Training course – AI Image & Video Generation – Product Management

AI Image & Video Generation for Product Managers

Create images and video with Midjourney, GPT-Image, Adobe Firefly and Runway: prompting, image rights, brand consistency and workflows.

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

“AI Image & Video Generation for Product Managers” is designed for roles such as Product managers, Product Owners in agile teams and Heads of Product and product directors and shows step by step how to use AI Image & Video Generation productively, safely and transparently in Product Management – from the fundamentals to advanced workflows.

AI image and video generators are changing how visuals are produced for campaigns, presentations, product pages and training materials. In this hands-on day you will get to know the key tools, including Midjourney, image generation in ChatGPT, Adobe Firefly and Runway, and understand how they differ in style, handling, licensing terms and purpose. You will practise structured prompting for subject, composition, lighting and style, and learn to vary, edit and adapt results for different formats.

Using these images responsibly matters just as much as creating them. You will clarify which usage rights apply to AI-generated content, where the risks lie regarding personality rights, trade marks and copyright, and when labelling is advisable or required. You will also develop methods to keep visual language and corporate design consistent across many assets, for example with style references and prompt templates. Finally, you will set up a repeatable workflow from idea through approval to publication.

Product managers connect customer needs, business goals and technical delivery. Their day revolves around discovery, prioritisation, specification and alignment with engineering, design, sales and leadership. Generative AI speeds up almost every one of these steps: it analyses customer feedback, interviews and support tickets, helps write product requirements and user stories, structures competitor analyses and prepares roadmap communication for different stakeholders. With vibe coding, product managers can build clickable prototypes themselves and test ideas before committing engineering capacity. AI agents bring together signals from analytics, CRM and feedback tools. That leaves more time for product vision, decisions and conversations with customers.

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?

  • Product managers
  • Product Owners in agile teams
  • Heads of Product and product directors
  • Product marketing teams
  • UX researchers and product designers

Typical challenges we address

  • Large amounts of unstructured feedback from many channels
  • Heavy effort for specifications and stakeholder alignment
  • Prioritising under uncertainty and competing interests
  • Long lead times from idea to testable prototype

What you will be able to do

  • You can choose the right image or video tool for a task based on clear criteria.
  • You can write structured prompts that deliberately control subject, composition, lighting and style.
  • You can edit and adapt AI images and short clips for different channels and formats.
  • You can assess legal risks around copyright, trade marks, personality rights and labelling duties.
  • Synthesise customer feedback and market information with AI into well-founded product decisions.
  • Produce specifications, user stories and roadmap communication faster and more precisely with AI.
  • Build clickable prototypes through vibe coding to validate ideas early with users.

Course outline

Module 1 Tool overview
  • Midjourney, GPT-Image, Adobe Firefly and other image generators compared
  • Video generation with Runway and similar tools: text-to-video and image-to-video
  • Strengths, limitations and typical use cases for each tool
  • Selection criteria: image quality, usability, licensing terms and enterprise features
Module 2 Prompting for images and video
  • Anatomy of an image prompt: subject, setting, composition, lighting, perspective and style
  • Using aspect ratios, variations, negative instructions and style references
  • Describing camera movement, scene progression and duration in video prompts
  • Working iteratively: assessing, refining and documenting results
Module 3 Editing, extending and refining
  • Generative fill, expanding canvases and removing unwanted elements
  • Swapping backgrounds, staging product shots and adapting formats
  • Upscaling and post-production in common graphics software
  • Preparing short clips for social media, presentations and websites
Module 4 Image rights, labelling and risk
  • Copyright status of AI-generated content and providers’ terms of use
  • Risks involving real people, trade marks, protected works and style imitation
  • Transparency and labelling duties under the EU AI Act, particularly for deepfakes
  • Content credentials and internal documentation of how images were created
Module 5 Brand consistency and production workflow
  • Translating visual identity and corporate design into prompt templates and style guides
  • Using style references and consistent characters or products across series
  • Defining a workflow from briefing through generation and review to approval
  • Organising asset management, versioning and team collaboration
Module 6 Practice lab: Product Management
  • Synthesising customer feedback
  • PRDs and user stories
  • Preparing prioritisation
  • Competitor and market analysis
  • Prototypes via vibe coding
  • Roadmap and release communication
Module 7 Data protection, quality & transfer to daily work
  • Customer feedback and usage data often contain personal information and are subject to the GDPR; they should be pseudonymised before being processed in AI tools. Roadmaps and unreleased product information are trade secrets, and AI features in your own product must be assessed against the requirements of the EU AI Act.
  • 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

Synthesising customer feedback

Interviews, support tickets, app reviews and surveys are grouped by theme, problem and request and turned into an opportunity overview with supporting quotes for discovery.

PRDs and user stories

Problem statement, target users and goals become drafts of product requirement documents, user stories with acceptance criteria and edge cases, refined with engineering and design.

Preparing prioritisation

AI helps score initiatives using frameworks such as RICE or Kano, surface assumptions and prepare arguments for and against options ahead of prioritisation discussions. Disagreements become easier to resolve.

Competitor and market analysis

Feature comparisons, positioning and pricing models of competitors are structured and updated regularly; claims are backed by sources and checked critically. You keep track of market moves without lengthy manual research.

Prototypes via vibe coding

Product managers use AI coding tools to build clickable prototypes and simple functional demos to test concepts with users and make requirements tangible for the team.

Roadmap and release communication

Roadmaps, release notes, internal enablement material and customer communication are tailored to the audience – technical for engineering, benefit-led for sales and customers. Every audience gets exactly what it needs.

Prerequisites

Design experience is helpful but not required. You should have a basic familiarity with digital image formats and your organisation’s corporate design. Experience in product management or as a Product Owner; no programming skills required.

Technical requirements

You will need a laptop with an up-to-date browser. Access to at least one image generator such as ChatGPT, Midjourney or Adobe Firefly is ideal; trial access is provided for selected exercises.

Data protection & compliance

Customer feedback and usage data often contain personal information and are subject to the GDPR; they should be pseudonymised before being processed in AI tools. Roadmaps and unreleased product information are trade secrets, and AI features in your own product must be assessed against the requirements of the EU AI Act.

Dates & locations

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

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

Frequently asked questions

Can I use AI-generated images commercially?

That depends mainly on the provider’s terms of use and your subscription plan. In addition, purely AI-generated content generally does not enjoy copyright protection under German and most European law, which limits exclusivity. On the course you learn to check licensing terms, recognise risks around trade marks and real people, and document how assets were created.

How do I achieve a consistent look for my brand?

Consistency comes from a system: you translate your corporate design into fixed prompt components, use style and subject references, and define colours, framing and lighting moods as binding rules. A review step and a library of approved reference images then ensure that several people in the team can produce coherent results.

Do I have to label AI-generated images and videos?

The EU AI Act sets out transparency obligations, particularly for deepfakes, meaning realistic depictions of people, places or events. Platform rules and advertising standards also apply. On the course you clarify when labelling is mandatory, when it is sensible on a voluntary basis and how to establish a consistent practice across your organisation.

Can AI make product decisions?

No, but it improves the basis for them. AI condenses feedback, surfaces assumptions and prepares options. Product vision, weighing trade-offs and accountability for decisions remain with product management. In the course you use AI deliberately as an analysis and sparring partner without giving up critical judgement.

How far can I get with vibe-coded prototypes?

Very far for clickable interfaces, simple logic and user testing – often within a few hours. Production-ready software with security, scalability and maintainability remains engineering's job. The course shows how prototypes improve collaboration with the team rather than replacing it.

How much does “AI Image & Video Generation for Product Managers” 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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