Stitch Fix

Shae Daberkow is a strategic human resources and operations executive who leads enterprise transformation at scale. She builds high-performing HR teams, modern operating models and programs that align people strategy with business growth, technology modernization and measurable performance improvement.

As director of shared services at Stitch Fix, Daberkow is leading the evolution of HR service delivery through AI-enabled support, automation and stronger governance. Her experience spans senior leadership roles at Amazon, Google Cloud, AWS, CommonSpirit Health and other global organizations across technology, healthcare, retail and financial services. She has led complex organizational transformations, large HR teams, M&A integrations and enterprise-wide initiatives while driving meaningful change for some of the world’s most influential organizations.

AI Needs Human Judgment, Not Less of It

The HR function is at a crossroads. Artificial intelligence is quickly becoming part of the employee experience, from answering routine questions and guiding managers through policies to identifying patterns in workforce data. The opportunity is real: less administrative work, faster access to information and more capacity for HR teams to focus on the moments that require discernment, empathy and leadership.

But that opportunity comes with a responsibility. AI should not be treated as a replacement for human judgment. It should extend it.

People provide the goals, context, judgment and corrections that shape an AI-enabled outcome. They decide which questions are worth asking, what information is relevant, when an answer requires escalation and what “good” looks like in the context of a specific employee, manager, team or business decision. AI can make that work faster and more accessible. It cannot independently establish the values, tradeoffs and accountability that should govern it.

That is why HR has a central role to play in how organizations adopt AI. The work is not limited to selecting a tool or launching a chatbot. It is about shaping the operating model around the technology.

In my work leading HR transformation and shared services, I have seen that technology succeeds when it is connected to a clear purpose: simplify work, improve service delivery and make it easier for employees and managers to get the support they need. When it is introduced as a collection of isolated projects, it often adds another layer of complexity. When it is built into a thoughtful employee experience and supported by sound governance, it can change how work gets done.

“AI should not be treated as a replacement for human judgment. It should extend it.”

Consider an AI-enabled employee support experience. The aspiration is not simply to deflect inquiries or automate answers. It is to help employees find reliable information quickly, complete straightforward tasks with less friction and reach a knowledgeable person when the situation is nuanced, sensitive or consequential. That requires an intentional design. The content must be current. Policy owners must be accountable. Employees need to understand when they are interacting with AI and how to challenge or escalate an answer. HR professionals need visibility into recurring questions and points of confusion so they can improve the underlying process, not just respond to the same issue more efficiently.

This is where governance becomes practical. HR should help define the use cases that are appropriate for AI, the data it can access, the controls needed for sensitive decisions and the measures that indicate whether it is actually improving the employee experience. Governance should not be a committee that slows progress. It should be a set of working practices that make innovation responsible and repeatable.

For example, every AI use case should have a clearly accountable business owner, a defined decision right and a feedback loop. HR, technology, legal, security and business leaders each bring a necessary perspective, but shared input cannot mean unclear ownership. HR should own the people process and experience; technology should ensure sound architecture, integration and security; and leaders should be accountable for the business outcomes the technology is meant to improve.

The same principle applies to data. HR data carries context that is easy to lose when it is reduced to fields in a system. An absence may reflect a caregiving responsibility. A performance pattern may require a conversation, not a conclusion. A workforce trend may point to a process problem rather than an individual issue. AI can help surface information, but people must interpret it responsibly.

The most capable organizations will not be those that automate the most. They will be the ones that make their people more capable: giving employees better self-service, equipping managers with timely guidance and freeing HR teams to spend more time on judgment-intensive work. That requires HR to move beyond being a consumer of technology and become an active designer of how technology, processes, data and human accountability work together.

The future of HR is not less human. It is more intentional about where human judgment matters most.