Recruiters Strengthen Intake Processes To Manage Surging Application Volume

Job application volume is currently surging by 400%. There seems to be no shortage of applicants, but companies are struggling to hire at a timely pace. While part of the disconnect revolves around general hiring slowdowns and economic hesitation, many recruiters say automated applications are partly responsible for the pause. AI tools are lowering the barrier to apply, making application volume a weaker signal of true fit.

Katherine Valaitis is fully steeped in the friction hiring teams are experiencing. A Talent Acquisition Strategist at HR and payroll consultancy Willory and formerly a Senior Talent Acquisition Partner at Pitney Bowes, she filled more than 90 roles in 2025 alone while maintaining a 98% offer acceptance rate. As a certified AI-driven recruiting power user, she has spent the past several years working across high-volume hourly and professional roles, giving her a clear view into how automation is affecting the talent funnel and how recruiters are adapting.

“Volume is up, absolutely, but the quality of that volume is way down. You’re not getting 400% more qualified applicants. That’s the problem,” Valaitis says. Recruiters note that some candidates using natural language modeling to auto-apply can confuse systems with resumes that may surface a relevant keyword, but ultimately don’t match the role. But candidates aren’t the only ones muddying the waters. The job market itself is a mess of mirrored postings and data-harvesting “ghost jobs.” To fight the bots and the bloat, recruiters are fighting back tactfully, using systems to filter out throwaway applications and enforce a baseline level of effort from applicants.

• Fighting the fluff: She describes a market so compromised that filtering out what’s authentic has become a core part of the job. “We are in a really bizarre market right now. Fraud is more common than it’s ever been in the world of HR and in hiring practices. And then you have organizations that are posting jobs to collect data. You have to pull out so much bloat and fluff to get to the actual numbers and what’s relevant.”

Valaitis says part of the problem lies in what happens internally before the job is even posted. If the intake process is sloppy, for example, the applicant pool will be too. Another issue is poorly defined requirements: if compensation, core skills, and success profiles are vague, the published role tends to attract more of the bloat she described. She advises, for one, revisiting job descriptions to build a strong funnel. Another suggestion is for recruiters to lock down firm parameters upfront and push back on hiring managers if a role isn’t actually urgent. Once roles are live, there’s one last barrier that can affect the speed of hiring: hiring manager feedback. Even when intake is tight, interview loops can stall on calendars and delayed responses, a structural lag many teams try to address with better interview scheduling practices. Prioritizing better systems, she says, is key.

• The pre-check lane: Pre-approving compensation and skills allows recruiters to bypass mid-funnel delays. “If I know that we are going to go up to 110 percent of the pay bracket for somebody from specific target companies with specific core skills, I want to be in a position to say, move quick on candidate A. They hit all of these bullet points, and they’re within what you gave me for approval for pay,” Valaitis says. Part of moving quickly means providing this information up front.

• Billing by the hour: Valaitis notes that establishing these parameters early helps costly structural delays. “You often see the breakdown that everybody loves to complain about, which is the time for feedback from the hiring manager. I think there’s a sincere reality that hiring is expensive, and interviewing is expensive. Pushing managers to give that feedback quickly or to make the time on the calendar quickly will continue to be a lag until somebody finally starts billing them by the hour.”

AI tools can help handle volume, but it’s important for teams to implement best practices around it to avoid bias. Various federal guidelines are regularly publishing guidance on how to use AI with integrity and safely, avoid discriminatory impacts in automated screening, and comply with emerging labor guidance on AI in employment. Valaitis says these concerns make algorithmic literacy a priority for both recruiters and candidates. She points to automated video interviews as a case in point that these tools have blind spots, and recruiters who don’t understand them have no way of knowing when results are being skewed.

• Dress for the algorithm: Savvy candidates are learning how to physically adapt to automated video screens. “If you had really big glasses, it would confuse the AI and not be able to figure out where your face was. But if you were wearing smaller glasses, you had a higher success rate of getting through that screening,” she explains. Her advice isn’t to abandon the tech, but to stay informed about its limitations.

How recruiters reach candidates is also changing. Where cold-calling a slate of applicants was once a standard first touch, spam filters and call-screening apps often intercept unknown numbers. Valaitis says that change is pushing teams toward email and text as the initial contact, and how quickly a recruiter responds is a signal to candidates that the role is real and worth pursuing. She ties this to a wider push to speed up the hiring process without sacrificing clarity. She aims for a two-business-day window from application to first outreach for qualified candidates. When a company’s time-to-hire regularly creeps toward 60 days instead of staying closer to her preferred 45-day benchmark, that’s a sign internal processes deserve a closer look.

• Tables turned: Top candidates are not waiting around for slow internal processes, and Valaitis says high application volume is giving hiring teams a false sense of security. “If they’re interviewing with us, they’re probably interviewing somewhere else,” she says. “We continue to hear that we’re in an employer’s market. I think that is shifting so much to a no man’s land on what the market is. Our best talent, our most qualified talent, has options.”

For organizations struggling to find quality hires despite high application volume, Valaitis suggests taking a second look at the job posting itself. Does the job description reflect what was actually agreed on with the hiring manager before the role went live? If not, that’s the first thing to fix. Tightening job descriptions from the start rather than relying on filters and automation downstream ensures better candidates. She’s also playing close attention to how a company’s culture and values show up in talent attraction efforts.

• More than a paycheck: Research shows company culture is highly important to Gen Z entrants to the workforce, and building strong candidate experience often leads to better matches. “Gen Z wants inclusion. They want to be in the office and have that connection that comes along with that inclusion,” Valaitis says. “They want to feel valued when they’re going to work, and that generation is really shaping what our workplace looks like.” Delivering that employee value proposition may not shorten every search, but she believes it can help retain top candidates throughout lengthier hiring processes.

It’s difficult to fully eliminate the challenges that come with hiring in this moment, but Valaitis says the right benchmarks keep teams from stalling when it matters most. Small adjustments like committing to review talent within two business days or waiting ten business days before opening interviews won’t fix everything, but they prevent the kind of delays that cost companies their best candidates. “Work toward eliminating analysis paralysis. If you spend too much time, you’re going to miss out on something great,” she says.