Training course · Generative AI · Content & PR

Generative AI for Content and PR Teams

Vendor-neutral, hands-on day: how language models work, where they go wrong and how to roll out AI successfully in your team.

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

“Generative AI for Content and PR Teams” is a hands-on course for roles such as Press officers and PR managers, Content marketing managers and Editors and copywriters. Rather than learning Generative AI in the abstract, you work on tasks from your daily routine – with examples, exercises and templates from Content & PR.

Generative AI has reached most organisations, yet teams often lack a shared understanding of what language models can actually do and where their limits lie. In this vendor-neutral course you will learn how large language models generate text, why they hallucinate and how careful prompting, context and source checking lead to reliable results. Rather than relying on any provider's marketing claims, you will work with transparent criteria that help you compare tools and judge their fit for your own tasks.

The second focus is everyday implementation. You will identify concrete use cases in your area of work, weigh benefit, risk and effort, and draft a realistic roll-out plan for your team. This covers ground rules for handling confidential data, a practical prompt library and ways to build acceptance and make results measurable. Throughout the day you work with examples from your own field, so you leave with an actionable roadmap rather than a set of abstract ideas.

Content, communications and PR teams must tell relevant stories to journalists, customers, employees and search engines with limited resources. Generative AI is changing this daily work noticeably: AI assistants research topics, develop content strategies, structure articles and white papers, draft press releases, Q&A documents and interview briefings and optimise copy for search engines and AI-powered search. Automation supports media monitoring, topic tracking and repurposing content across formats. At the same time, the demands on credibility are rising: facts must be correct, quotes must be approved and crisis communication requires sensitivity. AI is therefore a tool for research, structure and variants, while stance, quality and accountability remain with communications professionals.

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?

  • Press officers and PR managers
  • Content marketing managers
  • Editors and copywriters
  • Internal communications teams
  • SEO and corporate publishing leads

Typical challenges we address

  • Producing high-quality expert content with little time and many review rounds
  • Drafting press releases and statements quickly and precisely
  • Repurposing content for search, social media and newsletters
  • Continuously monitoring and assessing media coverage and the topic landscape

What you will be able to do

  • You can explain clearly how language models generate text and why hallucinations occur.
  • You can write prompts that consistently deliver useful, verifiable results.
  • You can compare AI tools against transparent criteria covering data protection, features and cost.
  • You can identify and prioritise concrete use cases for your area of work.
  • Develop content strategies and high-quality copy for different formats with AI support.
  • Produce press releases, Q&As and holding statements faster while checking facts systematically.
  • Automate media monitoring and content repurposing while respecting copyright and media law.

Course outline

Module 1 How large language models work
  • Tokens, context windows and probabilities: what happens when a model generates text
  • Training knowledge versus web search versus your own documents (RAG)
  • Text, images, audio and code: what multimodal models can do today
  • Realistically assessing typical strengths and weaknesses in office work
Module 2 Spotting hallucinations and getting reliable output
  • Why models produce plausible-sounding errors and when the risk increases
  • Prompting techniques: role, context, examples, output format and step-by-step instructions
  • Requesting sources, cross-checking facts and introducing a four-eyes principle
  • Scoping tasks so that AI assists rather than decides
Module 3 Choosing tools without vendor bias
  • Overview of chat assistants, AI built into office suites and specialist tools
  • Criteria: data processing, hosting location, admin features, integrations and pricing model
  • Enterprise licences, API access and locally hosted open-source models compared
  • Building a simple scoring matrix for your own tool selection
Module 4 Identifying use cases in your field
  • Systematically capturing recurring writing, research and analysis tasks
  • Rating benefit, risk and implementation effort for each use case
  • Distinguishing quick wins from strategic initiatives
  • Creating a prioritised use-case backlog for your team
Module 5 Rolling out generative AI in your team
  • Usage rules: which data may go into which tool and who signs off results
  • Building and maintaining a shared prompt library and templates
  • AI champions, training formats and peer exchanges to embed new habits
  • Measuring success: documenting time saved, quality and user satisfaction
Module 6 Practice lab: Content & PR
  • Topic research and content strategy
  • Press release drafts
  • Articles and white papers
  • Content repurposing
  • Media monitoring insights
  • Crisis and Q&A preparation
Module 7 Data protection, quality & transfer to daily work
  • AI-supported communication must respect copyright, quotation rules and personality rights; quotes must never be invented and must be approved by the person quoted. Confidential information such as unpublished financial results belongs only in approved AI environments, and the EU AI Act's transparency duties apply to AI-generated text on matters of public interest.
  • 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

Topic research and content strategy

An AI assistant analyses search intent, customer questions and industry trends, clusters topics and proposes a content plan with formats, audiences and key messages for the team to prioritise.

Press release drafts

From facts, quotes and background information, AI produces an inverted-pyramid draft including headline variants, boilerplate and a short version for social media.

Articles and white papers

AI creates outlines, summarises expert interviews, drafts individual sections and checks readability, flow and consistent use of technical terms, before subject matter experts sign off the content.

Content repurposing

A white paper or webinar is turned into blog posts, LinkedIn posts, newsletter sections and FAQ entries, each with adapted length, tone and call to action.

Media monitoring insights

Automations collect online media mentions; AI summarises tone, key statements and relevant journalists and drafts a daily or weekly press review.

Crisis and Q&A preparation

AI helps anticipate critical questions, draft Q&A documents and holding statements and run through crisis communication scenarios, which are then agreed with management and legal.

Prerequisites

No technical background is required. It helps to bring along typical tasks from your day-to-day work that you would like to support with AI. You work in communications, PR or content marketing and have experience in professional writing.

Technical requirements

You will need a laptop with an up-to-date browser and internet access. A free account with a common AI assistant is sufficient; company licences are welcome.

Data protection & compliance

AI-supported communication must respect copyright, quotation rules and personality rights; quotes must never be invented and must be approved by the person quoted. Confidential information such as unpublished financial results belongs only in approved AI environments, and the EU AI Act's transparency duties apply to AI-generated text on matters of public interest.

Suggested dates

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

  • Mon, 23 November 2026 Online Request
  • Thu, 3 December 2026 Augsburg Request
  • Wed, 16 December 2026 Online Request
  • Thu, 7 January 2027 Online Request
  • Wed, 13 January 2027 Kaiserslautern Request
  • Mon, 18 January 2027 Online Request

Frequently asked questions

Is the course tied to a specific AI tool?

No. The training is deliberately vendor-neutral. You work with widely used chat assistants and learn principles that apply to all major language models. That way you can transfer your skills to whichever tool your organisation has approved and evaluate new offerings yourself using clear criteria instead of relying on marketing statements.

How is confidential company data handled during the course?

For the exercises you use anonymised or fictitious examples from your area of work. At the same time you learn which categories of data may be entered into which tools, what to look for regarding data processing agreements and use of inputs for training, and how to set out these rules clearly for your team.

Will we leave with something concrete to implement?

Yes. You leave with a prioritised use-case backlog, a scoring matrix for tool selection, tested prompt templates and a draft set of team usage rules. These materials are designed so you can take them straight into internal discussions with management, IT and your data protection officer.

How do we prevent false facts in AI-generated copy?

AI assistants can produce convincing but incorrect statements. Work with supplied sources as context, ask for claims to be referenced and introduce a mandatory fact check before publication. In the course we develop prompt patterns and review routines that support exactly this.

Do search engines penalise AI-generated content?

Search engines primarily assess quality, usefulness and expertise, not how content was produced. Mass-produced thin content does harm rankings, however. Content that performs well combines genuine expertise, examples and data, with AI providing structure and efficiency and experts providing substance.

How much does “Generative AI for Content and PR 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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