Role-Based Programme
RB1259

AI for Customer Support & Service

Advanced Support Intelligence, Resolution Automation & Customer Experience Excellence

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Duration
32 Hours
Level
Advanced
Delivery
Instructor-Led
Format
Capability Development

Programme Objectives

  • Develop advanced capability to apply AI across customer support, service requests, troubleshooting, escalations, knowledge management, quality monitoring, and service improvement.
  • Use AI-assisted analysis to understand customer intent, urgency, sentiment, recurring issues, service risks, and resolution opportunities.
  • Apply AI to improve ticket triage, response quality, troubleshooting, escalation handling, knowledge retrieval, documentation, and agent productivity.
  • Use AI-assisted analytics to strengthen first-contact resolution, response time, SLA performance, customer satisfaction, service consistency, and operational efficiency.
  • Build responsible AI-enabled Customer Support workflows with strong privacy, security, validation, escalation controls, and human oversight.

Tools covered

Generative AI AssistantsAI Search & ResearchTicket ClassificationCustomer Sentiment AnalysisKnowledge ManagementTroubleshooting SupportRoot Cause AnalysisSLA IntelligenceConversation SummarisationCustomer Communication SupportQuality MonitoringSupport AnalyticsWorkflow AutomationAI AgentsDecision-Support Tools

Who should attend

  • Customer Support Managers
  • Customer Service Managers
  • Customer Support Team Leaders
  • Service Desk Managers
  • Customer Support Specialists
  • Technical Support Professionals
  • Customer Service Executives
  • Helpdesk Professionals
  • Support Operations Professionals
  • Customer Experience Professionals
  • Escalation Managers
  • Support Quality Analysts
  • Knowledge Management Professionals
  • Customer Support Analysts
  • Leaders Responsible for Customer Support & Service Operations

Prerequisites & Participant Readiness

  • Experience in customer support, customer service, helpdesk, service operations, technical support, or customer experience
  • Familiarity with tickets, SLAs, escalations, troubleshooting, customer communication, and service metrics
  • Basic awareness of Generative AI and common business applications
  • Comfort working with customer conversations, support records, and service information
  • No programming knowledge required

TOC Modules

Concepts
  • Understanding Generative AI, reasoning models, automation, and AI agents
  • Exploring AI applications across support intake, diagnosis, resolution, communication, and analytics
  • Distinguishing AI-assisted support from fully autonomous customer service
  • Understanding hallucinations, customer-data sensitivity, operational risk, and human accountability
Practical activities
  • Mapping AI opportunities across the Customer Support lifecycle
  • Identifying activities suitable for augmentation, automation, or continued human ownership
  • Creating an AI opportunity map for Customer Support teams

Scenarios

High Ticket Volume to AI-Enabled Support Operations

Ticket Intake → Intent Classification → Priority → Knowledge Retrieval → Guided Resolution → Escalation → SLA Monitoring → Support Analytics

Participants use AI to analyse a high-volume support environment, improve ticket triage and resolution workflows, introduce controlled automation, and create a scalable support operating model.

Recurring Customer Complaints to Service Improvement Plan

Customer Complaints → Sentiment Analysis → Issue Clustering → Root Cause → Support Quality → Knowledge Gaps → Corrective Actions → Customer Experience Metrics

Participants use AI to identify recurring customer complaints, determine root causes, improve support quality and knowledge, and create a measurable customer-service improvement roadmap.

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