Status : Verified
| Personal Name | Melendres, Ronald Anthony C. |
|---|---|
| Resource Title | AI-driven microlearning through scenario building: future and impacts for newly promoted virtual managers |
| Date Issued | 02 June 2025 |
| Abstract | This study examined how AI-driven microlearning would shape the leadership development of newly promoted managers in fully virtual consulting firms over the next 2 to 3 years. Grounded in technology foresight, the study applied Prof. Glen Imbang’s Ten-Stage Scenario Building Model to explore multiple AI adoption pathways and their organizational implications. The scenarios address key uncertainties such as AI trust, regulatory constraints, and the balance between automation and human mentorship. The study identified key predictable variables, critical uncertainties, and scenario logics that shaped four distinct scenarios: AI-Optimized Leadership Development, Human-AI Hybrid Model, AI Hesitation and Virtual Leadership Gaps, and AI Adoption with Compliance Bottlenecks. The findings highlighted that while AI-based microlearning enhances training scalability and personalization, its effectiveness depends on cultural acceptance, governance frameworks, and alignment with leadership models. The study contributed a strategic foresight framework to guide virtual consulting firms in integrating AI for leadership development while preserving human-centered capabilities essential to long-term organizational success. |
| Degree Course | Master of Technology Management |
| Language | English |
| Keyword | Scenario building, Artificial intelligence, Leadership development, New manager training |
| Material Type | Thesis/Dissertation |
Preliminary Pages
318.48 Kb
Category : P - Author wishes to publish the work personally.
Access Permission : Limited Access