Course Format and Delivery
Delivery Method: LiveOnline
Schedule: 3 sessions of 4.5 hours
Cost: $1,495 USD
All sessions are delivered live by an expert instructor in a fully interactive online environment.
*20% off for group bookings when booking 3 or more attendees from the same organization on the same course dates in the same transaction.
About this course
Quickly learn how to apply generative AI in your L&D job role. Use AI for content development, training plans, skills gap analysis, LMS integration, learner engagement strategies, and much more.
This two-day class is designed to supercharge the operational efficiency of anyone who works in enterprise learning, training, talent development, or corporate education. With fast-paced lessons and hands-on practice, you will learn to integrate AI in L&D work, from personalized content creation and adaptive learning pathways to data-driven performance analysis and engagement strategies. You will also receive guidance on strategic planning for AI adoption in L&D, address ethics and data privacy considerations, and prioritize human-centric learning experiences for your learners.
By the conclusion of the workshop, you’ll be ready to harness generative AI to assist with instructional design, LMS reporting, learner engagement, and optimized learning outcomes. This class is a must-attend for L&D professionals who need to lead the charge in talent innovation.
What you will earn
This course will contribute 14 PMI® professional development units (PDUs) towards your chosen certification (12 Ways of Working and 2 Business Acumen).
What you will learn
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Use AI for better skills gap analysis, needs assessment, competency mapping, and SME collaboration.
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Develop AI-assisted learning content, assessment content, module descriptions, and much more.
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Quickly generate personalized learning pathways and curriculum taxonomies.
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Better align training objectives with business goals and career development needs with AI assistance.
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Integrate AI tools and analysis with existing LMS and education platforms.
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Increase the quality and frequency of your stakeholder communication with AI while maintaining a human touch.
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Parse engagement metrics and learner-generated content for insights and recommendations that weren’t available before.
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Apply AI in evaluating training effectiveness and learner engagement.
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Address ethical and privacy considerations in AI-enabled learning environments.
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Use AI task automation to cultivate a better organizational learning culture.
What you will need
To get the most out of this course, it is recommended that participants have relevant experience working in a learning and development context.
This course is great for
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Training and Development Managers
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Instructional Designers and Learning Designers
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Chief Learning Officers and Directors of Learning
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Corporate Trainers and Technical Trainers
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eLearning Developers and Content Developers
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HR and Talent Development Directors
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Learning and Development Specialists
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Organizational Development Managers
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Learning Management Systems Administrators
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Facilitators and Educators in Corporate Settings
Topics Covered
Section 1: Introduction to Generative AI in Learning & Development
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AI and its impact on the L&D function
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Aligning course expectations and outcomes
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The intersection of AI and adult learning principles
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Navigating the course: Tools, resources, and collaboration platforms
Section 2: Foundations of AI in L&D
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Understanding the mechanics of generative AI models
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Identifying key AI technologies relevant to L&D
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Limitations of AI and how to mitigate them
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Differentiating AI myth and reality
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Strategic considerations for adopting AI in L&D
Section 3: AI-Driven Content Creation and Curriculum Design
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Techniques for automating content generation with AI
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Principles of instructional design applied to AI-generated content
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Customizing AI tools for diverse learning styles
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Enhancing curriculum development with AI insights
Practice: Creating a mini-module using AI-generated content
Practice: Quality assurance in AI-generated learning materials
Section 4: Personalization and Adaptive Learning Pathways
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Using AI to create personalized learning experiences
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Integrating learner feedback and performance data into AI recommendations
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Ethical considerations in personalized learning
Practice: Design adaptive learning pathways with AI assistance
Section 5: Data-Driven Insights and Learner Analytics
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Leveraging AI for advanced learner analytics and insights
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Tools and techniques for capturing and analyzing learning data
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Translating data into actionable teaching and learning strategies
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Privacy and security best practices for learner data
Group practice: Interpreting AI-generated analytics to inform L&D decisions
Section 6: Integrating AI with LMS and EdTech Platforms
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Overview of AI integration capabilities in popular LMS and EdTech platforms
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Technical considerations for AI integration: APIs, plugins, and custom development
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Accessing and analyzing LMS data with an AI agent
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Developing an integration roadmap for your LMS
Practice: Sandbox with AI tools using LMS data
Section 7: Enhancing Learner Engagement with AI
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AI-driven strategies for increasing learner engagement and motivation
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Using AI for more compelling gamification, simulations, and interactive content
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How AI can assist with personalized feedback and support
Practice: Use an AI agent to design an AI-driven learner engagement campaign
Practice: Maintaining human touch in AI-augmented learning
Section 8: AI for Talent Development and Skills Gap Analysis
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How to use AI to more quickly identify organizational talent and skills gaps
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Using predictive models for future skills and competency needs
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Aligning AI insights with talent development strategies
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Measuring the impact of AI-driven talent development initiatives
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Prioritizing alignment with organizational goals
Practice: Use AI to scan large data sources, identify skills gaps and recommendations, and create a talent development plan
Section 9: Ethical and Privacy Considerations in AI-assisted Work
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Key ethical considerations for using AI in learning contexts
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Navigating data privacy laws and regulations in AI applications
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Balancing personalization with privacy
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Developing an ethical AI use policy
Practice: Identifying ethical concerns and solutions in AI-assisted learning scenarios
Section 10: Developing Your AI-Enabled L&D Strategy
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Assessing your organization's readiness for AI in L&D
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Identifying strategic AI opportunities in your L&D function
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Roadmapping your AI integration journey
Practice: Build an AI adoption strategy and set SMART goals
Section 11: Course conclusion: Preparing for the Future
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Emerging AI technologies and their potential in L&D
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Future-proofing your L&D strategy with AI
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Action planning and final Q&A
Questions about this Course?
Phone: 1-800-373-7028
Email: info-us@softed.com
We'd love to have the opportunity to discuss how we can assist your business.