faster.

Great. Thank you. So, I know you mentioned that companies are are different phases of their, deployment with AI. If if a company wants to start integrating today AI today in a way that supports their workforce, which is really, you know, the where where Endela plays. What's the first thing they should do?

I hear a lot of folks saying, oh, we need an AI strategy. We need a strategy. And, I think it's funny. You know, AI shouldn't just be the solution that's looking for a problem. Like, it's a new technology. It's a big shift. But you do the same thing that you're always always doing is you start with the problem that you're trying to solve. Right? So define the problems that you wanna solve, the outcomes that you're looking to drive, and then you kinda work backwards to figure out how AI fits in from there. And the way you do that so what we've done at Andela and, you know, what I've seen working in other companies is you really have to focus on first having some AI literacy inside of the company. And so, like, when you take any group of humans, you're going to have a small subset of that group who identify as early adopters.

And those are the people who always try technology first. They're not afraid to take risks. Those are the pioneers. And so you wanna find and identify those people in your company, because they're probably already working with AI. They probably know a lot more about it than you do. Enable them to kind of lead the charge here. It's it almost starts as, like, a grassroots movement, and it requires you to take a really experimental mindset. So get this group together, have them start trying things. Be okay with failing fast, right, and kind of get that machine going. And once you do that, it's a lot of trial and error, you will start to kind of find some sweet spots. Those folks will start to share their knowledge, share their wins, share their failures throughout the organization.

Other people will start to kind of join the movement, if you will, and you can start to build repeatable processes from there. And so I think that's a really important step. It works well for a lot of folks or it has worked well in a lot of companies. Mhmm. The bigger thing here, though, is this is it's not just a small new technology that's going to affect your engineering team. AI is you know, usage of AI inside of a company is a cultural shift, and it impacts every single department. It's not just the tech department. And so I think companies do need to be talking about it. They need to communicate clearly about what their position is on AI. There's kind of a change management exercise to be done. Right? Once you kind of you started to experiment, you found that repeatable process, then it's like, okay.

Well, how does this affect the broader company? What stance are we taking? What policies do we want to roll out? So I think that's also a really important step.

Yeah. Thank you for all of that, Courtney. Let's go back to something you said earlier a little bit. You talked about how AI may or may not take someone's job, but someone who knows how to a how to use AI may be a bigger risk for a lot of workers. So, from your vantage point, at Andela, how do you see AI being used as a tool for, well, hiring, but also upskilling? And, what are the benefits of this expanded role of AI in these realms?

Yeah. There's so much potential in this area, and this is an area that I'm really passionate about, so I'll try to keep it short. But I think there's so many different applications of AI, when it comes to hiring processes. There's also a lot of noise being introduced. I'll I'll start with that. Everyone's probably heard the story of, oh, I posted a job, you know, two days ago, and I got a thousand applications, and 85% of those were just garbage from, you know, AI bots. And so it is AI, you know, as much as it will supplement and help us make progress, it will also introduce quite a bit of noise. And going back to the topic of jobs being created, people are going to have to figure out how to solve for those problems. It's gonna create a lot of issues too.

But when it comes to applying AI in the in the hiring process, there's, you know, obvious things that you can do to automate, some of the the more mundane tasks in hiring, like sending sourcing requests, certain tasks around interviewing. But I think one of the most interesting potential usages for AI is when you're thinking about how to actually evaluate and understand human potential. And so when you think about a hiring process, what a recruiter is actually doing and what a panel of interviewer or interviewers are actually doing is trying to really deeply define, you know, what the company needs, what the role is about, who's gonna be successful in that role.

So So a really good understanding of the job, basically, the opportunity, and then a really well rounded understanding of the individual. And that's super hard. It's not just about understanding, you know, can this person write Java code and can they do it well? But there are so many other things that you have to try and get a handle on. Like, what is this person's work style like? What are their ultimate career aspirations? What kind of environment will they fit into? What is their life like to an extent? And is that gonna fit with the company's culture? Really hard problems to solve. Human matchmaking is difficult. And so, when you think about that process, there are a lot of different people involved. Everybody kind of has a different perception of what good is. People have biases.

People are different from day to day. You know, you wake up one day and you're in you're not in a great mood for whatever route you slept wrong and your neck hurts. I don't know. But we can leverage AI to collect a lot of that type of data for us. And AI is not gonna wake up with her neck. AI is going to be pretty consistent throughout the entire process. Hopefully, going to be unbiased. Right? AI can actually get you a very well rounded picture of a person through data that you can then use to make decisions in a hiring process. And we we haven't had anything like that before in the past.

And so I think we can if we can solve that, we can leverage AI to solve that problem really well. That's gonna be a game changer for hiring. It's just gonna simplify so many things and, you know, reduce the risk in making a hiring a wrong hiring decision. And I'm really excited about that. I think with upskilling too, you can imagine once you have enough information about an individual, what they're trying to achieve in their career, where there might be gaps, you know, that they perceive or gaps that they have uncovered in different hiring processes, you can much more easily think about how to build a career road map, using AI that is actually that is actionable, that you can then take steps to actually fill some of the gaps that you've perceived or that you've been, you know, communicated about.

And so that, again, is something that we just haven't had in the past, and I think it has potential to really, accelerate things in the hiring space.

Yeah. Thank you. Thank you, Courtney. I know we, we we talked before about how, you know, people need to pick up the tools if they haven't, and, curiosity is key. We are, just a couple minutes, left of our session, like, two, actually. So why don't we just gonna go back to big picture for a second and just speak, briefly about what what excites you most, from your vantage point at Andela, intersecting with companies and tech talent around the world, about the intersection of AI and the workforce in the next decade?

Well, I think I'm certainly very excited about the, the potential for AI to enable folks to finally focus on things that they really like to do and that they they care about most. Going back to kind of the automation of mundane tasks. And if you think about, a specific example, like, being a product manager, you do type you tend to do a lot of discovery work, and so that might mean customer research, market research, UX research, whatever it might be. PMs love doing that work typically because you're you're talking to folks, you're uncovering problems. It's really great insight. But it's really right now, it's, like, very paperwork heavy. Like, you might spend 50% of your time just, you know, taking notes and then aggregating your notes and then trying to figure out what kind of themes are surfacing and then, you know, presenting that information back and then prioritize. Like, it's a lot of paperwork.

And with AI, I mean, we're already seeing tools come out that, help to automate a lot of that and do a lot of that work for you. So you can take that 50% of time and spend it actually talking to customers versus doing the paperwork. And that's a huge unlock for a PM. Like, that increases the amount of time you get to do things that you like doing. And so I'm really excited about that. I think there's a mill there's, you know, so many examples that you could pull and so many things that we haven't even thought of yet, that we'll start to see unlock over the next couple years. And then, like I said, I am really, really excited about the hiring space, the potential to make hiring easier. I think it's good that, you know, there there seems to be more of a focus now with AI, and, like, AI helping us to become more productive coders or pre PMs.

There's more of a focus now on soft skills in in hiring and in in jobs, as a whole. We're seeing that in Della. And, I think AI, like I was saying, has the potential to help kinda bring that out, bring that to the forefront, help people improve their soft skills so they can differentiate themselves in hiring processes with their soft skills, which is really exciting. And, you know, if hiring gets easier, if if we are able to solve that problem, then the kind of reach of opportunities expands as well. And that's what we're really focused on in Adela. Right? We work with companies and talent worldwide, and we see a global remote workforce as the future. If we can increase opportunities for everyone, you know, using AI, that's a huge win, and that's what we're very focused on.