Training course · ChatGPT · Quality Management

ChatGPT for Quality Management Teams

Use ChatGPT safely and productively at work: projects, custom GPTs, data analysis, Canvas and privacy settings in team workspaces.

Duration
1 day (7 hrs)
Format
Online or on-site
Language
German or English
Participants
open dates or exclusive for your team
Certificate
Certificate of attendance

Overview

This course connects ChatGPT with the everyday processes of Quality Management. Participants work on realistic scenarios and leave with prompts, workflows and checklists they can use straight away.

For many business teams, ChatGPT is the first AI tool they use every day – yet there is a methodical gap between asking the odd question and achieving real productivity gains. In this hands-on day you learn to apply ChatGPT deliberately to recurring work: drafting and editing text, summarising documents, analysing spreadsheets and structuring decision papers. You work with Projects that keep files and instructions together, with Canvas for reworking longer documents, and with data analysis for Excel and CSV files. Every exercise is based on genuine tasks from your own function.

The second focus is scale and responsibility. You build a custom GPT that knows your templates, tone of voice and review rules, and that colleagues across the workspace can use. We also clarify which data belongs in ChatGPT and which does not, how Team and Enterprise workspaces differ from personal accounts, and which settings matter for model training, memory and sharing. You leave with a personal prompt library, a working GPT and clear ground rules for using ChatGPT responsibly across your organisation.

Quality management depends on clean documentation, systematic analysis and rigorous follow-up of actions. Generative AI can relieve quality teams exactly there: AI assistants create and revise procedures, prepare audits, analyse complaints, support 8D reports and FMEA and compare documents with standard requirements such as ISO 9001 or IATF 16949. Automation sends reminders about action deadlines, evaluates inspection data and consolidates supplier ratings. That leaves more time for root cause work, process improvement and collaboration with production and engineering. AI output must not replace conformity with standards; it needs expert review and must enter the management system through controlled processes. When document control and approval workflows are respected, AI becomes a reliable tool for quality and efficiency.

The course is delivered live – either online in a virtual classroom or on-site in our training rooms in Munich, Salzburg, Berlin, Augsburg, Hanover, Bremen, Stuttgart and Kaiserslautern. We can also run it exclusively for your team.

Who is this course for?

  • Quality managers and management representatives
  • Quality engineers and quality planners
  • Internal auditors
  • Complaint and supplier quality managers
  • Process owners in management systems

Typical challenges we address

  • Keeping extensive quality documentation current, consistent and compliant with standards
  • Analysing and resolving complaints and nonconformities quickly
  • Preparing internal and external audits efficiently
  • Reliably tracking actions from audits, 8D reports and management reviews

What you will be able to do

  • You write structured prompts that reliably produce usable results for your day-to-day tasks.
  • You organise your work in Projects and revise longer documents efficiently with Canvas.
  • You analyse spreadsheets and files with data analysis and critically verify the results.
  • You build a custom GPT for a recurring task and share it with your team.
  • Create and maintain quality documentation efficiently and in line with standards using AI.
  • Use AI for complaint analysis, 8D, FMEA and audit preparation.
  • Integrate AI output into your management system in a controlled and traceable way.

Course outline

Module 1 Foundations and effective prompting
  • How language models work: strengths, limitations and hallucinations
  • Building effective prompts with role, context, task and output format
  • Refining iteratively instead of starting over: follow-ups and correction loops
  • Choosing models and using web search and deep research appropriately
Module 2 Projects, Canvas and document work
  • Setting up Projects to group files, instructions and chats by topic
  • Summarising, comparing and interrogating long documents
  • Using Canvas to revise text and drafts section by section
  • Templates for emails, reports, minutes and presentation outlines
Module 3 Data analysis with spreadsheets and files
  • Uploading, cleaning and analysing Excel and CSV files
  • Calculating KPIs, replicating pivot logic and explaining variances
  • Generating charts and preparing them for presentations
  • Verifying results: checking calculation steps and sanity checks
Module 4 Custom GPTs for recurring tasks
  • Identifying and scoping good use cases for GPTs
  • Configuring instructions, knowledge files and conversation starters
  • Testing, improving and sharing a GPT within the workspace
  • Maintenance, change tracking for instructions and ownership in the team
Module 5 Privacy, workspaces and governance
  • Personal accounts versus Team and Enterprise workspaces
  • Settings for model training, memory, temporary chats and sharing
  • Handling personal and confidential data in line with GDPR
  • Internal usage policy and quality assurance for AI output
Module 6 Practice lab: Quality Management
  • Writing procedures
  • Standards gap analysis
  • 8D report support
  • FMEA preparation
  • Audit preparation
  • Complaint data analysis
Module 7 Data protection, quality & transfer to daily work
  • AI-generated documents must meet the standard's requirements for controlling documented information and be reviewed by experts before release. Customer data from complaints and confidential product information may only be processed in approved, GDPR-compliant AI environments.
  • Ground rules for safe AI use in your team
  • Checking results: facts, sources, tests and the four-eyes principle
  • Personal action plan for the next 30 days
  • Open questions, outlook and resources for further learning

Practical scenarios from your field

Writing procedures

An AI assistant turns process descriptions and interviews into procedures and work instructions with a consistent structure, checks them for contradictions with other documents and suggests improvements.

Standards gap analysis

AI compares existing documents with the requirements of ISO 9001, IATF 16949 or ISO 13485, highlights possible gaps and produces an action list for expert evaluation.

8D report support

For complaints, AI structures the problem description, suggests containment actions and possible root causes and writes the 8D report in a form customers can understand.

FMEA preparation

Based on process steps and experience, AI suggests failure modes, effects and causes and helps the team facilitate and document FMEA sessions.

Audit preparation

From standard clauses and the process map, AI creates audit questions, checklists and audit plans and condenses audit notes into a structured draft report with findings.

Complaint data analysis

Complaints and inspection results are analysed by defect type, product and supplier, trends identified and priorities for improvement projects proposed.

Prerequisites

Confident use of office applications and a web browser; no prior AI knowledge is required. Feel free to bring your own non-confidential sample tasks from your daily work. You work in quality management and know the requirements of your management system, for example ISO 9001.

Technical requirements

A laptop with an up-to-date browser and a ChatGPT account; a paid plan or access to your organisation's Team or Enterprise workspace is recommended for custom GPTs, Projects and data analysis.

Data protection & compliance

AI-generated documents must meet the standard's requirements for controlling documented information and be reviewed by experts before release. Customer data from complaints and confidential product information may only be processed in approved, GDPR-compliant AI environments.

Suggested dates

All dates are suggestions – your preferred date is always possible.

  • Thu, 26 November 2026 Online Request
  • Wed, 2 December 2026 Kaiserslautern Request
  • Tue, 8 December 2026 Online Request
  • Wed, 16 December 2026 Bremen Request
  • Tue, 19 January 2027 Online Request
  • Mon, 1 February 2027 Salzburg Request

Frequently asked questions

Do I need a paid ChatGPT licence for the course?

You can follow the fundamentals with a free account. However, features such as custom GPTs, Projects with larger files and advanced data analysis are tied to paid plans or come with far more generous limits there. Ideally you join with access to your organisation's Team or Enterprise workspace, so you practise under real conditions.

May I enter confidential company data into ChatGPT?

That depends on your plan, your contractual terms and your internal policy. In Team and Enterprise workspaces, content is not used for training by default, but GDPR and confidentiality obligations still apply. In the course you learn how to classify and anonymise data and how to choose the right settings.

How is a custom GPT different from a saved prompt?

A GPT bundles persistent instructions, knowledge files and optional tools such as web search or data analysis into a dedicated assistant. Colleagues can use it without any prompting skills and get consistent results. A saved prompt, by contrast, has to be copied and supplemented with context every time, which is far more error-prone.

Do auditors accept AI-generated documents?

What matters is not who drafted a document but whether it is technically correct, controlled, approved and applied in practice. If you review AI drafts, release them through your document control and keep responsibility clear, they meet the standard's requirements. We show how to integrate AI cleanly into these processes.

Can AI replace an FMEA?

No. An FMEA relies on the team's cross-functional knowledge of product and process. AI can prepare, make suggestions and document, which makes sessions more efficient. Ratings and decisions on actions remain with the team, which is accountable for the result.

How much does “ChatGPT for Quality Management Teams” cost?

The course costs a flat €949 plus VAT per participant – whether online or on-site. This includes 1 training day(s) with a live trainer, course materials, a lab environment and a certificate of attendance.

Can I suggest my own date?

Yes. Our suggested dates are just a guide. In the request form you can always describe your preferred date or period in free text – we check availability and confirm within one working day.

Is the course online or on-site?

Both are possible: live online in a virtual classroom or on-site in Munich, Salzburg, Berlin, Augsburg, Hanover, Bremen, Stuttgart or Kaiserslautern. We can also run the course exclusively for your team.

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