A K–12 HR leader’s honest take on AI in the hiring process.
GUEST COLUMN | by Jennifer Duvall
Not long ago, hiring a teacher meant posting a job, collecting applications, reading through stacks of resumes, calling references, and sitting across a table from a candidate to get a feel for their potential impact in the classroom. It was time-consuming, imperfect, and deeply human.
That process is changing faster than most K–12 districts realize.
‘hiring a teacher …That process is changing faster than most K–12 districts realize.’
AI has quietly entered the K–12 hiring process—not with fanfare or a districtwide rollout announcement, but incrementally, through applicant tracking systems that sort resumes before a human ever sees them, platforms that rank candidates based on keyword matching, and tools that analyze interview responses for tone, word choice, and engagement.
For districts drowning in open positions and short on HR bandwidth, the appeal of AI is obvious. It promises to move faster, reduce bias, and surface better candidates. Sometimes it delivers on that promise. Sometimes it does not. Most districts are figuring that out in real time—and without much of a roadmap.
The Pressure That Made AI Attractive
To understand why AI is gaining traction in K–12 hiring, you have to understand the environment it walked into.
Teacher shortages have pushed HR teams to their limits. In many districts, a single HR director is managing dozens of open positions simultaneously, coordinating interviews, processing paperwork, and trying to make thoughtful hiring decisions under intense time pressure. Something had to give.
AI tools that can screen hundreds of applications overnight and surface a shortlist by morning do not feel like a luxury in that environment. They feel like a lifeline.
Some of what AI can do in the hiring process is extremely useful—from speeding up the writing of job descriptions to helping districts cast a wider net with job postings. It can remove identifying information from applications to reduce unconscious bias, flag candidates whose certifications match district needs, and send automated communications that keep applicants informed and engaged during a process that can otherwise go silent for weeks.
These are real improvements over manual processes that were never designed to handle the volume K–12 HR teams are managing today.
What Gets Lost When the Algorithm Decides
But this is where we need to slow down, because the efficiency gains are real—and so are the risks.
Teaching is one of the most relationship-dependent professions there is. The ability to connect with a nine-year-old who is struggling, read a room of thirty teenagers, or earn the trust of a skeptical parent does not show up cleanly in a resume keyword match.
Yet increasingly, the candidates who make it to the interview stage are those whose applications were optimized for the algorithm—not necessarily those who would be most effective in a classroom.
Letters of recommendation are a good example of this tension. For decades, a strong letter from a cooperating teacher or principal who knew a candidate well carried real weight in the hiring process. It revealed something an application could not: how someone handled a hard day, responded to feedback, or demonstrated the kind of resilience the job demands.
AI systems largely cannot parse that nuance. A letter is reduced to a document, scanned for sentiment, and scored. The human signal gets flattened.
I am not arguing that letters of recommendation are perfect. They are prone to their own biases and inconsistencies, and the growing reality is that many are now being drafted by AI, further diluting their authenticity. But replacing them with algorithmic ranking without acknowledging what gets lost in the trade is a mistake districts will ultimately feel in their classrooms.
The Threat Question Nobody Wants to Answer
There is another conversation happening in K–12 HR circles that does not always make it into the official talking points: Are HR professionals feeling threatened by AI?
Honestly, some are. That is worth taking seriously rather than dismissing.
When a tool can screen one hundred applications in the time it takes a human to read twenty, it is natural to ask what that means for the people whose jobs have historically included that screening.
The answer, I believe, is not that AI should replace HR judgment. AI should handle more of the mundane, transactional work so HR professionals can devote themselves to the relational work. That includes coaching hiring managers, building connections with potential candidates before a position opens, and thinking strategically about what the district’s workforce should look like over the long term.
AI cannot do that work. But the shift will happen only if HR leaders are willing to let go of the tasks AI can handle and lean into those it cannot.
What Responsible AI Adoption Looks Like
Districts that are getting this right share a few things in common.
They are transparent with candidates about where and how AI is used in the hiring process. They have established guardrails that keep human judgment in the loop at critical decision points, particularly final hiring decisions. They are training HR teams not only to use AI tools, but also to evaluate what those tools produce.
They are also asking hard questions about equity—specifically, whether the AI systems they use are producing diverse candidate pools or quietly narrowing them.
None of this requires a massive technology budget or a dedicated AI task force. It requires leadership willing to engage with the technology honestly and acknowledge both what it can do and what it should not be asked to do alone.
AI is not going to solve the teacher shortage. It is not going to replace what happens when a principal sits across from a candidate and learns things no resume or ranking could reveal—how that person thinks on their feet, talks about kids, or carries the kind of presence that makes a classroom come alive.
But when used thoughtfully, with clear guardrails and a commitment to keeping the human signal in the process, AI can make K–12 hiring faster, fairer, and more strategic.
That is worth pursuing. Just not blindly.
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Jennifer Duvall is a Principal Advisor at Red Rover.
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