Description

 Introduction

The Skills & Talent Intelligence (AI-Driven) in Cornerstone training provides a comprehensive understanding of how artificial intelligence powers skills management, talent insights, workforce planning, and personalized development within the Cornerstone ecosystem.

This program explores how Cornerstone’s AI-driven skills graph, talent intelligence tools, and predictive analytics enable organizations to:

1. Build a dynamic, skills-based workforce
2. Identify skill gaps and future capability needs
3. Personalize learning and career paths
4. Improve internal mobility and succession planning
5. Align workforce capabilities with business strategy

Participants will gain hands-on exposure to AI-powered features such as skills inference, role recommendations, proficiency tracking, and workforce analytics dashboards.

Prerequisites

1. Basic understanding of HR processes (L&D, Talent Management, Performance)
2. Familiarity with Cornerstone LMS or Talent modules
3. General awareness of AI concepts in HR (helpful but not mandatory)
4. Access to Cornerstone environment (Admin or Super User access preferred)
5. Basic understanding of reporting & dashboards
6. Knowledge of data structures in HR systems (optional but beneficial)

Table of Contents

Module 1: Foundations of Skills-Based Organizations

1. Evolution from job-based to skills-based workforce
2. Role of AI in modern talent management
3. Overview of Cornerstone Talent Intelligence
4. Understanding the Cornerstone Skills Graph

Module 2: AI-Driven Skills Architecture

1. What is a Skills Graph?
2. Skills ontology and taxonomy in Cornerstone
3. AI-based skill inference mechanisms
4. Skill normalization and validation
5. Mapping skills to roles and job families

Module 3: Configuring Skills Framework in Cornerstone

1. Creating and managing skill libraries
2. Role-to-skill mapping
3. Skill proficiency levels setup
4. Importing and syncing skills data
5. Governance and data quality best practices

Module 4: AI-Powered Skill Inference & Recommendations

1. How AI infers employee skills
2. Profile enrichment using machine learning
3. Learning recommendations based on skill gaps
4. Career path recommendations
5. Role-fit analysis and internal mobility suggestions

Module 5: Talent Intelligence Dashboards & Analytics

1. Skills analytics overview
2. Identifying organizational skill gaps
3. Workforce capability heatmaps
4. Predictive workforce planning insights
5. Skills supply vs demand analysis

Module 6: Skills-Based Learning & Development

1. Personalized learning journeys
2. Adaptive learning paths using AI
3. Aligning certifications to skill frameworks
4. Continuous skill validation strategies

Module 7: AI in Succession & Career Mobility

1. Skills-based succession planning
2. Internal mobility insights
3. Talent pools based on skills
4. Identifying high-potential talent using AI signals

Module 8: Integration & Ecosystem Alignment

1. Integrating skills data with HRIS
2. Linking performance data with skills intelligence
3. API integrations and data flows
4. Data privacy & ethical AI considerations

Module 9: Implementation Strategy & Best Practices

1. Change management for skills transformation
2. Building a skills-first culture
3. Adoption strategies
4. Common implementation challenges
5. ROI measurement & business impact metrics

Module 10: Hands-On Labs & Case Studies

1. Configuring AI-driven skills mapping
2. Running skill gap analysis
3. Designing personalized learning journeys
4. Real-world case study discussion