Role-Based Programme
RB1575

AI-Powered Quality Management System Administration

Intelligent QMS Governance, Documentation & Compliance Automation

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

Programme Objectives

  • Develop advanced capability to apply AI across Quality Management System administration, documentation, compliance, audits, CAPA, change control, and management review.
  • Use AI to organise and analyse policies, SOPs, work instructions, forms, quality records, audit evidence, deviations, CAPA, and QMS performance information.
  • Build repeatable AI-assisted workflows for controlled-document administration, approval tracking, periodic reviews, audit preparation, corrective-action follow-up, and reporting.
  • Apply AI to identify document inconsistencies, overdue actions, compliance gaps, recurring quality issues, and opportunities to improve QMS effectiveness.
  • Design responsible AI-enabled QMS administration workflows with appropriate controls for document integrity, traceability, access, approvals, compliance, auditability, and human oversight.

Tools covered

Generative AI AssistantsAI Search & ResearchDocument AISpreadsheet & Data AnalysisQMS Documentation ToolsQuality AnalyticsAudit & Compliance ToolsKnowledge Management AIReporting & Dashboard ToolsWorkflow Automation

Who should attend

  • QMS Administrators
  • Quality Management System Managers
  • Quality Systems Professionals
  • Quality Assurance Managers
  • Quality Managers
  • Document Control Professionals
  • Quality Compliance Professionals
  • Quality Auditors
  • CAPA Coordinators
  • Quality Engineers
  • Process Quality Professionals
  • Continuous Improvement Professionals
  • Quality Analysts
  • Management System Coordinators
  • QMS Administration Team Leads

Prerequisites & Participant Readiness

  • Working knowledge of Quality Management Systems, Quality Assurance, document control, compliance, or quality administration
  • Familiarity with SOPs, controlled documents, audits, CAPA, deviations, change control, or quality records
  • Basic proficiency with spreadsheets, documents, data interpretation, and workplace productivity applications
  • No previous AI course attendance required
  • No programming background required

TOC Modules

Concepts
  • Understanding Generative AI, Document AI, analytical AI, and workflow automation
  • Mapping AI opportunities across documentation, records, audits, CAPA, compliance, and management review
  • Understanding AI assistance versus authorised QMS and Quality Assurance decisions
  • Recognising risks involving inaccurate content, poor traceability, confidentiality, and uncontrolled changes
Practical activities
  • Mapping an existing QMS administration lifecycle
  • Comparing manual and AI-assisted QMS activities
  • Creating a QMS AI opportunity matrix

Scenarios

Controlled Document Change to QMS Implementation

Change Request → Impact Assessment → Document Review → AI-Assisted Revision → Approval → Controlled Release → Training Assignment → Evidence Capture → Effectiveness Review

Participants use AI-assisted techniques to manage a simulated QMS document change, analyse its impact, coordinate controlled revision and approval, assign required training, and maintain full traceability.

QMS Data to Continuous Quality Governance

Audit Findings + Deviations + CAPA + Document Status + Training Compliance + Quality Metrics → AI Analysis → Recurring Gaps → Priority Actions → Automated Follow-Up → Dashboard → Management Review

Participants design an AI-enabled QMS administration workflow that consolidates quality-system information, identifies recurring compliance and administration gaps, automates follow-up, and improves management visibility while retaining final QMS decisions with authorised professionals.

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