Training course · AI Agents · Marketing

AI Agents for Marketing Teams

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

Duration
2 days (14 hrs)
Format
Online or on-site
Language
German or English
Participants
open dates or exclusive for your team
Certificate
Certificate of attendance

Overview

“AI Agents for Marketing Teams” is a hands-on course for roles such as Marketing managers and heads of marketing, Performance and digital marketing specialists and Product and brand managers. Rather than learning AI Agents in the abstract, you work on tasks from your daily routine – with examples, exercises and templates from Marketing.

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. Over two days 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.

Marketing teams now cover more channels, audiences and formats than ever, often on the same budget. Generative AI is fundamentally changing the work: AI assistants support market research, persona development and positioning, draft campaign concepts, landing page copy and ad variants and analyse campaign data. AI agents and automation take over routines such as adapting content for different channels, reporting or enriching leads. The value does not come from mass production but from faster testing, better personalisation and more time for strategy and creativity. Clear brand guidelines as the foundation for prompts, careful handling of customer data and editorial review keep content accurate, legally sound and on brand.

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?

  • Marketing managers and heads of marketing
  • Performance and digital marketing specialists
  • Product and brand managers
  • Marketing operations and CRM owners
  • Agency staff

Typical challenges we address

  • Delivering a consistent brand message across many channels and formats
  • Testing campaigns quickly and drawing meaningful conclusions
  • Sharpening target groups and personas with data
  • Organising content production and approvals with limited resources

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.
  • Use AI for audience analysis, campaign concepts and copy variants within your brand guidelines.
  • Analyse campaign data with AI support and make well-founded decisions.
  • Automate marketing routines in a privacy-compliant way with clear approval steps.

Course outline

Day 1

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

Day 2

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: Marketing
  • Audiences and personas
  • Campaign concepts
  • Ad and copy variants
  • Campaign reporting analysis
  • Competitor monitoring
  • Marketing automation
Module 7 Data protection, quality & transfer to daily work
  • Marketing use of AI must comply with the GDPR and ePrivacy rules on tracking, consent and personalisation; customer data belongs only in approved tools. Unfair competition law applies to advertising claims, copyright and trademark law to generated content, and the EU AI Act's transparency duties to AI-generated media.
  • 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

Audiences and personas

An AI assistant condenses market studies, customer feedback and sales notes into personas with needs, objections and buying criteria, then derives key messages and value propositions for campaigns.

Campaign concepts

From the brief, goals and budget, AI develops several campaign ideas with a central idea, channel mix, messages and KPIs, which the team evaluates, combines and refines.

Ad and copy variants

AI creates variants of headlines, ad copy, subject lines and calls to action within brand guidelines and prepares A/B tests whose results are then analysed.

Campaign reporting analysis

Exports from ad platforms, web analytics and CRM are combined, anomalies explained and recommendations drafted, so reporting meetings can focus on decisions rather than data gathering.

Competitor monitoring

AI summarises publicly available information on competitors, such as website messaging, product launches and pricing communication, and highlights differences from your own positioning.

Marketing automation

Workflows enrich new leads, segment contacts, draft personalised nurture emails and notify sales as soon as a lead meets defined qualification criteria.

Prerequisites

You should already use an AI assistant such as ChatGPT, Copilot or Claude on a regular basis. No programming skills are required. You work in marketing or at an agency and understand the basics of campaign planning and digital channels.

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

Marketing use of AI must comply with the GDPR and ePrivacy rules on tracking, consent and personalisation; customer data belongs only in approved tools. Unfair competition law applies to advertising claims, copyright and trademark law to generated content, and the EU AI Act's transparency duties to AI-generated media.

Suggested dates

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

  • Tue, 24 November 2026 – Wed, 25 November 2026 Online Request
  • Wed, 2 December 2026 – Thu, 3 December 2026 Munich Request
  • Tue, 8 December 2026 – Wed, 9 December 2026 Online Request
  • Mon, 18 January 2027 – Tue, 19 January 2027 Online Request
  • Thu, 4 February 2027 – Fri, 5 February 2027 Berlin Request
  • Tue, 9 February 2027 – Wed, 10 February 2027 Online 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.

How do we keep AI-generated content on brand?

Start with well-documented brand guidelines covering tone of voice, sample copy and banned terms, and provide them as context to AI assistants. Combined with reusable prompt templates and editorial approval, this produces consistent copy. In the course we build such templates together for your channels.

Who owns the rights to AI-generated content?

Purely machine-generated content is generally not protected by copyright in many jurisdictions, including Germany, whereas works substantially shaped by people can be. You also need to check that outputs do not infringe third-party rights such as trademarks or well-known imagery. We discuss practical rules for approval and labelling.

How much does “AI Agents for Marketing Teams” cost?

The course costs a flat €949 plus VAT per participant – whether online or on-site. This includes 2 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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