Kasey LynchMay 11, 2023
Topics: HR Experience

HR’s Newest Jedi: Generative AI

May the force of generative AI be with you, not against you.

In a special May the 4th episode of Talent Experience Live, Phenom’s John Harrington, Director of Product Marketing, and host Devin Foster explored the capabilities of generative AI, from writing relevant job descriptions to supercharging the interview experience and other revolutionary use cases. 

This one’s a must-see for Star Wars fans — and anyone who wants to find out how generative AI can assist rather than replace talent teams! 

View the episode below, or keep reading for highlights.

How is generative AI impacting HR already?

For anyone who needs to catch up on the nuances, here’s the rundown: traditional AI is based on a set of rules that analyzes data to help solve problems or provide recommendations to aid in decision-making. Generative AI, on the other hand, is capable of statistical learning and pattern recognition that enable the creation of new content — images, video, text, works of art, music, and other outputs. 

Although generative AI is still in its early stages, the technology is already changing the way people approach work in a variety of industries. Employees are using generative AI in their personal lives, and bringing those uses to work. 

Generative AI tools hold a lot of promise for HR and talent teams in terms of enhancing efficiency, productivity, and decision-making. In fact, Phenom just introduced Phenom Experience+ (X+), our new platform-wide generative AI capability that accelerates efficiencies and automation to help talent teams work smarter and faster.

Generative AI also spawns implications related to policy, compliance, and governance. Organizations are challenged with embracing all the benefits generative AI has to offer — but proceeding with caution, ensuring it’s used ethically and transparently. 

“In the spirit of trying to create great experiences and trying to make sure that you’re meeting people where they are, there has to be an objective to understand the implications of generative AI,” Harrington said. “There’s a lot of excitement around it right now.”

What are some strategic uses for generative AI? 

Generative AI is complementary in nature. With its data analysis capabilities, it can be trained on the specific context of an organization’s talent landscape, identifying potential staffing deficits, skills gaps, and opportunities to upskill, for example. The system gives a heads-up on these forthcoming issues so that team leaders can make proactive decisions and set priorities to align with upcoming needs.

“And it does this dynamically, without any sort of manual effort of time-consuming processes. It’s truly going to be that sidekick in the cockpit that can help you do your job more effectively,” Harrington said.    

What’s an example of a practical HR use case for generative AI? 

When thinking about applying generative AI to recruiter and TA functions, it’s key to remember that the technology should augment the work you do — not be trusted to do the work for you. “It’s all about making sure that you’re using it to further your objectives, but you’re actually making the final decision. You’re allowing it to influence your behavior, but not outsourcing your behavior to it,” Harrington emphasized.

An important outcome of using generative AI should be that TA and HR team members have more time to spend with people — to focus on conversations and interactions that will help them determine whether that person will be a good fit. “Let the AI take care of the aspects of your job that are time-consuming, that are manual, that take you away from that human connection,” Harrington said.

Use Case: The Job Interview

Putting generative AI to work during job interviews is one of the technology’s most promising capabilities, Harrington said. Think about what happens during a job interview: It’s a fast 30 to 40 minutes — and a lot of effort for the hiring team is spent on note-taking and documenting responses.

Enter generative AI. The technology can instantly capture the conversation in real-time, document candidate responses, and then interpret nuances and produce recommendations on key themes, the quality of responses, and next steps for that candidate.  

Meanwhile, with the manual lift of note-taking out of the way, interviewers can better immerse themselves in the conversation with the candidate, getting a better sense of whether the person will be a good fit. 

Generative AI helps get the hiring team up to speed quickly post-interview. It can quickly surface key aspects that should be addressed in the next round of interviews — the boxes that need to be checked — letting interviewers focus on the more intricate details of selection. 

How has generative AI evolved?

Since its earliest stages, the intention of AI has been to improve human efficiency and productivity. Across many industries (including HR), it’s been adopted to help teams save time so they can focus on strategic efforts.

Generative AI builds on those capabilities, taking in context and providing on-the-fly recommendations. “It’s going from being an informer … to something that can actually co-create and develop things by your side that allow you to take action quicker,” Harrington said. 

Developing job descriptions is a good example of how generative AI has evolved into a co-creator. The technology can be applied to analyze relevant information — things like:

  • Recruiter and hiring manager input

  • Skills and experience requirements

  • Candidates who have been a good fit in the past (and those who have not)

  • Top-performing employees already in the role

  • How the job role fits in with team and organizational goals

Generative AI can quickly analyze this type of data and surface a job description that reflects relevant detail. The end product will need a human to ensure accuracy and quality, but the bones will be there. 

Generative AI acts like a virtual assistant. It can run in the background, soaking up information on your work habits and tasks, and then automatically generate reminders to keep you on track. 

How do organizations need to prepare for adopting generative AI?

“The reality is, [generative AI] is here. It’s part of how work is being done,” Harrington said. The benefits of the technology are too advantageous to shy away from — but to fully leverage those benefits in the most ethical way possible, leaders need to understand its uses and implications. 

Related: ChatGPT: The Must-Have AI Tool for HR Companies

One of the most critical ways to ensure successful implementation, adoption, and usage is to proceed with caution when selecting a vendor. When vetting a generative AI tech vendor, organizations should look at:

  • The vendor’s approach to AI and how they deliver it 

  • Whether the vendor has a long-standing history with the technology

  • If the vendor can serve as a partner in meeting objectives and staying compliant

For example, Phenom takes a layered approach to generative AI. The technology is built on a foundational model that accounts for large language models (e.g., ChatGPT and others). Layered on top of that model is a specialized language model that provides HR context on the job roles you typically hire for, and industry-and geography-specific considerations. And then, on top of that, is another layer with organization-specific context. 

“When you have that context-oriented approach to generative AI, you’re really laser focusing everything it’s creating, and creating a great experience because it’s bringing the most relevant details to the stakeholder who needs to know the information, whether it’s an HR practitioner or a candidate,” Harrington said. 

What role does a “human in the loop” play in generative AI?

With any sort of AI, machine learning, or automation technology, keeping a “human in the loop” is crucial to realizing maximum value. This concept refers to the need for people to actively be involved in reviewing the accuracy and quality of system output and functioning as the ultimate decision-makers when it comes to taking action on recommendations. 

Take candidate screening, for example. The candidate profiles recommended by generative AI will only be as good as the fit criteria and data it’s been trained on — and can only improve with human feedback over time. So recruiters using generative AI for this should continuously provide feedback to “teach” the tool how to improve matching capabilities.  

“The whole point is to make sure that you’re engraining yourself — your perspectives and your information that you use to make decisions — and you’re helping the AI get coached up and educated to give you a better set of recommendations in the future,” Harrington said. 

What are some top considerations for HR leaders to be aware of?

Generative AI may be new, but it’s being adopted at lightning speed — and it’s important to stay ahead of how it’s being used in your organization. HR leaders have some valid concerns to address, Harrington acknowledged. These include:

  • Who will use it and how?

  • How will it transform the way people work?

  • How will it change the organization’s approach to all aspects of the talent lifecycle (e.g., sourcing, interviewing, hiring, employee experience)? 

  • What are the regulatory implications?

  • Are we remaining cognizant of bias?

  • Are we using it ethically and defensibly?

“Getting educated is a really important part of the equation,” Harrington said. “We’re going this direction [and] it’s a responsibility of organizations to understand it.”

Join Phenom for a live virtual event that dives into the specifics of generative AI. 

And don’t forget to catch TXL every Thursday at noon ET. Get notified of all upcoming TXL episodes here.

*The information provided on this website does not, and is not intended to, constitute legal advice. All information, content, and materials available on this site are for general informational purposes only.

Kasey Lynch

Kasey is a content marketing writer, focused on highlighting the importance of positive experiences. She's passionate about SEO strategy, collaboration, and data analytics. In her free time, she enjoys camping, cooking, exercising, and spending time with her loved ones — including her dog, Rocky. 

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