How One Healthcare System Screened 1,800 Graduate Nurses in Two Weeks Using Voice AI

For large healthcare systems, graduate nurse hiring isn't a quarterly initiative. Rather, it's a high-stakes event that happens twice a year with compressed timelines and massive volume.

When thousands of qualified candidates apply within two-week windows, the traditional recruiter phone screen model breaks down. Candidates expect speed and transparency while recruiters struggle to maintain quality conversations at scale.

One major non-profit healthcare system had already proven that Phenom's industry-specific applied AI and automation could greatly improve its hiring experience through its pilot with Phenom's high-volume solution. But their graduate nurse recruitment presented an even bigger challenge — one that would require technology capable of handling screening conversations at scale without sacrificing the personal connection healthcare candidates expect.

The story of how this organization beta tested Phenom Voice Screening Agent (hear it in action here!) offers lessons in HR innovation under pressure. But to understand why using this type of automated, context-specific screening method made sense as the next step, it helps to first understand the volume problem they faced with graduate nurse hiring.

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How do healthcare systems screen thousands of graduate nurses during peak hiring seasons?

The scale of graduate nurse hiring at this healthcare organization was staggering. The system runs hiring cycles for these candidates twice annually, and the application volume overwhelms traditional recruiting processes. "We get about 1,500 to as many as 3,000 applicants," explained their Director of Belonging and Talent Attraction. "And that's within a two-week window." Compounding the issue? Eight recruiters were responsible for screening every single candidate.

That volume creates real problems. Traditional phone screens meant candidates experienced delays that healthcare systems competing for the same talent pool can't afford. "Candidates want to see that we respect their time and respect the fact that they're likely getting multiple offers from other healthcare providers," she explained.

To manage the volume, the organization traditionally brought in three to five additional administrative staff to support the eight recruiters during these windows. Everyone worked compressed schedules to clear the screening backlog. But this approach consumed recruiter time that could have been spent on positions that don't have a high volume of applicants, where sourcing and relationship-building actually drive outcomes. The healthcare system needed a way to free recruiters from high-volume screening work, and they had already seen automation work for other hiring challenges.

How can high-volume hiring technology reduce healthcare recruiter screening time?

Before Voice Screening Agent, the organization piloted Phenom High-Volume Hiring. The approach was methodical: start with a single job family at one location, test a streamlined application with seven to twelve standard questions, and allow qualified candidates to bypass the traditional recruiter phone screen by self-scheduling their interviews.

"We really wanted to give recruiters the opportunity to spend a lot more time focusing on the positions that don't have that high volume of applicants, where they do need to network and source those candidates," the leader explained. The solution worked because it identified qualified candidates quickly while empowering them to move through the process at their own pace.

The results went beyond expectations. Time to fill dropped from 30 days to 23 days — a 23% improvement. Even more notable was recruiter efficiency: "It was about 20 minutes that it was taking a recruiter to spend with each candidate throughout that entire journey. And we're down now to eight minutes," she revealed. That 60% reduction meant the team could accomplish more without adding headcount. The quality improved, too — the organization went from reviewing seven candidates per hire down to just three.

After proving success at one location, the healthcare system rolled out High-Volume Hiring across all locations for that job family. Just as important, the pilot created organizational confidence that AI-powered automation could deliver real business results, setting the stage for testing something even more ambitious.

What are the results of using an AI agent to screen graduate nurse applicants?

Given the success the team experienced with High-Volume Hiring, the talent attraction leader viewed Voice Screening Agent as a natural next step. The graduate nurse group was the ideal beta test case: predictable volume, compressed timeline, and urgent need for recruiter capacity. The TA leader managing graduate nurse hiring tested the product herself and agreed to pilot it. The team briefed Phenom's product owner on what to expect: hundreds of applicants would hit the system on day one. They weren't sure he fully grasped what that would mean in practice.

Day one proved them right. Applications flooded in within hours, overwhelming the platform and temporarily breaking the system. By day two, the issue was completely fixed. But the TA leader faced a critical decision: scrap the beta test and return to traditional phone screens, or trust the technology would stabilize. She chose to keep going. Day one tested (and temporarily broke) the system's limits. Hundreds of graduate nurse applications flooded the system within hours, overwhelming the platform.

By day two, the system was completely fixed. But the TA leader faced a critical decision: scrap the beta test and return to traditional phone screens, or trust the technology would stabilize. She chose to keep going.

The team established twice-weekly meetings with Phenom's product owner to share real-time feedback on both candidate experience and recruiter workflow issues. The product team responded quickly — delivering fixes within hours. "We were giving that feedback in real time, and the product team was actually working on it in real time," the talent attraction leader explained.

Her trust paid off. Nearly 1,800 screening invitations were sent, and 85% of candidates completed the Voice Agent screening — showing candidates not only accepted AI screening but welcomed it. Even more surprising, recruiters who initially might have feared job displacement became supporters, providing detailed feedback on improving the experience.

By the pilot's end, the TA leader asked: "Any chance we'll have this for the September cohort?" Her manager, who had expressed "real concerns" mid-pilot, began asking if Voice Screening Agent could be bundled with High-Volume Hiring. "We turned two folks who were nervous about it into believers.”

Related: Reimagining Screening: How Voice AI is Redefining the Candidate Experience

Will AI screening tools replace healthcare recruiters or help them?

The announcement could have triggered resistance from recruiters worried about job security. Instead, they became unexpected supporters. "When you hear ‘We're going to apply an agent to screen your applicants for you,’ you think a recruiter is going to get nervous," the leader acknowledged. "These recruiters embraced it."

Rather than viewing the Voice Screening Agent as a threat, recruiters saw it as a tool that freed them to do work requiring human judgment and relationship-building. They provided detailed feedback on improving the recruiter experience, suggesting ways to sort candidate information and improve workflows. "They were giving us feedback to enhance the experience from a recruiter perspective. And then to find out, they too are hoping that in the next cohort, we can apply this technology."

The recruiter response reflected a broader organizational approach: "It didn't take anyone's job away. It really just opened up our opportunity to do more." In a healthcare environment where organizations are constantly asked to "do more with less," Voice Agent represented a genuine solution. Recruiters could redirect hours previously spent on high-volume phone screens toward positions needing more active sourcing or toward hospital rounding to engage clinical staff about open positions.

How should healthcare HR teams evaluate AI recruiting technology?

When evaluating new AI technologies for the HR team, they ask: "Will it affect our ‘moments that matter?’” These are critical touchpoints across the candidate journey from attraction through alumni status. If the answer is yes, and the potential outcomes map to fiscal year priorities, the technology merits serious consideration.

For attraction, “moments that matter” include the application process, 24/7 access to information through chatbots, and abandoned application follow-up. For current employees, it covers internal mobility, employee referrals with real-time status checking, and career progression. "We look at the journey and we say, where could we automate or where do we have automation already built in, and where do we need it?"

Applying this lens helps resist technology-for-technology's sake decisions and ensures AI investments connect to genuine candidate or employee pain points rather than vendor sales pitches.

Before committing to any beta test, the opportunity is socialized with peers who lead recruiting operations, providing a clear description of what the tool does, and asking whether they see value. "Transparency and buy-in are really important," she emphasized. “We do fiscal year priorities every year, and we write out what the strategy is, what we hope to accomplish with it... and we share that transparently with our executive leadership team to get that buy-in."

How are healthcare systems implementing AI across the entire hiring process?

Instead of focusing on isolated tools, the HR team is building toward automation across the entire talent lifecycle using Phenom’s unified solution that brings healthcare-specific context to every interaction. Voice Agent will continue with a second pilot using a smaller candidate volume before wider rollout. They're also exploring bundling Voice Agent with High-Volume Hiring to create a unified experience from application through interview scheduling.

"AI and automation have gone from a nice-to-have to a must-have,” she said. “If we're not doing it, then we are actually slowing the process down. And that's not what candidates are accepting of us." Healthcare talent has options, and systems that can't deliver speed and transparency will lose to competitors who can.

To that end, the healthcare system is also preparing to beta test Phenom Talent Marketing Agent and potentially Phenom Interview Intelligence, focusing on Phenom Intake Call Agent, which would automate the initial recruiter-hiring manager conversation where job requirements are defined.

Key Takeaways

This healthcare system's Voice Screening Agent pilot wasn’t about seeing if AI could replace their recruiters. It was about collaborating with Phenom in pursuit of providing a better overall talent experience. When 1,800 graduate nurse applicants overwhelmed the agent on day one, the team kept going, provided real-time feedback, and emerged with an 85% screening completion rate, proving that candidates welcome AI when it respects their time.

The shift from skepticism to support shows what's possible when organizations approach AI with transparency rather than fear. Recruiters who initially might have worried about job security became supporters who requested Voice Screening Agent for future hiring efforts. Similarly, leaders who expressed concerns mid-pilot began asking how to bundle it with High-Volume Hiring.

For healthcare organizations watching competitors move faster while their own teams struggle with volume, the biggest takeaways are salient: use a "moments that matter" approach to filter HR technology decisions, establish real-time collaboration with vendor partners during beta tests, and maintain continuous transparency about how AI augments rather than replaces work.

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