Kickstart AI Learning in Your Org with This Workshop Template

AI is evolving at lightning speed. From generative models with enhanced reasoning capabilities (like Claude 3.7 Sonnet) to hyper-real video generation (like Veo 3), it’s easy to feel like you or your team are falling behind. By creating space for testing and exploration, you and your team can build confidence, ask better questions, and think critically about how to use AI responsibly.

At Brandience, we’re not new to this. We’ve been leveraging generative AI since its earliest days not just experimenting but embedding it into how we work. We’ve developed a formal AI policy, built a suite of custom AI agents to boost efficiency, and established an internal AI Hub that keeps us sharp on the latest developments and safe, ethical AI-use.

Our AI Hub also leads regular workshops to ensure everyone feels empowered to engage with the technology. One of our recent sessions? A hands-on Lunch & Learn focused on AI image generation. The key lesson was: prompting matters.

The workshop is structured to start with basic prompts for generating an image and gradually build in complexity, allowing participants to see firsthand how different inputs lead to dramatically different image outputs.

The goal wasn’t to master the tech overnight. It was to create a safe, smart, and fun space for our team to explore, ask questions, and build confidence with the tools.

Try It for Yourself: Free Workshop Template for AI Exploration

We’re sharing our workshop template with you: a simple, collaborative toolkit to help you guide your team to explore AI image generation and understand how the way you frame a prompt can dramatically shape the results.

No technical expertise required, just curiosity and a willingness to play.

Tip: You don’t need a paid tool to get started. Free generative AI platforms like ChatGPT or Google Gemini work great for this workshop. If someone on your team does have access to a paid version, try comparing outputs. It’s a great way to spark discussions around prompt quality and model capabilities.