AI in Construction Recruitment: How a U.S. Leader Slashed Hiring Time

Construction recruitment has always been a challenge. On average, it takes 12.7 days to hire a worker in the recruitment in construction industry (source: inFeedo). For one of the largest construction companies in the U.S., the timeline stretched even longer—15 days on average. And when you’re hiring in large volumes across multiple projects, those extra days created serious problems. Delays piled up, recruiters felt overwhelmed, and projects risked falling behind schedule.

When they came to us, their biggest pain point was clear: the hiring process was too slow. Applications sat in inboxes, recruiters spent hours screening resumes, and interviews often started weeks later than they should have. Projects were left waiting for workers who should’ve been on site much sooner. They needed a faster way to bring in skilled people without cutting corners. That’s when we stepped in with CloudApper AI Recruiter for UKG.

How We Helped Them Transform Hiring

We began by analyzing their construction worker recruitment workflow from start to finish. The problem wasn’t the number of candidates—they had plenty. The real issue was the time-consuming steps between application and job offer. Every stage, from paperwork to resume review, added days to the timeline.

We introduced CloudApper AI Recruiter for UKG, and the difference was immediate.

Here’s what changed:

• Simple QR Code Applications: Candidates applied instantly by scanning a code at job fairs or project sites—no long forms, no wasted time.

• Chatbot Screening: A friendly chatbot captured experience, qualifications, and resumes in minutes.

• AI-Powered Ranking: Instead of manually reviewing hundreds of resumes, AI automatically matched candidates against job requirements and ranked them.

• Instant Shortlists: Recruiters received ready-made lists of the best candidates, so interviews could be scheduled the same day.

Within weeks of adopting the solution, their time-to-hire dropped from 15 days to under 4 days—a 73% reduction.

Why This Made Such a Big Difference

The impact went far beyond saving time. With a faster cycle, the company could finally keep projects staffed without delays. Recruiters felt less pressure, hiring managers had candidates ready on demand, and applicants enjoyed a smoother experience.

Here’s what the numbers looked like after the shift:

• Time-to-hire reduced by 73% – cut from 15 days to under 4 days.

• Recruiter efficiency improved by 65% – manual resume screening dropped from ~6 hours per job to less than 2.

• Interview scheduling accelerated by 80% – what used to take 5–7 days was completed in just 1–2 days.

• Candidate engagement increased by 40% – more applicants completed the process thanks to the simple QR code and chatbot flow.

• Overall hiring capacity doubled – recruiters could now manage up to twice as many open roles without additional staff.

This solution can also help them in seasonal construction recruiment.

And in construction, speed matters. When workers get to the site faster, deadlines are met, budgets are protected, and clients stay satisfied.

Why They Trusted the Integration

A major factor in their decision was how seamlessly the solution integrated with UKG/Kronos. They didn’t have to change their systems or retrain their teams. Candidate data flowed directly into their existing platform, making adoption smooth and stress-free. For a large organization with complex processes, this level of compatibility gave them confidence to move forward quickly.

What It Means for Construction Companies

Every company dealing with construction recruitment knows the pain of waiting on talent. A few extra days in the hiring cycle can push back entire projects and raise costs. This case proves that AI recruiting in construction can slash those delays and make hiring as fast as the job demands.

By bringing time-to-hire down to under 4 days, this firm turned recruitment into a strength rather than a bottleneck. For them, faster hiring meant more than convenience—it meant protecting timelines, improving workforce reliability, and keeping projects profitable.