Hawaii HR department seeks AI tool to cut civil‑service application backlog

Brian Feruto, deputy director for the Department of Human Resources and Development, told attendees that the department faces a large application‑screening backlog and is seeking an AI‑assisted tool to speed hiring.

"Morning, hackers. My name is Brian Feruto. I am the deputy director for the Department of Human Resources and Development, and we have a problem," Feruto said, describing the agency as "the state central HR agency for the executive branch." He said the department administers recruitment and hiring for about 17,000 civil‑service positions statewide and currently manages 3,500 to 4,000 vacancies at any given time.

Feruto said the staffing division uses the NeoGov recruitment platform to review applications and verify minimum qualifications. He told the group the department receives about 1,000 applications per week (roughly 3,900 per month) and currently has more than 5,500 applications awaiting review. "Examiners or application reviewers spend about 30 minutes to 10 hours per application," he said, and the backlog has slowed hiring for critical positions, increasing burnout among examiners and causing some qualified applicants to drop out of the process.

To address that, Feruto outlined requirements for an "AI and automation tool" to assist screening. He said the desired tool would "rapidly identify applicants who meet MQs, auto generate a recruiter scoring matrix using staff inputs, rank candidates by DQs or desirable qualifications, and then hopefully learn and improve over time." He added the system must include a human review loop.

Feruto identified several guardrails the department requires: alignment with Hawaii Administrative Rules and Hawaii Revised Statutes chapter 76; explainable, transparent screening logic; protection of applicant data privacy; and the ability to integrate with or export to NeoGov. He also asked for a rapid pilot goal: reduce the backlog by 75% within three months (from about 5,500 to roughly 1,400 applications) and achieve 85–90% accuracy compared with human reviewers, while helping lower the state's vacancy rate by 2–3%.

The presentation framed the request as a technical collaboration rather than a formal procurement decision. Feruto invited participants to "come build with us," describing next steps as data intake, smarter evaluation, and maintaining human oversight.

Details not specified in the presentation included a procurement timetable, budget or funding sources for the tool, and whether any outside vendors have been selected. Feruto named Enterprise Technology Services (ETS) as a coordinating partner for the state's HR database work but did not give further implementation dates or contractual details.