Importance of clean HR data for AI: What CHROs should know

Having to second-guess data is a CHRO’s nightmare, and clean data is more important than ever when adding AI to HR operations.

A lack of trust in data will affect an HR team’s ability to work effectively and could reduce other leaders’ trust in the HR team. HR AI implementations will receive a lot of attention from other company leaders, and CHROs must make sure that HR-related AI adoption isn’t negatively impacted by bad data.

Here are some key points CHROs must consider about clean data and its effect on AI.

1.     Bad data hygiene could lead to inaccurate AI predictions

AI often makes predictive analytics easier to carry out and more accurate. Historically, HR-related predictive analytics have focused primarily on turnover. However, more advanced AI tools will enable HR teams to improve overall results and predict data such as new hire success, promotion opportunities and growth patterns for employees.

Inaccurate data would derail these use cases.

2.     Poor data quality distracts HR from strategic work

HR staff having to constantly second-guess and clean data will slow down a CHRO’s team and distracts everyone from the strategic work that they should be focusing on.

For example, HR business partners may need to help department leaders anticipate employee growth needs. But if HR discovers that the data they’re using for the project isn’t reliable, it will take HR longer to complete the project and prevent them from moving on to other, potentially even more important, work.

3.     Bad data can lead to bad advice for employees

As AI expands in scope, some CHROs and their subordinates are implementing AI as a tool for answering employee questions. However, issues with the employee or policy data that feed the AI tool could lead to employees receiving incorrect information. Employees using the incorrect data to make decisions, such as investment moves, could lead to legal issues.

In addition, employee confidence in HR will decrease if answers from the AI tool are consistently wrong because of bad data.

4.     Bad data can negatively affect system adoption

If AI results are consistently wrong, employees will stop using the system that is producing the results, even if the issue stems from data.

A CHRO has likely invested significant time and money in a new system, so the data used by AI must be accurate. A system’s bad reputation among employees can be extremely difficult to reverse.

5.     Confidential data must be protected

Once CHROs ensure that HR data is clean, they must ensure that confidential data is being safeguarded from AI as well.

Boundaries must exist between the data that AI can use in its models and off-limits data in order for the company to remain compliant with local laws. For example, the AI models and the data that they produce should at no time share Personally Identifiable Information. AI should also not share confidential information, such as employee salaries or reasons for employee terminations.

Eric St-Jean is an independent consultant with a particular focus on HR technology, project management and Microsoft Excel training and automation. He writes about numerous business and technology areas.