AI-Augmented Learning Leader

Why Choose Garranto Academy for Your AILL Training?

Garranto Academy delivers industry-leading AILL training with hands-on labs, practical tools, and globally aligned capability frameworks.

Course Overview:

The AI-Augmented Learning Leader (AILL) program prepares modern Learning & Development professionals to become Capability Architects who design, automate, and measure intelligent learning ecosystems. Moving beyond traditional compliance-driven L&D, the program builds expertise in capability intelligence—where learning is adaptive, data-driven, and continuously measurable. Participants will gain hands-on skills in creating skill matrices, automating learning workflows, developing capability dashboards, and implementing AI-driven credentialing systems aligned with Education 4.0, WEF Future of Work Skills, UNESCO AI Literacy, SFIA, and OpenBadge 3.0 standards. By the end of the program, learners will be equipped to lead enterprise transformation and build trusted, scalable, AI-powered learning systems that accelerate workforce capability and future-readiness.

What You'll Learn in Our AILL Certification Course?

Course Objectives:

Upon successful completion of this course, learners will be able to:

• Redefine L&D as a reflexive, AI-enabled capability engine focused on measurable outcomes.

• Build multi-axis skill matrices across sectors, functions, and emerging technologies.

• Design AI-driven learning automation and continuity systems integrated into business workflows.

• Develop data-driven credentialing models with modular, verifiable proof-of-skill evidence.

• Visualize learning impact using capability dashboards and reflex analytics for leadership insights.

• Enable organizations to transition from traditional training models to adaptive, intelligence-driven learning ecosystems.

Prerequisites

• 3+ years L&D or HR experience

• Knowledge of digital learning systems

• Strong English communication skills

• Comfortable using AI tools

Course Outlines:

Module 1: Capability Intelligence Framework Design

• Objective: Redefine L&D as a reflexive, AI-enabled capability engine

• Core Learnings:

• Capability as a loop: Learn → Apply → Reflect → Credential → Evolve

• Cognitive reflex vs content consumption

• Embedding future skills (creative thinking, tech fluency, systems thinking)

• Studio: Capability Reflex Diagnostic Sprint

• Deliverable: Role-Reflex Map for 3 Job Families

Module 2: Multi-Axis Skill Matrix Design (Sector × Function × Tech)

• Objective: Create a living skills matrix aligned to domain needs and

transformation priorities

• Core Learnings:

• Use AI (ChatGPT/Galileo) to generate skill grids by role clusters

• Layer in reflex types (e.g. Cognitive, Ethical, Systemic)

• Include frontier tech exposure: AI, Blockchain, XR, Cybersecurity, Digital Twins, Quantum

• Studio: Skill Matrix Builder Lab

• Deliverable: Reflex-Based Skill Matrix (Sector Function×Tech)

Module 3: Intelligent Learning Automation & Knowledge Continuity

• Objective: Automate and personalise learning delivery across workflows

• Core Learnings:

• AI-prompted learning nudges, personalized suggestions

• Auto-learning flows (e.g., from KPI drops or performance feedback)

• Knowledge flow and memory continuity across GCC hubs

• Studio: Learning Trigger Flow Sprint

• Deliverable: Workflow Learning Flow (Make.com / Notion AI) + Memory Continuity Blueprint

Module 4: AI-Driven Credentialing & Skill Validation

• Objective: Shift from attendance-based certification to verified proof-of-skill

• Core Learnings:

• Modular credentials based on evidence: reflex, outcome, proof

• Micro-badging architecture using OpenBadge schema

• Blockchain or GitHub-based verification (optional demo layer)

• Studio: Credentialing Architecture Design Lab

• Deliverable: Credential Logic Map + Sample Badge Design + Verification Path

Module 5: Capability Dashboards and Reflex Analytics

• Objective: Visualise how learning fuels performance and decision quality

• Core Learnings:

• Reflex Index: tracking growth of applied skill, not just time spent

• Dashboards for capability velocity, business function alignment

• L&D visibility for execs via Power BI, Tableau GPT, or Notion roll-ups

• Studio: Reflex Intelligence Dashboard Sprint

• Deliverable: Capability Dashboard with 3 Role-Based Reflex KPIs

Module 6: Capstone: Proof of Capability Intelligence (PoCI)

• Challenge: Build a complete learning–capability system for a function/team of

your choice

• Deliverables:

• Capability Role Map

• Multi-Axis Skill Matrix

• Auto-Triggered Learning Flow

• Reflex Dashboard

• Credential System Blueprint

Course Outcomes:

Upon completing the "AI-AUGMENTED LEARNING LEADER" course, participants will:

• Build AI-augmented learning ecosystems that evolve with organizational needs.

• Use AI and analytics to personalize, automate, and measure enterprise learning impact.

• Redefine L&D functions into capability intelligence systems that enhance workforce agility.

• Implement AI-driven credentialing frameworks with verifiable, modular skill proof.

• Design multi-layer capability models integrating skills, roles, and performance indicators.

• Develop reflexive learning workflows that support continuous capability development.

• Create capability dashboards and analytics reports for leadership decision-making.

Key Benefits of Becoming an AI-Augmented Learning Leader

Becoming an AILL equips you to build intelligent, data-driven learning ecosystems that accelerate workforce capability and performance

How AI-Augmented Learning Can Transform Your Organization

AI-powered learning shifts organizations from traditional training models to adaptive, reflexive, and data-intelligent capability ecosystems