10-07-2025
AI Won't Replace HR, But It Will Expose Every Broken System
Apryl Evans is the CHRO at USA for UNHCR, driving people strategy to support mission impact and well-being.
We're in an era of AI theater, where companies adopt sleek advanced tools fast, and then suffer with messy application behind the scenes. It's what happens when leaders prioritize performance optics over system readiness, skipping the hard work of aligning structure, ethics and culture.
Nowhere is this more visible than in HR. Too many companies integrate AI into outdated job structures, uneven feedback cultures and inequitable career design. Then they wonder why it accelerated bias and eroded trust. If your competency models are a decade old and your performance systems still reward output over insight, AI won't fix the problem. It will simply codify dysfunction in real time.
The question isn't whether AI will replace HR. It's whether your systems can support AI without betraying your people. If performance feedback is unclear, career pathways are vague or internal mobility only favors the well-connected, AI will mirror that reality—loudly and a lot faster.
Automation Scales Everything, Including Confusion
AI is not a neutral actor. It scales existing patterns, whether intentional or broken. For example, I advised a high-performing organization where leaders launched a talent-matching platform to improve internal mobility. But while the tool surfaced stretch opportunities, top talent didn't apply. Why? They'd never received the feedback, coaching or clear career conversations that would encourage them to pursue internal opportunities.
At another organization I advised, we delayed an AI rollout by 90 days—not because the tech wasn't ready, but because managers weren't ready to lead through it. So, we paused, trained differently and recalibrated expectations. By taking the time to integrate AI properly, the organization experienced lower attrition, increased mobility and faster trust recovery.
These examples show why the "we'll fix it after the pilot" mindset is dangerous. You can't automate what you haven't defined. And you shouldn't automate what you haven't audited. Before rolling out any AI-powered platform—whether it's for hiring, feedback or performance—you need a structural reckoning.
Ask yourself whether job levels are clear and equitable. Do your feedback loops create clarity or protect power? Is psychological safety practiced or just promised? These aren't philosophical questions. They're design imperatives because trust is a precondition for AI success.
HR's New Mandate: Architects Of Humanized AI
HR leaders shouldn't avoid AI. We should shape it. Our department is uniquely positioned to embed ethics, clarity and inclusion into the architecture AI depends on. But that requires more than input. It requires influence. Here are some key steps to help ensure your AI systems actually deliver.
• Audit before automating. Broken systems can't be streamlined, and no algorithm can resolve what your design refuses to acknowledge. So, look for areas where performance signals are missing, inconsistent or inequitable.
• Build cross-functional launch teams. The kind of bias that can include AI doesn't sit in one function. Involve DEI, legal, IT and operations early in the implementation process. That way, you can ensure there's cultural integration as well.
• Measure behavior, not just output. Behavioral science belongs in your AI governance plan. As you monitor your AI systems, consider factors like whether it rewards insight or velocity or whether it punishes dissent instead of supporting psychological safety.
• Design recovery and feedback loops. No AI is infallible, so you must establish processes for when tools misfire. For example, what is the escalation protocol? Who has override authority? Do employees know how to raise concerns?
Human-Centered AI Must Become Our Standard
According to McKinsey's 2024 State of AI report, more than 60% of companies expected to increase their AI investment, but few have clear policies for how AI intersects with ethics and employee well-being. That's not a tech gap. That's a leadership gap.
We don't protect humanity by rejecting AI. We protect it by refusing to build systems that ignore how people actually work, grow and thrive. Because in a world of machine learning, your organizational structure becomes your leadership philosophy—just written in code. So, if you wouldn't trust your performance system without AI, you shouldn't trust it with that kind of technology. AI won't disrupt HR. It will reveal who already gave up on doing the real work.
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