Role-Based Programme
RB1330

AI for Operational Quality & Compliance

Quality Intelligence, Control Assurance & Compliance Excellence

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Duration
16 Hours
Level
Intermediate
Delivery
Instructor-Led
Format
Capability Training

Programme Objectives

  • Develop practical AI capabilities for operational quality, compliance monitoring, control assurance, audit readiness, and corrective-action management.
  • Apply AI to analyse quality data, non-conformities, control failures, compliance exceptions, recurring issues, and operational risks.
  • Use AI to improve SOP and policy reviews, audit preparation, CAPA documentation, root-cause analysis, and compliance reporting.
  • Strengthen quality and compliance performance through risk-based prioritisation, evidence analysis, control monitoring, and continuous improvement.
  • Apply responsible AI practices related to regulatory information, sensitive operational data, accuracy, traceability, confidentiality, and human oversight.

Tools covered

Generative AI AssistantsAI Search & ResearchQuality Data AnalysisCompliance Monitoring SupportControl AnalysisAudit ReadinessRoot-Cause AnalysisCAPA AnalysisRisk & Exception AnalysisSOP & Policy ReviewOperational ReportingExecutive Summarisation

Who should attend

  • Operational Quality Managers
  • Quality Assurance Managers
  • Quality Control Professionals
  • Compliance Managers
  • Operational Compliance Professionals
  • Quality Analysts
  • Compliance Analysts
  • Process Quality Professionals
  • Internal Control Professionals
  • Audit Coordination Professionals
  • Operations Managers
  • Risk & Compliance Professionals
  • Business Excellence Professionals
  • Process Owners
  • Quality & Compliance Leaders

Prerequisites & Participant Readiness

  • Experience in quality assurance, compliance, operations, internal controls, process management, or audit coordination
  • Familiarity with SOPs, policies, quality metrics, non-conformities, audits, controls, and corrective actions
  • Basic familiarity with Generative AI tools is recommended
  • Ability to interpret operational, quality, and compliance information
  • No programming knowledge required

TOC Modules

Concepts
  • Understanding Generative AI, reasoning models, multimodal AI, and AI assistants
  • Exploring AI applications across quality monitoring, compliance, audits, controls, and reporting
  • Understanding how AI differs from QMS, GRC, audit, workflow, and analytics systems
  • Recognising hallucinations, incomplete evidence, and limitations in compliance-related decisions
Practical activities
  • Mapping quality and compliance activities to practical AI use cases
  • Identifying high-value versus high-risk AI applications
  • Comparing traditional and AI-assisted quality workflows

Scenarios

Recurring Quality Failure to CAPA Plan

Quality Finding → Evidence Review → Severity Assessment → Root-Cause Analysis → Control Gap → Corrective Action → Preventive Action → Effectiveness Check

Participants use AI to analyse a simulated recurring quality issue, identify probable systemic causes, create a structured CAPA plan, and define evidence for verifying improvement.

Audit Findings to Compliance Improvement Roadmap

Audit Findings → Requirement Mapping → Control Review → Risk Prioritisation → Evidence Gaps → Remediation Actions → Governance → Compliance Roadmap

Participants use AI to analyse simulated audit findings, identify high-risk control weaknesses, prioritise remediation actions, and develop a structured quality and compliance improvement roadmap.

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