Master change leadership with our Singapore-focused module combining classical models (Kotter, Lewin, ADKAR) and AI-driven tools. Learn stakeholder engagement, digital transformation readiness, and data-powered strategies to lead effective organisational change.
Overview
Change Management focuses on managing and leading organizational change, blending classical change management theories with AI-driven strategies. Students explore frameworks for effective change (e.g. Kotter’s 8 Steps, Lewin’s Change Model, ADKAR) alongside modern digital transformation practices. Equal emphasis is placed on people-centric skills (stakeholder engagement, communication, overcoming resistance) and AI tools that facilitate change. By integrating AI analytics and automation, students learn to plan and implement changes more efficiently, using data to anticipate challenges and tailor change initiatives. This module prepares learners to champion change in a business world where technology and AI are continuously driving organizational evolution.
The Details
FOR SKILLSFUTURE CLAIMS
Registered Title: (Change Management
(Classroom and Asynchronous e-learning))
TPGateway Code:
total hours
53:00
Mode of Learning
On Campus
Curriculum
Course Duration
SSG Approved Training & Assessments Hours:53:00Trainer Facilitated Hours (On Campus/Virtual):32:00Self-Directed E-learning Hours:04:00Assignment Hours:16:00Assessment Hours:01:00
Programme Objectives
Upon completion of this module, students will be able to:
Explain key change management theories and models, and apply them to business scenarios.
Develop comprehensive change management plans (including communication and training) for business initiatives.
Leverage AI tools (e.g. analytics, chatbots) to assess organizational readiness, monitor change progress, and address resistance.
Analyze employee feedback and performance data to refine change strategies and improve adoption rates.
Demonstrate skills to lead digital transformation projects, balancing human factors with AI-driven insights.
Learning Outcome:ChatGPT or similar GPT-based assistants – to draft change announcements, training materials, and FAQs for employees, ensuring clear and consistent communication.
Stakeholder analysis and engagement strategies during change
Learning Outcome:Survey and Sentiment Analysis Tools (e.g. Qualtrics with AI sentiment analysis) – to collect employee feedback and analyze sentiment toward changes, allowing early detection of resistance or issues.
Communication planning and managing resistance to change
Learning Outcome:AI-powered Chatbots (internal use) – for employee support during transitions (answering common questions about new systems or policies), providing 24/7 change helpline functionality.
Learning Outcome:Microsoft Power BI / Tableau – for visualizing change KPIs (e.g. productivity, adoption rates) and real-time dashboards to monitor the impact of change initiatives.
AI in Change Management: Using data analytics and predictive modeling to guide change; AI-based employee sentiment analysis to gauge morale; chatbots and NLP for change communication; digital adoption platforms to support technology rollouts
Learning Outcome: Predictive Analytics Platforms – to forecast outcomes of change (e.g. identifying departments at risk of low adoption), enabling proactive interventions (examples include IBM Watson Analytics or SAS Advanced Analytics for predictive modeling).
