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Quest Training

AI in Human Resources Management Training Course

Artificial Intelligence is transforming Human Resources Management by enabling organizations to improve workforce decisions, automate repetitive processes, identify talent opportunities, and enhance the employee…

HRDA · HR Analytics, Digital HR, Technology & AIAll LevelsClassroomEnglish , Arabic
Duration
5 Days
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Sectors:Human Resources & Talent ManagementCategories:HR Analytics, Digital HR, Technology & AI

Course Overview

Artificial Intelligence is transforming Human Resources Management by enabling organizations to improve workforce decisions, automate repetitive processes, identify talent opportunities, and enhance the employee experience. From recruitment and workforce planning to performance management and learning, AI is becoming an increasingly important capability for modern HR functions. This course provides a practical and management-focused understanding of how Artificial Intelligence can be applied across the HR lifecycle. It focuses on business applications rather than programming, helping HR professionals and organizational leaders understand where AI can create measurable value and how it can be integrated with existing HR strategies and processes. Participants will explore AI applications in talent acquisition, employee analytics, performance management, learning and development, workforce planning, employee engagement, skills management, and intelligent HR automation. The course also examines how predictive analytics and AI-generated insights can support more proactive workforce decisions. Particular attention is given to responsible AI in Human Resources, including employee data privacy, algorithmic bias, fairness, transparency, accountability, human oversight, and governance. Participants will learn how to balance AI-driven insights with professional judgment and organizational policies. Through practical exercises, business scenarios, and applied workshops, participants will develop the ability to identify high-value AI opportunities, assess implementation requirements, manage associated risks, and develop an actionable roadmap for AI-enabled Human Resources Management.

Learning Objectives

  • By the end of this course, participants will be able to:
  • Understand the strategic role of Artificial Intelligence in modern Human Resources Management.
  • Identify high-value AI applications across the employee lifecycle.
  • Evaluate opportunities for using AI to improve HR efficiency and effectiveness.
  • Analyze how workforce data and AI can support better HR decision-making.
  • Apply predictive analytics concepts to workforce planning and talent management.
  • Improve talent acquisition and recruitment processes through AI-enabled solutions.
  • Use AI-supported analytics to strengthen performance management.
  • Identify opportunities for intelligent automation across HR processes.
  • Enhance employee experience through AI-enabled digital HR services.
  • Apply AI to identify skills gaps and support learning and development.
  • Evaluate AI applications for employee retention and workforce planning.
  • Assess algorithmic bias, privacy, fairness, and ethical risks in HR applications.
  • Establish appropriate governance and human oversight for AI-enabled HR decisions.
  • Develop performance measures for evaluating the business value of AI initiatives.
  • Build a practical roadmap for implementing AI across Human Resources.

Who Should Attend

This course is designed for HR executives, HR directors, Human Resources managers, Talent Management managers, Recruitment and Talent Acquisition leaders, Learning and Development managers, Performance Management professionals, Workforce Planning managers, and senior professionals responsible for organizational people strategy. It is also suitable for HR specialists, People Analytics professionals, Organizational Development teams, HR transformation leaders, digital transformation professionals, data and analytics teams, IT professionals supporting HR systems, and managers involved in workforce strategy and employee experience. The programme is particularly relevant to government and public-sector organizations, banks and financial institutions, oil and gas and energy companies, engineering and industrial organizations, telecommunications, healthcare, logistics, and large corporations seeking to modernize Human Resources through Artificial Intelligence, analytics, and intelligent automation.

Learning Outcomes

  • By the end of this course, participants will be able to:
  • Explain how Artificial Intelligence is changing the future of Human Resources.
  • Identify practical AI use cases across the HR lifecycle.
  • Assess organizational and HR readiness for AI adoption.
  • Analyze workforce data to generate actionable HR insights.
  • Interpret predictive analytics for workforce-related decisions.
  • Improve recruitment and talent acquisition using AI-enabled approaches.
  • Strengthen performance management through AI-supported analytics.
  • Identify HR processes suitable for intelligent automation.
  • Enhance employee experience through AI-enabled services and virtual assistants.
  • Use AI to identify skills gaps and support personalized learning.
  • Apply workforce analytics to improve talent retention and workforce planning.
  • Recognize bias, privacy, transparency, and fairness risks in AI-enabled HR decisions.
  • Establish appropriate governance and human oversight for AI applications in HR.
  • Measure the organizational value and performance impact of AI initiatives.
  • Develop an actionable AI strategy and implementation roadmap for Human Resources.

Course Outline

Course Outline

Day 1

Artificial Intelligence and the Future of Human Resources

  • Understanding Artificial Intelligence and its relevance to HR.
  • From traditional Human Resources to AI-enabled HR management.
  • The role of data in modern workforce decision-making.
  • AI across the employee lifecycle.
  • Identifying high-value AI opportunities in HR.
  • AI-driven transformation of HR roles and responsibilities.
  • Assessing organizational readiness for AI adoption.
  • Building a data-driven HR culture.
  • AI, workforce strategy, and organizational performance.
  • Practical Application: Identifying and prioritizing AI opportunities within an HR function.
Day 2

AI in Talent Acquisition and Recruitment

  • AI applications in workforce and talent planning.
  • Intelligent job analysis and skills identification.
  • AI-supported candidate sourcing and screening.
  • Matching candidate skills with job requirements.
  • Using AI-enabled analytics to support recruitment decisions.
  • Improving candidate experience through intelligent HR services.
  • Intelligent automation of recruitment processes.
  • Algorithmic bias and fairness in recruitment.
  • Human oversight in AI-supported hiring decisions.
  • Practical Application: Designing an AI-enabled recruitment process.
Day 3

AI in Performance, Talent and Workforce Management

  • AI-supported employee performance analysis.
  • Performance indicators and workforce analytics.
  • Predictive analytics for employee turnover and retention.
  • Identifying workforce skills and competency gaps.
  • AI applications in learning and development.
  • Personalized learning and development pathways.
  • Predictive workforce planning.
  • Forecasting future workforce and skills requirements.
  • AI-supported talent management and succession planning.
  • Practical Application: Analyzing a workforce scenario and developing AI-supported HR interventions.
Day 4

Employee Experience, Intelligent Automation and AI Governance

  • AI-enabled employee services and virtual assistants.
  • Improving employee experience and internal service delivery.
  • Automating repetitive HR processes.
  • Generative AI applications in Human Resources.
  • Using AI to support HR content, documentation, and knowledge management.
  • Employee data privacy and information protection.
  • Algorithmic bias, fairness, and transparency.
  • AI governance, accountability, and human oversight.
  • Managing AI-related risks in Human Resources.
  • Practical Application: Assessing AI risks and developing an HR AI governance framework.
Day 5

AI Strategy and Transformation in Human Resources

  • Building an AI strategy for Human Resources.
  • Identifying and prioritizing AI use cases.
  • Evaluating business value, cost, risk, and expected return.
  • Developing an AI-enabled HR operating model.
  • Building an implementation roadmap and transformation priorities.
  • Establishing KPIs for measuring AI impact in HR.
  • Managing organizational change and developing HR AI capabilities.
  • Strengthening collaboration between HR, technology, data, and business functions.
  • Scaling successful AI applications across the HR function.
  • Final Workshop: Developing an Integrated AI Strategy and Implementation Roadmap for Human Resources.

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