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AI RecruitingBest Practices

Getting the most out of AI Sourcing: Tips & tricks from TA pros

Melissa

Melissa Suzuno

HR Insights Writer

Posted on

December 9, 2024

It’s easy to get caught up in the excitement of AI tools. They promise to save time while cutting out the repetitive recruiting tasks that don’t bring us much joy or fulfillment. This is clearly a common opinion—according to Gartner, 76% of HR leaders are already using AI to stay competitive. But how do you separate the hype from the real areas of opportunity? In other words, how do you know you’re being strategic and not just jumping on the bandwagon?

Ani Sapru, Head of Product Marketing at Gem recently hosted a discussion between Rob Anderson, Head of Talent at Earnest and Michael Potteiger, Senior Customer Success Manager at Gem to address these questions. Their goal was to help you make sense of all the information that’s out there so you can make informed decisions about what’s best for you. As Rob put it, “I don’t think you should add AI in a particular area just because it’s what everyone else is doing. You should use it for what’s most important for you and your team.”

We’ll share a few highlights from their conversation here, or you can tune in to the on-demand webinar for even more insights.

What are the top use cases for AI in recruiting?

The most popular ways recruiters are currently using AI to save time are through candidate matching/ranking, candidate personalization, and automated candidate sourcing.

AI is helping recruiters work faster

Ani explained the differentiation between each of these terms:

  • Candidate matching refers to using AI to help you find the ideal candidate fit to your job requirements.

  • Candidate personalization broadly involves personalizing the entire process and can include recruitment marketing, having a chatbot that answers standard job seeker questions, or scheduling and sending personalized interview prep to candidates.

  • Candidate sourcing refers to surfacing candidates who meet the requirements for your open roles.

Rob is especially excited about the potential to personalize the candidate experience at scale. Here’s what he had to say about how this can work.

Michael shared how AI tools can help personalize outreach to candidates you’ve communicated with in the past.

Why does it make sense to use AI for sourcing?

We asked Gem customers to share why they’re setting their sights on AI sourcing specifically. Here’s what they told us:

  • Headcounts have noticeably shrunk for talent teams over the past few years, and they’re still being asked to do more work with fewer resources.

  • The cost of talent is growing but they’re on a much tighter budget, so they’re looking at how to reduce their spend on job boards, agencies, etc.

  • Generative AI has gotten really good, so it feels like there’s less hype and more actual results.

Elaborating on this point, Rob said, “I don’t think it’s just that we’re being asked to do more with less—it’s that we actually can do more with less. And that’s very important for TA leaders to think about how to continually evolve your team.” Rob recommends looking at areas where your team tends to spend a lot of time or activities that “grind your gears”—like sourcing—and considering how you might lean on AI to help.

Michael added that one of the benefits of AI technology is that it allows you to use natural language in a way that saves time and effort. Rather than relying on keywords or Boolean strings, you can frame your requests more simply and still target people from specific industries with your desired qualifications.

Best practices for AI sourcing from the TA pros

When you’re just getting started with AI sourcing, it can be a little overwhelming to know how to start. Ani shared a few overall best practices, including being as specific as possible, keeping it concise, and trying to remove anything subjective from your list of qualifications.

How to get better results with your AI sourcing bot

“Where it becomes most beneficial is when you start to put it in practice. Treat this as you would any other search. Maybe come up with a defining metric of what success would look like to you—like the number of results that come back—and just continue to iterate. You can have your inputs or what you want to do, but you won’t actually learn until you see it in real-time.”– Rob Anderson, Head of Talent, Earnest

Michael shared one specific example from his own work with Gem customers. Here’s how he broke it down.

Take a page from the panelists’ playbook and try experimenting with different tactics. Just be aware that you will likely need to continue iterating a few times until you end up with the most effective prompts.

Get even more tips and tricks from Rob and Michael in the full webinar, which is available on-demand here. Or if you’d like to see how Gem’s AI Sourcing tools can save time and boost efficiency for your team, get in touch with our sales team to schedule a demo.

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