Training course · Generative AI · Social Media

Generative AI for Social Media 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

This course connects Generative AI with the everyday processes of Social Media. Participants work on realistic scenarios and leave with prompts, workflows and checklists they can use straight away.

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.

Social media teams work at the pace of the platforms: constantly changing formats, trends and algorithms, and a community that expects quick responses. Generative AI becomes a daily sparring partner. AI assistants build content calendars, draft posts, captions, hooks and short-form video scripts, adapt content for LinkedIn, Instagram, TikTok or YouTube and suggest replies for community management. Automation gathers comments and mentions, summarises sentiment and creates reports. Image and video tools help with visuals and subtitles. The human touch remains decisive: authenticity, a feel for timing and crisis sensitivity cannot be automated. Used wisely, AI frees time for interaction, creative formats and a strategy based on real data rather than gut feeling.

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?

  • Social media managers
  • Community managers
  • Content creators and editors
  • Corporate influencers and employer branding teams
  • Social media agency staff

Typical challenges we address

  • Producing high-quality content regularly for several platforms
  • Responding to comments and messages quickly and in the right tone
  • Spotting trends and reacting in time with suitable formats
  • Measuring success and preparing reports for management and clients

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.
  • Plan and produce platform-specific content efficiently and on brand with AI.
  • Use AI for community management and social listening with clear escalation rules.
  • Observe labelling duties, copyright and data protection for AI-generated content.

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: Social Media
  • Content calendar
  • Platform-specific posts
  • Short-form video scripts
  • Community management
  • Social listening insights
  • Automated reporting
Module 7 Data protection, quality & transfer to daily work
  • Social media activity is subject to advertising disclosure and imprint rules, copyright and personality rights for images and music, and the EU AI Act's transparency duties for deepfakes and AI-generated content. Personal data from comments and messages must be processed in line with the GDPR.
  • 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

Content calendar

An AI assistant turns communication goals, topic clusters and seasonal moments into a content calendar with format ideas, platform allocation and posting frequency for the team to adjust and approve.

Platform-specific posts

One core message becomes several variants: an expert LinkedIn post, an Instagram caption with hashtags and a hook for short-form video, each in the appropriate tone.

Short-form video scripts

AI drafts scripts and storyboards for Reels, Shorts or TikToks with a strong opening, clear structure and call to action, and creates subtitles and descriptions.

Community management

Comments and direct messages are sorted by request and sentiment, reply suggestions prepared in the brand voice and critical posts highlighted for personal handling.

Social listening insights

Automations collect mentions and comments; AI summarises recurring topics, questions and sentiment trends and provides ideas for new content and product feedback.

Automated reporting

Metrics from platform exports are combined, top and bottom performing posts analysed and a monthly report with insights and recommendations drafted.

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 manage social media channels professionally and know the main platforms and their formats.

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

Social media activity is subject to advertising disclosure and imprint rules, copyright and personality rights for images and music, and the EU AI Act's transparency duties for deepfakes and AI-generated content. Personal data from comments and messages must be processed in line with the GDPR.

Suggested dates

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

  • Fri, 27 November 2026 Online Request
  • Wed, 2 December 2026 Munich Request
  • Wed, 9 December 2026 Online Request
  • Fri, 8 January 2027 Hanover Request
  • Wed, 20 January 2027 Online Request
  • Wed, 27 January 2027 Berlin 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.

Do AI-generated posts need to be labelled?

Under the EU AI Act, deepfakes in particular, as well as AI-generated text on matters of public interest that has not been editorially reviewed, must be disclosed. Platforms also have their own rules for labelling realistic synthetic content. In the course we draw up a clear labelling policy for your team.

Doesn't AI content feel generic?

It does when AI is used without context. With your own experiences, customer voices, data and a clearly defined brand voice as input, drafts become far more distinctive. AI provides structure and variants; you contribute the personal perspective and a feel for your community.

How much does “Generative AI for Social Media 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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