School district HR leaders are using AI to cut through administrative work - from sorting employee records to screening principal applicants - but they're drawing a firm line: the technology assists decisions, it doesn't make them.
In Virginia's Fairfax County Public Schools, the district used AI to create a Python script that sorted through more than 40,000 employee records scattered across different systems, extracting relevant information and organizing it for upload into a single platform. William Solomon, the district's chief human resources officer, said the task previously consumed staff time that could have gone toward strategic work.
"It probably doesn't sound like the most glamorous use case for AI, but I would argue that it actually empowered us to focus on more of the strategic work and less of the task-oriented work," Solomon said during a virtual panel hosted Aug. 11 by ILO Group, an education strategy and policy firm.
The caution around AI's limits comes as other sectors face legal pushback for using the technology in hiring and layoff decisions.
AI in hiring: Faster screening, human final say
Indianapolis Public Schools, Indiana's largest district, built an internal AI tool to score initial principal applicants using the same rubric its staff previously applied manually. Before the tool, a team reviewed every application before advancing candidates to the in-person hiring process. Now the AI handles that initial scoring, and candidates who meet the threshold move to a hiring committee.
Christina Aden Hamer, chief HR officer at IPS, said the district spent a year gathering community feedback on AI use before launching a pilot program. The district's guiding principle, she said, is that AI never replaces a decision.
"I think the overarching North Star - that we have continued to not only be accountable to for our community and stakeholders - is that AI for IPS is not a replacement for any decision," Aden Hamer said.
The district also uses AI to generate salary offering emails, but the tool completes manual calculations based on compensation rubrics, salary schedules, and collective bargaining contracts. It does not assess soft skills or other non-tangible criteria that factor into pay.
For HR professionals looking to apply similar approaches in their own organizations, resources like AI for Human Resources and the AI Learning Path for CHROs offer practical guidance on implementation.
Governance and data privacy guardrails
Colorado's state education department took a different approach: let staff experiment first, then build structure around what works. Margarita Tovar Rosales, deputy commissioner of policy and talent at the Colorado Department of Education, said the agency worked with education nonprofit WestEd to help every operational team develop AI use cases. After the pilot, staff knew who to contact for AI initiatives and the department could build consistent workflows.
Without governance, Tovar Rosales said, AI use can become too sprawled, costly, and unproductive at scale.
On data privacy, IPS does not allow personally identifiable information in its AI tools. The district built its systems through Google's Gemini platform rather than relying on multiple third-party vendors, and its HR templates use secure spreadsheets without sensitive data. That approach has saved the district over $300,000 for the 2026-27 school year, with an additional $500,000 in expected savings the following year as it phases out third-party software.
Fairfax County Public Schools avoids using Social Security numbers and dates of birth in AI tools, but does use names and work locations because its tools operate within a secure network with single sign-on credentials.
"The flexibility to be able to use AI to tease out details is gold," Solomon said.
Why this matters for HR professionals
These district examples offer a template for HR teams in any sector: identify the most repetitive, rule-based tasks - record sorting, initial applicant screening, salary calculation - and automate those first. Keep human judgment on anything involving evaluation, compensation, or employment decisions. And build governance early, before AI use spreads informally across teams, to avoid wasted spending and inconsistent practices.
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