While an increase in applications might seem beneficial on the surface, it also adds pressure to University Recruiting teams to manage overwhelming workloads and reduced quality of candidates. More than half of UR teams have reported an increase in entry-level application volume, with nearly a quarter experiencing more than a 10% increase. It’s safe to say this explosion of student applications is heavily influenced by generative AI (GenAI). 

The GenAI Surge & What It Means for Early Talent Recruiting 

Nearly half of students report using AI-powered tools like ChatGPT to help them apply for jobs. The introduction and prominence of GenAI in the job search, such as auto-fillers, resume generators, and auto-apply bots, enable students to apply for open positions at an unprecedented rate. Some tools even allow candidates to apply for multiple jobs with one click. 

Because GenAI is commonly leveraged to optimize resumes and match job descriptions–rather than accurately reflecting one’s true background–the quantity of applications has skyrocketed and they’re all looking the same, making it hard to select the real right candidate. 

Challenges University Recruiting Teams Face 

“We’re seeing candidates use Generative AI to be someone they are not or even steal an identity to get paid as that person. Many are easy to catch during interviews, but a few have slipped through the nets. Managers report some new hires who do not know how to do the work they are hired for.” 

– Head of Global TA as a large Tech company

While some uses of GenAI present a low-level threat to the integrity of the recruiting process, such as students using ChatGPT to train them for an interview, others pose much higher risk. Early talent could be using GenAI to misrepresent their skills or experience–even going so far as to commit identity fraud. 

 

The onslaught of applications and decrease in quality (or, arguably, honest) candidates creates the perfect storm for a necessary increase in screen time. To effectively filter out promising prospects from questionable candidates, recruiters are forced into an extensive, front-end screening process. 

Strategic Solutions 

Some strategies to overcome this bottleneck include incorporating knockout questions–targeted questions that screen candidates who don’t meet core requirements–and pre-application assessments that require specific technical skills to narrow down the talent pool.

Other teams have leveraged tech to combat tech, such as employing AI-driven talent matching tools to counterbalance the GenAI flood. Other tools have algorithms that identify best-fit candidates based on data, which can actually reduce bias in the recruiting process as well. 

It’s also wise to present students with clear guidelines on using GenAI in your recruitment process to avoid ambiguity. By clearly explaining when AI-generated content is acceptable and when it’s prohibited, University Recruiting teams can push forward the importance of authenticity. Establishing guidelines can help to limit inappropriate use of GenAI, and increase the speed, ease, and accuracy of decision making in hiring. 

GenAI has irrevocably altered today’s University Recruiting landscape, but by adopting innovative approaches and focusing on high-quality talent, University Recruiting teams can still achieve ambitious goals amidst the application avalanche.