Role-Based Programme
RB1331

AI for Operational Quality & Compliance

Advanced Quality Intelligence, Compliance Monitoring & Risk Control

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

Programme Objectives

  • Develop advanced capability to apply AI across operational quality, compliance monitoring, audits, controls, documentation, and continuous improvement.
  • Use AI-assisted analysis to identify quality deviations, process non-conformities, control weaknesses, recurring compliance issues, and operational risks.
  • Apply AI to SOP reviews, audit preparation, evidence analysis, CAPA management, risk assessment, quality reporting, and compliance tracking.
  • Use AI-assisted analytics to improve quality consistency, control effectiveness, audit readiness, corrective-action closure, and management visibility.
  • Build responsible AI-enabled Quality and Compliance workflows with strong governance, traceability, validation, confidentiality, and human oversight.

Tools covered

Generative AI AssistantsAI Search & ResearchQuality AnalyticsCompliance MonitoringAudit AnalyticsRoot Cause AnalysisCorrective & Preventive Action AnalysisRisk & Control MappingSOP AnalysisException DetectionQuality KPI DashboardsDocumentation IntelligenceWorkflow AutomationAI AgentsDecision-Support Tools

Who should attend

  • Operational Quality Managers
  • Quality Assurance Managers
  • Quality Control Professionals
  • Compliance Managers
  • Operational Compliance Professionals
  • Quality Analysts
  • Internal Control Professionals
  • Audit Coordination Professionals
  • Process Compliance Managers
  • Operational Risk Professionals
  • Continuous Improvement Professionals
  • SOP & Documentation Professionals
  • Operations Managers
  • Governance & Control Professionals
  • Leaders Responsible for Operational Quality & Compliance

Prerequisites & Participant Readiness

  • Experience in quality, compliance, operations, audit coordination, process control, or operational risk
  • Familiarity with SOPs, audits, non-conformities, CAPA, controls, quality metrics, and compliance reviews
  • Basic awareness of Generative AI and common business applications
  • Comfort working with operational, quality, policy, control, and audit information
  • No programming knowledge required

TOC Modules

Concepts
  • Understanding Generative AI, reasoning models, analytics, automation, and AI agents
  • Exploring AI applications across quality, compliance, audit, controls, and documentation
  • Distinguishing AI-assisted compliance work from autonomous compliance decisions
  • Understanding hallucinations, evidence risk, confidentiality, and human accountability
Practical activities
  • Mapping AI opportunities across Quality and Compliance workflows
  • Identifying activities suitable for augmentation, automation, or continued human ownership
  • Creating an AI opportunity map for Operational Quality and Compliance teams

Scenarios

Repeated Quality Failures to CAPA & Control Improvement Plan

Quality Data → Non-Conformities → Root Cause → Control Gaps → CAPA → Effectiveness Review → KPI Monitoring → Governance

Participants use AI to analyse recurring quality failures, identify systemic root causes and weak controls, build corrective and preventive actions, and establish measurable quality monitoring.

Audit Findings to AI-Enabled Compliance Management Model

Audit Findings → Requirement Mapping → Evidence Gaps → Control Assessment → Corrective Actions → Risk Prioritisation → Compliance Dashboard → Review Cadence

Participants use AI to consolidate audit findings, trace them to requirements and controls, identify compliance gaps, prioritise remediation, and build a governed compliance-monitoring operating model.

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