Employee Transactions for HR Decision-Making
Description
AI is intended to automate repeatable tasks, improve efficiency, measure employee performance, support onboarding, improve customer experience, improve user adoption, and improve analytics and reporting to further support decision-making and personalize experiences.
Detailed example
- Built-in user aids: Intelligent search, personalized recommendations, and proactive guidance. - Configuration and maintenance: Automated tasks, predictive analytics, and streamlined processes. AI Agents are embedded and can be enabled by customers to be ready to help across all areas of the HCM lifecycle: - Intelligent Recruiting: AI helps in creating job descriptions, identifying and ranking candidates, and generating interview questions. - Personalized Employee Experiences: Generative AI provides customized recommendations for career development and learning paths and can generate personalized learning content. - AI-Powered Employee Self-Service: AI chatbots answer employee questions and guide them through tasks. - Data-Driven Workforce Planning: Generative AI transforms workforce data into actionable insights for strategic planning, supports scenario simulations, and forecasts skill gaps. - Enhancing Employee Well-Being: AI-powered sentiment analysis assesses employee feedback to evaluate morale and potential risks and can generate personalized well-being programs. - Core HR and Payroll: AI is being integrated to improve the efficiency of these functions.
AI / analytics pattern
Generative AI: AI that generates new or synthetic content (e.g., images, videos, audio, text, code).
Automation level / stage
a) Pre-deployment – The use case is in a development or acquisition status.
Expected benefit
- Increase efficiency of Core Human Resources (HR) and Payroll - Enhance employee and veteran outcomes e.g., improve customer experience and improve user adoption
Controls / human review
ATO: Not reported; PIA: Not published