• Understand key AI concepts (Machine Learning, NLP, and data analytics) and how they apply to customer service.

• Design and deploy a functional AI chatbot with at least 3 customer service scenarios, including escalation paths.

• Analyze customer feedback using sentiment analysis tools and report insights with ≥ 85% accuracy.

• Implement personalized automated communication (email, chat, notifications) using customer segmentation.

• Integrate AI into omnichannel service platforms, ensuring consistent and seamless customer experience.

• Measure service performance using AI-driven KPIs, including response time, customer satisfaction, and resolution rates.

• Apply ethical standards and data privacy principles in managing customer data and AI decision-making.

1. Customer Service Professionals looking to enhance service quality through technology

2. CRM & Customer Experience (CX) Teams focused on personalization and retention

3. Digital Communication Officers managing multi-channel platforms

4. IT Support / Developers building AI-based customer interaction tools

5. Trainers and Managers preparing teams for AI transformation in customer care

6. Professionals pursuing national or international certification in Customer Service Excellence, Digital Service, or AI Strategy

Module 1 – Introduction to AI in Customer Communication

• Role of AI in modern customer engagement

• Core technologies: NLP, ML, Predictive Analytics

• Overview of customer experience transformation

Module 2 – Building AI Chatbots

• Understanding intents, entities, and dialogue flow

• Creating customer service chatbots with tools (e.g., ChatGPT, Dialogflow)

• Escalation to human agents and fallback mechanisms

Module 3 – Sentiment Analysis & Feedback Interpretation

• Basics of sentiment analysis and text classification

• Tools for processing customer feedback

• Reporting actionable insights from AI analytics

Module 4 – Automated & Personalized Communication

• AI-driven email/chat/message automation

• Behavioral and demographic segmentation

• Designing tailored customer journeys using AI

Module 5 – Omnichannel AI Integration

• Principles of omnichannel service

• Integrating chatbots and AI into websites, apps, WhatsApp, etc.

• Case studies of successful omnichannel AI deployment

Module 6 – Ethics, Compliance & Data Privacy

• Managing customer data responsibly

• Avoiding bias in AI algorithms

• Regulatory frameworks: GDPR, Indonesia’s PDP Law

Module 7 – AI Performance Metrics & Service Improvement

• Defining KPIs: Response time, CSAT, NPS, automation rate

• Real-time monitoring using AI dashboards

• Evaluating impact and continuous improvement