Precise definitions help HR leaders evaluate vendors confidently and make faster technology decisions.

10 AI and HR Technology Concepts Defined

These are the definitions HR leaders need when evaluating AI tools and speaking with vendors.

1. Natural Language Processing (NLP) is the technology that lets systems read and interpret human text. It powers resume parsing, chatbot conversations, and job description analysis.

2. Machine Learning (ML) is a method where systems improve their predictions through exposure to data. Candidate scoring models and attrition prediction tools rely on ML.

3. Robotic Process Automation (RPA) handles repetitive rule-based tasks like data entry, report generation, and system updates without human input.

4. Predictive Analytics uses historical data to forecast future outcomes, such as which candidates are most likely to accept offers or which employees are flight risks.

5. AI Chatbots are automated conversation agents that answer questions, schedule interviews, and collect information from candidates and employees.

6. Sentiment Analysis reads tone and emotion in text data. HR teams use it to monitor employee engagement through communication patterns.

7. Skills Inference derives competencies from job history and education data, even when a candidate does not explicitly list them.

8. Bias Detection algorithms flag statistical patterns in hiring data that indicate potential discrimination in screening or selection.

9. Computer Vision processes images and documents. HR applications include identity verification and automated form extraction.

10. Workflow Orchestration connects AI outputs to downstream actions across multiple systems, turning individual automation events into end-to-end HR processes.

See These Concepts in Action

Learn how leading HR teams apply these ideas: practical HR automation guide.