TRAINING OVERVIEW

This course empowers professionals to harness AI tools and sentiment analysis technologies to decode stakeholder emotions, expectations, and engagement levels across communication channels. Participants will learn to apply natural language processing (NLP), machine learning (ML), and conversational AI to improve stakeholder relationship strategies, detect early signs of dissatisfaction, and build more transparent, data-driven communication plans.

TRAINING TOPICS

• Introduction to stakeholder sentiment analysis using AI
• Natural Language Processing (NLP) for emotional tone detection
• Real-time AI monitoring of stakeholder communications
• Machine Learning for predictive stakeholder behavior modeling
• Social listening tools and AI integration
• Conversational AI and chatbots for engagement
• Speech and text analytics in internal and external communication
• Ethical AI and bias mitigation in stakeholder analysis
• Communication strategy optimization with AI-driven feedback loops
• Tools overview: MonkeyLearn, Talkwalker, ChatGPT, Sprinklr

BY THE END OF THIS TRAINING COURSE, DELEGATES WILL BE ABLE TO

• Use AI to identify and monitor key stakeholder sentiment trends
• Apply NLP to extract emotions, topics, and intent from messages
• Integrate AI tools into stakeholder engagement workflows
• Analyze real-time communications to adapt strategies effectively
• Use ML models to predict stakeholder churn or advocacy
• Create AI-informed reports for leadership communication planning
• Design automated engagement channels for feedback collection
• Apply ethical considerations in data handling and communication

TRAINING IS TAILORED TO

• Communications Directors and Managers
• Stakeholder Engagement Specialists
• Project and Program Managers
• Public Relations and CSR professionals
• Change Management Consultants
• Customer Success and Service Leaders

TRAINING METHODOLOGY

The program blends expert-led instruction, practical tool demonstrations, NLP labs, group exercises, and role-based simulations. Participants engage in hands-on practice using AI-powered sentiment platforms and build a comprehensive communication dashboard by the end of the course.

DAY ONE: FOUNDATIONS OF STAKEHOLDER AI & NLP

• The role of AI in modern stakeholder management
• Stakeholder mapping and classification frameworks
• Core concepts of NLP and sentiment lexicons
• Overview of AI tools for tone and intent recognition
• Case study: Stakeholder sentiment crisis scenarios
• Lab: Annotating stakeholder texts for emotion classification

DAY TWO: REAL-TIME SENTIMENT MONITORING

• Building real-time sentiment dashboards
• Capturing stakeholder input from multiple channels
• Tools: Talkwalker, Brandwatch, MonkeyLearn demos
• Interpreting results with confidence scoring
• Lab: Configure a stakeholder sentiment alert system
• Activity: Create a sentiment escalation matrix

DAY THREE: AI IN STAKEHOLDER COMMUNICATIONS

• Generative AI for drafting tailored communication
• Using AI to respond empathetically to feedback
• Case Study: Chatbot vs. human response effectiveness
• Lab: Train a conversational AI to answer stakeholder FAQs
• AI-enhanced reporting to leadership
• Exercise: Communication scenario planning with AI insights

DAY FOUR: PREDICTION, INSIGHT, AND ENGAGEMENT

• Predicting stakeholder loyalty and churn using ML models
• Heatmapping stakeholder issues and urgency levels
• Lab: Apply regression to stakeholder engagement history
• Aligning sentiment trends with project goals
• Creating actionable insights from raw sentiment data
• Tools: Sprinklr, Power BI + AI integration

DAY FIVE: ETHICS, STRATEGY & IMPLEMENTATION

• Transparency and bias in sentiment algorithms
• Building an AI-powered communication playbook
• Final project: Strategy presentation on stakeholder AI integration
• Simulated feedback loops and communication refinement
• Final evaluation and group reflection
• Certificate award and next steps