Training course – AI Agents – Automotive

AI Agents for the Automotive Industry

Agentic AI for business teams: understand AI agents, automate workflows safely and keep control with human-in-the-loop and governance.

Duration
6 hours, one session
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 AI Agents with the everyday processes of Automotive. Participants work on realistic scenarios and leave with prompts, workflows and checklists they can use straight away.

AI agents go a step beyond conventional chat assistants: they plan sub-tasks, use tools such as search, files or business applications and complete multi-step work largely on their own. In this compact course you will learn how agents are built, how they differ from chatbots and traditional automation, and which tasks genuinely justify their use. Widely used platforms serve as practical examples, including Microsoft Copilot Studio, custom GPTs and Claude with projects and tool connections.

In the hands-on sessions you design agent workflows for tasks from your own area of work, from triaging requests through research and drafting to handing results over to business systems. You decide where a person reviews and approves, which permissions an agent receives and how errors are detected. A dedicated block covers governance, data protection and accountability, so that your agents not only work but remain controllable, traceable and defensible within your organisation.

The automotive industry is under immense pressure to change: electrification, software-defined vehicles, new competitors and demanding regulation are transforming manufacturers, suppliers and dealerships alike. Generative AI supports almost every stage of the value chain – from requirements management in engineering, through supplier communication and complaint handling in purchasing and quality, to sales and aftersales at the dealership. AI assistants help unlock specifications, standards and test reports, structure 8D reports or answer customer enquiries. AI agents connect data from different systems. What matters is protecting engineering know-how, meeting quality and safety standards and having clear approval processes.

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?

  • Engineering and requirements management staff
  • Purchasing and supplier management at OEMs and suppliers
  • Quality management and complaint handling
  • Sales, service and aftersales at dealerships
  • Production and logistics planning

Typical challenges we address

  • Extensive specifications, standards and requirement documents
  • Heavy documentation workload in quality management and complaints
  • Complex supply chains requiring constant coordination
  • Strict protection of engineering data and intellectual property

What you will be able to do

  • You can explain how AI agents are structured and clearly distinguish them from chatbots and classic automation.
  • You can select a suitable agent platform for your requirements using transparent criteria.
  • You can design an agent workflow for a real process in your area and build a working prototype.
  • You can define human-in-the-loop checkpoints, test cases and escalation rules.
  • Analyse technical documents such as specifications and standards with AI in a structured way.
  • Accelerate quality, complaint and supplier processes with AI support.
  • Use AI while upholding confidentiality, quality standards and approval processes.

Course outline

Module 1 What makes an AI agent
  • Agent building blocks: language model, instructions, knowledge, tools and memory
  • How agents differ from chatbots, macros and classic workflow automation
  • Levels of autonomy: from suggestion-making assistants to agents that act independently
  • Realistically judging which tasks suit agents and which do not
Module 2 Platform overview: Copilot Studio, GPTs and Claude
  • Microsoft Copilot Studio: agents grounded in company data and connected to Microsoft 365
  • Custom GPTs: configuring instructions, knowledge files and actions
  • Claude with projects, knowledge bases and tool access via the Model Context Protocol
  • Selection criteria: data access, integrations, administration and licensing
Module 3 Designing and building agent workflows
  • Breaking tasks into steps and defining hand-offs between agent and human
  • Writing system instructions, examples and knowledge sources for consistent output
  • Connecting tools: search, documents, email, spreadsheets and business applications
  • Building a prototype agent for a real process from your own area
Module 4 Human-in-the-loop, quality and error handling
  • Setting approval steps, escalation rules and thresholds for human review
  • Test cases, evaluation criteria and spot checks for quality assurance
  • Common failure modes: wrong tool choice, endless loops and fabricated facts
  • Using structured user feedback to improve the agent over time
Module 5 Governance, security and roll-out
  • Roles and responsibilities across business units, IT, data protection and works council
  • Least-privilege permissions, logging and protection against prompt injection
  • Positioning under the EU AI Act and GDPR: transparency, documentation and data flows
  • From pilot agent to production: operation, maintenance and measuring success
Module 6 Practice lab: Automotive
  • Analysing specifications
  • Complaints and 8D reports
  • Supplier communication
  • Unlocking standards and processes
  • Sales and aftersales
  • Training and technical documentation
Module 7 Data protection, quality & transfer to daily work
  • Engineering data, design documents and customer specifications are subject to strict confidentiality agreements and industry information security requirements such as TISAX, and may only be processed in approved AI environments. Customer data at dealerships falls under the GDPR, and safety-relevant content always requires expert sign-off.
  • 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

Analysing specifications

AI extracts requirements from lengthy customer specifications, compares them with the supplier's technical response, flags contradictions and ambiguities and drafts clarification questions for customers or development partners.

Complaints and 8D reports

Complaint descriptions are structured, potential causes gathered using methods such as Ishikawa and 8D reports written in clear language – root cause analysis remains the expert team's job.

Supplier communication

Requests, formal notices, escalations and audit reports are written precisely and in several languages, supplier ratings are commented on and meeting preparation is produced. Agreements are recorded for follow-up.

Unlocking standards and processes

Internal process descriptions, work instructions and quality requirements are made searchable, so staff receive answers with a reference to the governing document. New staff find applicable rules much faster.

Sales and aftersales

At the dealership, AI drafts offers, vehicle descriptions, replies to customer enquiries and service reminders and helps service advisers explain repairs clearly. Customer requests are captured for follow-up in the CRM.

Training and technical documentation

Training materials for assembly, service or new vehicle technologies are created from technical documents, simplified for the audience and translated into other languages. Quiz questions per chapter are included.

Prerequisites

You should already use an AI assistant such as ChatGPT, Copilot or Claude on a regular basis. No programming skills are required. Professional experience at a vehicle manufacturer, supplier or dealership; no programming skills required.

Technical requirements

You will need a laptop with an up-to-date browser. Ideally you have access to at least one agent platform such as Copilot Studio, ChatGPT with GPTs or Claude; practice accounts can be provided if needed.

Data protection & compliance

Engineering data, design documents and customer specifications are subject to strict confidentiality agreements and industry information security requirements such as TISAX, and may only be processed in approved AI environments. Customer data at dealerships falls under the GDPR, and safety-relevant content always requires expert sign-off.

Dates & locations

For every location we suggest a date roughly four weeks ahead. Your preferred date is always possible.

  • Munich Fri, 11 December 2026 6 hrs Request
  • Salzburg Fri, 11 December 2026 6 hrs Request
  • Berlin Fri, 11 December 2026 6 hrs Request
  • Augsburg Mon, 14 December 2026 6 hrs Request
  • Hanover Mon, 14 December 2026 6 hrs Request
  • Bremen Fri, 11 December 2026 6 hrs Request
  • Stuttgart Tue, 15 December 2026 6 hrs Request
  • Kaiserslautern Thu, 10 December 2026 6 hrs Request
  • Online Wed, 16 December 2026 6 hrs Request

Frequently asked questions

Do I need programming skills to build AI agents?

No. The platforms used on the course rely on visual interfaces, plain-language instructions and ready-made connectors. You learn to specify agents precisely from a business perspective, connect tools and test workflows. Where deeper technical integration would be needed, you will know which requirements to put to your IT team.

Which platform will we use during the course?

The course is vendor-neutral and uses Microsoft Copilot Studio, custom GPTs and Claude as examples. You build your prototype on the platform that is available or planned in your organisation. The principles of workflow design, control and governance you learn carry over to other agent solutions as well.

How do I stop an agent from acting without control?

Through deliberate design: agents receive only the minimum permissions they need, critical actions such as sending, booking or deleting require human approval, and every step is logged. In addition, you define test cases and escalation rules. These are exactly the control mechanisms you develop for your own use case during the course.

Can specifications be uploaded to AI tools?

Only into environments approved by your information security team that meet your customers' requirements. Many OEMs regulate this contractually. The course shows how to work with approved enterprise solutions, clean documents beforehand and which content never belongs in external services.

Can AI carry out a root cause analysis?

AI helps gather potential causes systematically, structure methods such as 5 Whys or Ishikawa and write reports. The actual analysis with measurements, tests and process knowledge remains the expert team's task. AI speeds up the path there and improves documentation quality.

How much does “AI Agents for the Automotive Industry” cost?

The course costs a flat €949 plus VAT per participant – whether online or on-site. This includes 6 hours of live training with a trainer, course materials, a lab environment and a certificate of attendance.

Can I suggest my own date?

Yes. For every location we suggest a date roughly four weeks ahead. In the request form you can always describe your preferred date or period in free text – we check availability and get back to you 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 and Kaiserslautern. We can also run the course exclusively for your team.

Can the course be tailored to our team?

Yes. Tailor-made courses cost approx. €4,500 more, depending on the topic and by arrangement. We agree content, examples and exercises with you in advance.

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