This module grounds executives in CRM fundamentals and how AI elevates engagement, personalization, and measurement across the customer lifecycle. You’ll connect CRM components with outcome metrics, surface near‑term AI opportunities, and examine privacy/security trade‑offs. A light introduction to graph‑based community modeling helps you visualize customer networks for segmentation and outreach.

Focus on the data foundations of AI for CRM: what to capture, how to integrate, and how to safeguard quality and governance. You’ll interpret outputs from predictive models (e.g., churn) and run a practical sentiment/voice‑of‑customer workflow—including multilingual considerations—to turn unstructured feedback into action.

Translate AI capabilities into engagement levers: personalization, assistants, and sales enablement. You’ll experiment with content/recommendation strategies, design and assess chatbot/voice‑assistant experiences, and apply LLM prompt design and specialization—all tied to revenue outcomes via lead scoring and cross/upsell.

Learn where automation moves the needle: dynamic pricing, revenue optimization, and fraud/security in customer interactions. You’ll estimate price responsiveness, design fraud‑prevention workflows with human‑in‑the‑loop review, and specify process KPIs to quantify efficiency and risk reduction.

Bring it all together into an executive‑ready plan. You’ll align AI initiatives with business goals using a Goal–Question–Metric (GQM) approach, produce a technology roadmap, and address change management, ethics, and risk so your AI‑CRM strategy is viable, governable, and future‑proof.