Before HR Jumps into AI, Do These 5 Things First

AI is everywhere in HR right now, and it’s not going away. Vendors are promising transformation. Leaders are asking for automation. And HR teams are feeling the pressure to do something, anything, and to do it fast.

Before you deploy another tool, chatbot, or algorithm, there are a few foundational steps that HR must take first. Skipping these doesn’t just slow adoption, it creates risk, confusion, and mistrust.

Here’s what to do before jumping into AI.

1. Get Clear on the Problem You’re Actually Solving

AI is not a strategy. It’s a tool. So treat it as one. Before introducing AI, HR needs to answer one simple question: What problem are we trying to solve? Is it:

  • Slow turnaround times?

  • Inconsistent decisions?

  • High manual effort?

  • Poor employee experience?

If the problem isn’t clearly defined, AI will amplify the noise rather than fix it.

2. Document and Simplify the Process First

AI should support a known, existing process, not replace one that only exists in people’s heads. Before introducing automation:

  • Document how the process actually works today

  • Highlight how it should work vs how it does work

  • Identify decision points and exceptions

  • Remove unnecessary steps

If a process is unclear or overly complex or complicated, AI will only make it fail faster.

3. Establish Ownership and Decision Rights

One of the biggest AI adoption failures in HR doesn’t lie with the technology, it lies with it’s governance. Before using AI:

  • Assign a clear process owner

  • Define who approves, who reviews, and who overrides

  • Decide where human judgment is required

AI should inform decisions, not quietly make them without any accountability.

4. Clean and Standardize the Data

AI is only as good as the data behind it. HR data is typically fragmented, outdated, or inconsistently defined. “Garbage in, garbage out.” Before deploying AI:

  • Standardize key data fields

  • Define data quality standards

  • Address known gaps and inaccuracies

Poor data doesn’t only reduce value, it also introduces issues with fairness and creates compliance risks.

5. Set Guardrails for Fairness and Transparency

HR systems don’t operate in a vacuum. They impact people’s jobs, pay, and future opportunities. Before using AI:

  • Define what “fair” looks like

  • Ensure decisions can be explained to employees

  • Build in human review for all sensitive outcomes

Trust is harder to rebuild than it is to protect.

AI Works Best on a Strong Foundation

HR doesn’t need to rush into AI to stay relevant. It needs to be intentional. When processes are clear, ownership is defined, and data is trustworthy, AI becomes a powerful accelerator and not a huge potential risk.

The businesses and organizations that succeed won’t be the ones who adopt AI first. They’ll be the ones that prepare for it properly.

View the HR Ops Effectiveness Framework
Previous
Previous

HR Isn’t Changing This Year (Part 1)

Next
Next

Effectiveness, Efficiency, Fairness, and Technology