AI in healthcare staffing: Real results, real ROI
The healthcare market is normalizing, but the opportunity remains strong. Healthcare staffing is considerably larger than it was in 2019, and demand for services continues. The challenge? Capitalizing on that opportunity efficiently while laying the groundwork for sustainable growth. That’s where AI in healthcare staffing becomes essential for competitive differentiation.
AI in healthcare staffing isn’t on the horizon—it’s already delivering measurable results for firms ready to take action. In a market where healthcare staffing firms are balancing fewer requisitions, ongoing provider shortages, and pressure to transform digitally, the leaders pulling ahead aren’t waiting for perfect conditions. They’re implementing AI strategically, solving real problems at the desk level, and seeing impressive returns.
During SIA‘s Healthcare Staffing Summit 2025, Catherine Pearson, President of Fastaff, Springboard, and HCS at Ingenovis Health, and Jonah Rader, President and COO of Connected Health Care, shared what’s working in their organizations. Their message was clear: AI and recruitment automation are transforming the provider experience and driving growth in challenging conditions.
The business case for AI in healthcare staffing
According to the GRID 2025 Industry Trends Report: Healthcare Spotlight, healthcare staffing firms predicted AI could save each recruiter 19 hours per week. And what’s more firms using AI are 96% more likely to grow.
But here’s what makes this critical: it has become harder to attract and retain healthcare professionals. Provider satisfaction with staffing firms has declined because processes are too complicated or take too long. The good news? The GRID 2025 Talent Trends Report: Healthcare Spotlight found that 75% of providers say their experience with recruitment AI was positive, and AI can increase provider loyalty by anywhere from 30% to 50%.
“You have to meet candidates where they are and understand that people want things now,” said Rader. “They want answers now. They want to be able to do their background check and schedule a phone screen without somebody calling or getting another random email.”
Where AI is being used in healthcare staffing today
The most successful AI implementations focus on specific, high-impact use cases. A framework for choosing where to deploy AI? “What are your major issues?” said Pearson. “So I would say something that is tedious and time-consuming, but not complex.”
Engaging candidates around the clock
Healthcare professionals work nights, weekends, and 12-hour shifts. Traditional business hours don’t work for them. Connected Health Care uses AI and automation across the talent lifecycle to meet candidates where they are, allowing them to complete tasks on their own time within their time constraints. Rader shared, “How can we place people faster, get people connected to the jobs faster, make the process streamlined, and then, obviously, of course, how can you just drive efficiency for your recruiters and account managers?”
Connected Health Care uses AI combined with other tools across the talent lifecycle as a win-win for both providers and recruiters. Rader said they’re using AI and automation to “expand on opportunities, expand on [candidate’s] interests, and then automate a lot of those processes through one system, so they’re not getting emails from four different portals and not having that confusing experience. On top of that, it leads to recruiters waking up in the morning with more actionable tasks to work on. Even that has provided a lot of opportunity to expand on where we can place our clinicians.”
Intelligent matching and sourcing
Job fit remains a critical pain point, especially when recruiters don’t understand provider desires or objectives, according to the GRID 2025 Talent Trends Report Healthcare Spotlight. Pearson said, “There are developed solutions on matching the right candidates to the right jobs where an LLM has more sophisticated job scoring based on the prior success rates with those clients, because you want your recruiters to have confidence that if they submit to this health system versus that, the likelihood of them getting an offer is greater.”
At Ingenovis Health, they want to spend less money on lower-margin jobs, relying more on their database rather than job boards, where costs can add up quickly. Pearson says, “It’s going to the database more. And with that, in 2025 so far, we’ve increased the number of placements when people source on their database by 200%.”
AI-powered candidate screening
Connected Health Care implemented AI-powered screening that engages candidates within 15 minutes of application, regardless of time of day. The results? Rader said, “We’ve seen a 58% completion rate from those invites with a satisfaction score of 4.73 out of 5. Candidates love the screener. One of the other important opportunities is that we all know clinicians are applying to a million different jobs. And so how can we utilize the tech to expand our recruiters’ capacity to place them at multiple places or multiple states, not just the one job that they apply for?”
Using AI for paper timesheet processing
Pearson highlighted automating paper timesheet processing as another use case. “Our candidates care about getting paid accurately and on time,” Pearson explained. “Mess up their paycheck two weeks in a row, and they won’t be happy to work for us.”
AI-powered paper timesheet processing extracts the data with rules you can set up, eliminating manual entry, reducing payroll errors, and accelerating payments to providers. Pearson said, “It makes that review really fast, and you can eliminate that manual time entry. …It helps streamline that in an easy way, to just eliminate that part of the friction.”
The results of using AI speak for themselves
Connected Health Care has heavily adopted Bullhorn Amplify and seen transformative results. “Data enrichment is huge. If it doesn’t live in your database, you can’t act on it. So, we spend a lot of time focusing on data health and enrichment. We’re saving roughly 200 hours per week on automated tasks and enrichment tasks, which means making the candidate connection to unique jobs easier because it’s all streamlined,” Rader says.
The operational improvements translate directly to business outcomes: “We’ve also seen results, especially over the last two months. Our pre-screen counts, so our recruiters actually talking to people, have gone up over 40% from month to month. We’re seeing longer talk times, longer average duration phone calls for our recruiters, which means they’re not only better prioritizing, but also having more meaningful conversations, and we’re having stronger outcomes. We’ve seen client submittals go up about 96% in the past 45 days. Placements were up over 35% month over month as well. I believe we’re only scratching the surface of that opportunity.”
The AI adoption framework that works in healthcare
Both leaders emphasized that successful AI adoption in staffing starts with understanding problems at the desk level and not implementing technology for technology’s sake. Pearson said, “Build cool things that solve problems, and they will adopt it.” Rader added, “Ask your team what’s taking up so much of their time that they don’t think is beneficial. That’s a great place to start.”
The practical approach both leaders recommend:
- Start small and specific. Identify one or two high-impact pain points—tedious tasks that consume time but don’t require complex decision-making.
- Centralize your data. If candidate interactions live across fragmented systems, your AI can’t learn effectively. Everything should flow into your ATS to create a single source of truth.
- Test with a core team first. Both leaders mentioned using the “SEAL Team Six” approach—a small group of adaptable recruiters who can test, provide feedback, and help refine the solution before broader rollout.
- Avoid commitment bias. If you’ve invested heavily in a solution that’s now outdated or underutilized, forcing adoption won’t solve the problem. Instead, be willing to pivot and focus on tools that show they help recruiters be more successful.
- Measure what matters. Your KPIs may need to change. If automation reduces the number of pre-screens required but increases placement rates, that’s a win—adjust your metrics accordingly.
The human element remains critical
AI in healthcare staffing isn’t about replacing relationships. It’s about enabling them at scale. After all, healthcare professionals still want to work with recruiters they trust. Pearson said, “It’s great that it’s still a relationship business. The recruiterless model did not win during the pandemic. It’s not like ordering an Uber, I’m going to quit my job, and I’m going to work on a 13-week assignment for less of a premium than I did before. They still want those relationships. So from everything that you’re doing with technology is trying to help recruiters foster those relationships…do this work so they can get to the recruiter faster, so they can talk to a person.”
AI handles administrative burden, qualification screening, and off-hours engagement, so that recruiters and candidates connect, those conversations are substantive and relationship-building.
Your competitive advantage starts now
The healthcare staffing firms that are successful today are iterating quickly and making disciplined decisions about where to invest in digital transformation. Waiting around for perfect conditions or comprehensive AI strategies means falling behind. The firms that start now—even with small steps—are building capabilities that compound over time.
Ready to see how AI can transform your healthcare staffing firm? Learn more about Bullhorn Amplify, our AI-powered solution designed to help you achieve more placements and better margins with the same team at bullhorn.com/amplify.
