People-First AI || Season 1 Episode 10

How should staffing and recruiting firms use artificial intelligence (AI) to prioritize human relationships and drive productivity and efficiency? 

In this episode, the team explores how people-first AI is revolutionizing the staffing and recruiting industry by enhancing human connections while automating mundane tasks.

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Transcript

Andy Weiss (00:00.964)
Greetings friends and welcome to Now Hiring!, our podcast about trends in staffing, recruiting and talent. I'm Andy Weiss, CMO of Ceipal and I'm joined as always by Ceipal's founder and CEO, Sameer Panakalapati. 

In this episode, we're going to dive into AI. Yes, we're checking the AI box, but I've been spending more time playing around with AI tools in the marketing and content creation and data space. 

I know Sameer, you've been playing around with and exploring some things across a wide spectrum of areas. And curious, kind of as you spend more time with these LLM models and tools kind of evolving, what's your current kind of feeling of the efficiency and capabilities of what we have at our disposal today?

Sameer Penakalapati (00:49.088)
Yeah, look, AI has been at least talking about it, exploring about AI adoption into specific to the staffing, talent acquisition, talent automation industry. It's been for five, six years now, right? But then last one, two years, the whole game has changed now, because especially when the GPT came into force and then Google Gemini got into. Now these models have trained with large volume of data. They're trying at different segments and sectors and categories and stuff. They're very powerful today, right? So that elevated the whole game of AI and building platforms around on those LLM platforms, right?

So now we are seeing you're not just making an incremental up on the AI enhancements. Now we are seeing the complete game changer on and bringing some of these new capabilities and new tools built around these long platforms.

Andy Weiss (02:00.418)
Is it, you said game changing, is the expectation that these are still gonna be game changing type advancements or we're seeing like this week, Apple rolled out its new iPhones and talking more about Apple intelligence. I know Microsoft is rolling out copilot and a lot of it's Microsoft Office applications. Google's doing the same thing with Gemini.

Is it becoming more mainstream or is the expectation that this is going to be truly game changing in this bright, shiny object?

Sameer Penakalapati (02:36.994)
No, I think it is real and the capabilities of the existing AI platforms built on applications built on those large language models as real. So it's not like some kind of a fancy, no, this is real. I mean, I think you want to see a lot more. It always reminds me that in 2010, 2012, that time,

you know, a lot of people were building apps on iOS and Android platforms, right? And every app was, people used to think that building a tech company is really an app, right? So you're actually seeing a lot more of a very similar situation that a lot of the people are building apps on LLMs, really, right? These are apps on LLMs. And some of these apps are very powerful, but based on these LLM platforms. So...

So I think there a lot of things that would change. Some of them get disrupted completely because it becomes irrelevant. Now given these new capabilities of these LLMs and apps built on LLMs, but some of them new apps comes into it that would enhance what is existing today. But really, you think about it, I just want to say it, if you're an enterprise platform, like Ceipal, like you have a...

workdays, safety success factors, all these big, large enterprise systems that does do a stream of things from end to end, right? Then you would enhance these enterprise platforms with the building in the AI apps on top of that. It's a huge advantage for the users and the customers who have these platforms because...

they can really appropriately enhance their automation and their intelligence in the dashboards tremendously. That's not incremental, it's just a leap and bounce of change now.

Andy Weiss (04:39.46)
because it's constantly learning on what you're doing.

Sameer Penakalapati (04:43.872)
Yeah, exactly. And also that the power of these trained models that intelligence that produce, it's not incremental. They're already training. these LLMs were funded tens of billions of dollars. And then these platforms are very powerful. And no one single company can build LLMs and train models with such a volume of data. It's almost impossible to do it.

It's not impossible technically, but financially.

Andy Weiss (05:14.2)
So I'm not going to go out to my garage and build an LLM.

Sameer Penakalapati (05:19.316)
Yeah, because look, think that you could build a model. Anybody can do it programmatically, you can build a model. But I think the model is only as good as you have trained the model with the large amount of data and with large amount of use case scenarios. If you don't have those data and the use case scenarios defined and trained them, it's not much useful. There's not much helpful.

These are become very popular because they're trained with throws of data and models and the throws of data and the use case scenarios that that's where it is today. So it's tough to do that today.

Andy Weiss (06:02.633)
Yeah, so we got really deep into kind of some technical stuff. I want to kind of zoom back out a little bit to, know, from the perspective of, you know, talent and staffing and recruiting as I'm kind of thinking about, AI, you know, I joked at the beginning of this episode, you know, we're checking the box off from a podcast standpoint, but, you know, as a staffing firm, you know, I should

everyone's telling me I should probably be thinking about AI as well. Like where do I start or how do I know how to apply it? Like what's the best place? Where does AI fit or where should it fit? How should I be thinking about this, Samir?

Sameer Penakalapati (06:45.006)
If you're a staffing forum, the first point is you are sourcing talent to your customers. How efficiently are you doing sourcing today? Now the sourcing has been tremendously up their game in terms of with AI automations. You are finding candidates. You are integrating your...

finding a top match of the candidates, and you ranking the candidates based on your various number of skills. So you can almost infinite combinations you can find, and then you can find those a good set of candidates, you you're looking for first top, first 10, first 20, whatever the set of candidates. And then you could really spend your time, your recruiter's time to really look into these candidates and actually spend a meaningful time connecting with those candidates.

and understand their needs are and then understand your client needs are and can actually map it. But all the background stuff that needs to be, that can be automated and you can compress the time, let's you like, know, and 90 % of the time compressed, then you have a lot more time, you really humanly gauge the talent. And then, you know, by doing that, you also build your reputation, your brand, your recognition, you are bringing because...

See, a lot of people have this perception that AI will become inhuman, will be less human touch. Actually, my argument here is, hey, you do some of this stuff that you compress your time to, you know, compress 90 % of the time, then you could keep more time and engage the candidates and actually build more human touch than less human touch.

Andy Weiss (08:31.728)
So I want to double click on that because I think that's an important point that you're an insightful point that you're making that, know, we're not. This could very easily turn into like this Stanley Kubrick 2001 Space Odyssey, Hal 9000 kind of world. But your argument is, hey, that's not that's not the ideal application. Like, especially in this space where it's a human business that AI can free you up.

to focus on the human pieces and use the technology to do the mundane routine stuff and you invest in the relationships and building value in your business. And that may be a way to use the technology and AI to be a differentiator for you. Is that fair?

Sameer Penakalapati (09:21.41)
Absolutely, you would, at end of the day, you would reduce the number of touch points with the prospective candidates for things that's not very important, like asking some basic questions about qualifications, exchanging calls between the two candidates, and trying to spend your time and browsing through candidates that's not a good fit, or you just keep searching for different set of candidates are different sources of the talent that's bringing into the organization. 

All of their stuff can be automated now, right? But then you would actually spend time with the candidates, understanding their needs are. And if you are the staffing firm, can able to tighten up your talent automation systems and give your recruiters more time with the candidates, because now the candidate that's spent with your recruiter has a better experience because the recruiter not only spending time, but they also have more knowledge about the candidates because you got the summary of the candidates, match, the candidate skills, skills map to the job description. 

So there is some meaningful points that why candidates should consider working with your firm. All of those things really enhance it. It's a time. That's how the staffing firms can differentiate themselves and get more business.


Sameer Penakalapati (10:46.016)
and create more value to their customers than just operating like anybody else.

Andy Weiss (10:50.97)
So should I be going, as I'm thinking about this, like if I'm running a firm, should I be going all in on like trying everything or should I be like testing different things, like leaning into it, like playing around with it? what's the kind of the right roadmap in terms of getting adoption? Because it's one thing if you make the decision that, as an organization, we're gonna use this tool or this approach.

But then how do you, you you got to get adoption within the organization. And there's just a lot of, there's a lot of change management that comes as part of this.

Sameer Penakalapati (11:29.44)
Yeah, no, it's like I give you an analogy, like a kid walking into the candy store. There's so much of it. It's like that. There's so many tools out there in the market. Focus on what candy you want or like what's the most you, your organization benefit from this, right? But I think it's important that it's not that, you know, the account manager, it's not that with the back office, front office managers really looking forward. It's a buy -in from the CEO to the line managers.

Sameer Penakalapati (11:58.1)
Everybody should get into it and then sit down and find what's our business priorities. What platforms out there that would create a best value for our business. And that's how you should start from there. The commitment from the top down is a key. If they don't have commitment, then you are like walking a kid to the candy store.

Andy Weiss (12:21.786)
So, okay, so we've got the how to not turn AI into a sugar-induced kind of stomach ache. I love it, I love it. let's say you're kind of a middle manager in one of these firms. How would you go about selling AI into senior leadership or the head of your organization kind of?

you know, getting some adoption there.

Sameer Penakalapati (12:53.046)
It's a good old business, Andy, really, right? It's not about, okay, I have this great feature. People want to hear, okay, how this helps to get more business, how it helps to get more clients, how I can do more placements, how I can build a better pipeline. You pick these three, four, the major objectives of the organization, because all of them helps to grow the business.

Then you map whatever you're planning on introducing to the organization to map where this problem, this tool, this system helps in this four or five identified business objectives. And then bring this, by doing this, we can create a 30 % more pipeline with the same money we're already spending on job portals or third party sourcing portals. 

And said, we could create more submissions to this customer in this quickly because this platform gives a better recommendation, have a better matches or a better communication channels. So as long as you, got to do this mapping, when them do the mapping and go to the CEO or the president of the forum or whoever the nation maker in the organization, right? they get it once they get it and you get the buy -in and so you map it.

Andy Weiss (14:10.638)
Yeah. Okay. we're building things out in terms of showing results. We're avoiding stomach aches. We're using the AI and technology to keep this business human at its core. So Sameer, we've covered a lot of ground in this episode. 

So everyone be sure and check out our other Now Hiring episodes on Spotify and YouTube. Also sign up for our newsletter and we invite you to extend the conversation on our new Slack channel. And until next time, we'll see you later. Thank you.