Application of AI in Learning and Development (L&D)

Course Objectives

• Understand AI’s role in enhancing instructional design within L&D
• Explore practical AI tools for each phase of instructional design
• Apply AI to streamline content creation, learner analysis, and engagement
• Develop a framework for integrating AI into L&D to improve efficiency and outcomes
• Create a practical action plan for using AI to meet organizational L&D goals

Target Audience

This course is ideal for L&D professionals, instructional designers, HR leaders, and educators who want to integrate AI into their instructional design processes to create effective, scalable, and personalized learning experiences.

Methodology

The Course content will be delivered through:

Game-Based Learning: Interactive, scenario-based games simulating real-world AI applications to demonstrate productivity improvement strategies.

Facilitative Methods: Guided group discussions and breakout sessions, enabling participants to collaboratively explore AI utilization for productivity.

Dynamic Debriefing: After each module, a structured reflection to help participants consolidate learning, identify practical applications, and develop actionable insights.

Course Modules

Day 1: Foundations of AI in Instructional Design

Module 1: Introduction to AI in L&D and Instructional Design Frameworks

Description:
This module provides an overview of AI’s potential to support instructional design (ID) in L&D. Participants will learn about key instructional design frameworks (such as ADDIE and SAM) and identify where AI tools can accelerate each phase, from analysis to implementation.

Learning Objectives:

• Understand the basics of AI and its application in L&D
• Learn key instructional design frameworks (ADDIE and SAM)
• Identify how AI tools align with different phases of instructional design

Module 2: Analysis Phase – Using AI for Needs Assessment

Description:
In the analysis phase, participants will explore AI tools that gather and interpret data to assess learning needs. They will learn to use AI for surveys, data analysis, and learner profiling, ensuring that learning objectives align with real needs.

Learning Objectives:

• Use AI to gather and analyze data for needs assessments
• Explore tools that support learner profiling and skill gap analysis
• Apply AI insights to establish relevant, data-driven learning objectives

Module 3: Design Phase – AI for Content Curation and Storyboarding

Description:
This module focuses on how AI can support the design phase by curating relevant content and generating course outlines. Participants will learn to use AI to source up-to-date information, build storyboards, and structure course materials.

Learning Objectives:

• Use AI tools to curate content and source learning materials efficiently
• Apply AI to create and organize course outlines and storyboards
• Develop design templates that are adaptable to learners’ needs

Module 4: Development Phase – AI-Assisted Content Creation

Description:
Participants will explore AI-driven tools that speed up content creation, such as video generation, automated text summarization, and interactive quiz creation. They will learn how to apply these tools to produce engaging content quickly.

Learning Objectives:

• Use AI tools for rapid content development, such as videos and quizzes
• Apply text-to-speech, summarization, and multimedia tools to enrich content
• Integrate interactive elements using AI to boost learner engagement