OVERVIEW
Artificial Intelligence (AI) is rapidly transforming the way organizations design, deliver, and evaluate training programs. For training managers, understanding how to effectively integrate AI into learning and development (L&D) strategies is no longer optional—it is essential for driving engagement, personalization, and measurable learning outcomes.
This two-day virtual program equips training managers with foundational knowledge and practical tools to incorporate AI into corporate training environments. Participants will explore generative AI, AI-driven curriculum design, data analytics, LMS integration, learner engagement strategies, and ethical considerations.
Through structured modules, discussions, and practical applications, participants will learn how to leverage AI responsibly to enhance instructional design, improve learner experiences, and generate meaningful insights from training data. By the end of the program, participants will be able to confidently apply AI tools to modernize their training strategies while maintaining ethical and data privacy standards.
By the end of this program, participants will be able to:
- Utilize AI to conduct skills gap analyses, needs assessments, and competency mapping.
- Create AI-enhanced learning content and structured curriculum frameworks.
- Design personalized learning pathways using AI tools.
- Integrate AI solutions with existing Learning Management Systems (LMS) and educational technologies.
- Analyze learner data to derive actionable insights and recommendations.
- Address ethical, privacy, and governance considerations in AI-powered learning environments.
2 Days (Virtual Delivery)
Typically conducted from 9.00am – 5.00pm each day.
The duration and delivery format can be customized to meet organizational requirements.
- Training Managers
- Learning & Development (L&D) Professionals
- HR & Talent Development Managers
- Instructional Designers
- Corporate Trainers
- Professionals responsible for workforce development and learning strategy
PROPOSED OUTLINE/AGENDA
DAY 1 (9am to 5pm)
- Icebreaker activity
- Introduction to trainer
- Program objectives and expectations
- Overview of generative AI and machine learning concepts
- Applications of AI in corporate training
- Opportunities and limitations of AI adoption in L&D
- Basics of prompting techniques for training professionals
- Using AI to support instructional design processes
- Generating learning objectives and structured module outlines
- Enhancing curriculum with AI-generated insights
- Ensuring quality, alignment, and instructional integrity
- Capturing and analyzing educational data
- Deriving actionable insights from learner interactions
- Applying analytics to improve learning strategies
- Ensuring privacy and security in learner data handling
- Understanding LMS data and system capabilities
- Techniques for accessing and interpreting LMS insights
- Roadmap for smooth AI integration into learning platforms
- Overcoming common implementation challenges
- Summary and reflections
- Q&A session
DAY 2 (9am to 5pm)
- Recap of Day 1 learning
- Sharing insights and applications
- Enhancing learning experiences using AI tools
- Personalization strategies for learner engagement
- AI-supported feedback and adaptive learning methods
- Predictive modelling for future skills and competencies
- AI-assisted competency mapping
- Evaluating the effectiveness of AI-driven talent initiatives
- Managing personalization while ensuring data privacy
- Establishing ethical AI usage guidelines
- Crafting internal AI governance policies
- Assessing organizational readiness for AI implementation
- Recap of generative AI’s role in modern L&D
- Key strategies for long-term AI integration
- Building a future-ready learning ecosystem
- Developing a simple AI implementation roadmap
- Key takeaways and action planning
- Program evaluation
- Final Q&A and wrap-up
PROGRAM METHODOLOGY
- Interactive Lectures – Foundational understanding of AI in L&D
- Demonstrations – Practical walkthroughs of AI tools
- Group Discussions – Sharing challenges and best practices
- Case-Based Learning – Real-world corporate learning scenarios
- Hands-On Activities – Applying AI to curriculum and analytics tasks
- Reflection & Action Planning – Translating insights into workplace implementation
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