Skills-Based University Recruiting for 2026: What Works When Applications, AI, and Cheating Collide
Wednesday, March 4, 2026
11am PT / 2pm ET
University recruiting teams are heading into the 2026 hiring cycle with more pressure than ever. Application volume is surging. Candidate behavior is changing fast. AI tools have made it harder to trust traditional screening signals, just as expectations around fairness, transparency, and candidate experience continue to rise.
The result? Many teams are rethinking how they screen, assess, and interview early-career candidates without slowing hiring down or lowering the bar.
On March 4 at 11 am PT, we’ll share benchmarks and real-world trends from top university recruiting teams, backed by CodeSignal Talent Science research. You’ll get a closer look at how leading teams are modernizing assessments, using AI thoughtfully, and putting the right guardrails in place to hire early-career talent efficiently, fairly, and with confidence.
In this live webinar, you’ll learn how to:
- Shift from school-based filters to skills-based assessments at scale
- Benchmark your funnel across screening, assessment, and interview conversion rates
- Adapt your process to how candidates are using AI today
- Protect assessment integrity, while still delivering a positive candidate experience
This practical, data-backed session is designed for university recruiting and talent acquisition leaders who want concrete ideas they can apply ahead of the next big university recruiting push, grounded in what peer teams are already doing successfully.
Featured speakers
Dr. Seterra Riggs
Dr. Seterra Riggs is a Talent Scientist at CodeSignal, where she leads research on innovative, skills-based assessments and learning solutions that advance evidence-based hiring and development across technical and non-technical roles. Her work focuses on developing and validating simulation-style and standardized assessments that enhance fairness, validity, and user experience. She partners with large enterprise organizations to advise on implementation of cutting-edge tools, including AI-enabled approaches, that align with evolving job demands and workforce needs. Beyond her applied work, Dr. Riggs has published research on diversity, equity, and inclusion, remote work, and persistence in STEM. She earned her Ph.D. in Industrial-Organizational Psychology from Old Dominion University.
Katie Fairbank
Katie Fairbank leads product marketing at CodeSignal, where she helps bring innovative hiring and learning solutions to life. With over a decade of experience in HR tech, including leadership roles at Cornerstone OnDemand, Katie has built positioning, go-to-market strategies, and messaging that truly connect with customers.
Why this matters now
%
of students use AI in job applications
x
more applications per recruiter
%
of employers hired “strong” candidates who didn’t perform
The next university recruiting push is closer than it looks. Teams that don’t adapt risk carrying outdated processes—and weak signal—into another high-volume season.
This session will help you pressure-test your current approach against what top teams are doing successfully, so you can head into the next cycle with more confidence and stronger signal.
Frequently asked
questions
Will I get the recording if I can't attend live?
Yes. Go ahead and register, and we’ll send you the on-demand recording so you can watch it anytime.
Who should attend?
University recruiting teams, TA leaders overseeing early-career hiring, and talent professionals building or evolving a skills-based hiring strategy.
Will there be an opportunity to ask questions?
Yes. We’ve reserved time for live Q&A at the end of the webinar. You can submit questions throughout the session, and our experts will address as many as possible. For questions we don’t have time to answer live, we’ll follow up individually after the event.
What if I'm already using CodeSignal?
Even better. You’ll get insights on how other CodeSignal users are evolving their university recruiting strategy and maximizing their existing investment.
