The rise of artificial intelligence in recruiting has created new efficiencies for employers, but it has also introduced new complications. Hiring teams are now sorting through larger volumes of applications, many of them generated or assisted by AI tools, as companies look for faster ways to identify qualified candidates.
Sebastian Scott, CEO of Clera, says the increase in application volume has changed the day-to-day reality for recruiters.
“Right now, AI has created a lot of noise in hiring,” Scott said. “Companies receive more applications than ever, but a growing share of that volume is mass-applied, poorly matched, or AI-generated. That makes it harder for even very strong recruiting teams to know where to spend their time.”
Scott said the shift has not eliminated the need for recruiters, but instead changed where they focus their attention.
“It is not about hiring managers trusting Clera instead of their own recruiting teams,” he added. “We work hand in hand with internal teams and help them do what they are best at: meet, assess, and close the right people.”
According to Scott, recruiting technology is increasingly moving beyond traditional keyword matching systems and relying more heavily on behavioral and contextual information gathered during the hiring process.
“We learn what a company is actually looking for, not just from a job description, but from the hiring manager’s feedback, past preferences, and the candidates they engage with over time,” Scott said. “The system gets sharper the more a team uses it.”
Clera said in a recent press release that it surpassed $1 million in annualized revenue within just months of launching and represents more than 80,000 professionals across the United States and Europe.
The broader hiring market has also seen companies reduce the length of recruiting cycles, particularly in competitive sectors where employers are trying to secure candidates more quickly.
“We are definitely seeing companies shorten hiring processes, often from months to weeks, and in some cases even days,” Scott said.
At the same time, some employers are reconsidering whether long interview processes actually improve hiring decisions.
“The old assumption was that more interview rounds meant more certainty,” Scott said. “In reality, seven rounds of interviews can still be a very indirect way of understanding whether someone will actually perform in the role.”
Scott said some companies are replacing portions of traditional interviews with practical evaluations designed to test how candidates perform in real-world scenarios.
“A well-designed work trial, a focused technical session, or a high-context introduction can often give a company better signal in less time,” he said. “We are actually seeing a lot of our startups move into work trials as part of their processes.”
While faster hiring can create concerns about poor decision-making, Scott argued that shorter timelines do not necessarily increase risk if evaluation methods are carefully designed.
“Of course, if companies simply rush, that can create risk,” he said. “But when the process is designed around better signals, faster and less risky can go hand in hand.”
Scott also pointed to the role recruiting systems can play in determining which candidates receive visibility during the hiring process. He said many existing systems still prioritize traditional markers of prestige.
“A lot of hiring systems still rely heavily on visible pedigree: the right school, the right company, the right title, the right keywords on a resume,” Scott said.
He added that candidates with nontraditional career paths are often excluded early in the screening process.
“That means many great candidates are filtered out before they ever get a real look, especially people with non-traditional paths, people who changed industries, self-taught engineers, or candidates who built impressive skills outside the most recognizable institutions,” he said.
Scott said evaluating candidates based on broader indicators of experience and potential can widen the range of applicants companies consider.
“Instead of only matching on surface-level credentials, we look at demonstrated skill, trajectory, motivation, and fit for the actual role,” he said.
As companies continue adapting to AI-driven hiring practices, recruiters and employers are increasingly weighing how to manage speed, candidate quality, and fairness in a rapidly changing labor market.