AI for Human Resources
Collaborate with AI to make recruiting, people ops, and policy engagement faster and fairer.
Practical information:
Course Description
In this Power BI case study, you will be exploring a dataset for a fictitious software company called Atlas Labs. This course focuses on helping you import, analyze and visualize Human Resources data in Power BI. Building on your existing knowledge of the platform, you'll learn how to effectively work with Power BI using example data.
You’ll carry out exploratory data analysis and will use DAX to help build powerful visualizations. You’ll finish your analysis by diving deeper into attrition and what factors impact attrition. This analysis will help the organization determine what action they will need to take to retain more employees.
We’ll finalize the case study by making design changes to our report that provides a clean, branded design.
What you'll learn
Write clear prompts that help AI tools support common HR tasks.
Use AI to draft fair job descriptions, rubrics, and interview questions.
Analyze workforce data with AI to surface trends and inform planning decisions.
Apply responsible practices when using AI for compliance reviews and sensitive employee data.
Understand how AI agents connect into workflows that improve HR operations.
Chapters
1. AI in Recruitment: Faster and Fairer
Learn how AI responsibly accelerates recruitment with inclusive job descriptions, sourcing strategies, and bias-aware interview questions.
2. Enhancing People Operations with AI
Discover how AI strengthens workforce planning, onboarding, and compliance. You’ll work with HR data, and create skill roadmaps that prepare your team for the future. Along the way, you’ll see how AI supports HR decision-making while safeguarding employee privacy.
3. Scaling HR Support with AI Agents
Explore how AI agents can help HR scale consistent support, while introducing new responsibilities around trust, boundaries, and ongoing ownership. You’ll learn when agents are the right tool, how employee-facing AI changes risk, and what HR must do after systems go live. This chapter focuses on practical, real-world stewardship: building agents thoughtfully, testing their behavior, and operating them responsibly over time.
Related courses
Artificial Intelligence in Business and Industry
Postgraduate - Kortrijk - KU Leuven, PUC - KU Leuven Continue, VAIA