AI image generation workflows are repeatable steps that take a creative brief through prompting, selection, editing, review and export using tools such as Midjourney, Adobe Firefly, DALL-E in ChatGPT, Google’s Imagen models or Stable Diffusion. Time is saved less by the generation itself and more by standardising the steps around it, so each image does not start from a blank prompt and an open-ended debate.
Most teams try image generators in an ad hoc way. Someone types a prompt, likes one result, and posts it. The next person cannot reproduce the look, and a month later the brand feed looks like it belongs to five companies. A workflow fixes that by making choices once and reusing them.
What does a reliable workflow look like?
A working process has six stages. Each stage has an owner and a clear output, which makes it easy to see where time leaks.
- Brief: the marketer fills a short template with purpose, channel, format, mood and must-avoid elements.
- Prompt build: the designer converts the brief into a prompt using the team’s library and reference images.
- Generate and shortlist: produce a batch, pick two or three candidates, discard the rest.
- Edit: fix artefacts, extend or crop for each format, add brand typography in a design tool.
- Review: a second person checks brand, accuracy and rights.
- Deliver and archive: export final sizes, store the prompt, seed or settings and source images together.
The archive step is the one most often skipped and the one that saves the most time later. When a campaign needs a fourth variant three months on, the stored prompt and reference let you match the original instead of guessing.
How do you choose the right tool for each step?
No single generator is best at everything. Midjourney is popular for stylised, high-aesthetic imagery. Firefly fits teams already inside Adobe apps and those who want licensed training data. ChatGPT’s image generation handles conversational edits and text inside images reasonably well. Stable Diffusion, run locally or through services, gives the most control through tools like ControlNet but needs more technical skill.
Many teams settle on one primary generator for concepts and Photoshop for the edit stage, because Generative Fill and Expand make format adaptation fast. Pick based on your existing licences and your legal team’s view on training data, not only on output samples.
Keeping style consistent
Most current tools accept reference images for style or character consistency. Build a small set of approved reference images per campaign and attach them to every prompt. Midjourney’s style references, Firefly’s style reference upload and image inputs in ChatGPT all serve this purpose.
Where do teams lose the most time?
The biggest drain is endless generation. Without a stopping rule, people keep regenerating in search of a perfect image. Set a limit, for example three rounds of four images each, then move the best candidate to editing. Perfection comes from editing, not from round fourteen.
The second drain is text inside images. Generators have improved, but logos, product names and small type still distort. Generate the image without text and add typography in Figma, Canva or Photoshop. It is faster than fixing garbled letters.
The third is unclear approval. If nobody knows who signs off, images bounce between Slack threads. Name the reviewer in the brief template.
What should the review checklist include?
Review exists to catch the errors generators make predictably. A short checklist keeps it fast.
- Anatomy: hands, eyes, teeth and limbs look natural.
- Geometry: straight lines are straight, reflections and shadows agree.
- Brand: colours sit within the palette, no off-brand objects.
- Accuracy: no invented products, fake interfaces or misleading claims.
- Rights: no recognisable real people, trademarks or copyrighted characters.
- Disclosure: label or keep Content Credentials where the channel or regulation expects it.
Rights deserve care. Prompting “in the style of” a named living artist, or generating a recognisable public figure, creates legal and reputational exposure. Most tools’ terms forbid some of these uses, and platforms such as Meta and YouTube have disclosure rules for realistic synthetic media.
How do you scale the workflow across a team?
Once the process works for one designer, write it down in a single shared page: the brief template, the tool list, the prompt library link, the stopping rule, the review checklist and the archive location. New colleagues should be able to follow it without a training session.
Next, set naming conventions. A file name such as campaign_channel_size_version tells anyone where an image belongs, and a matching prompt file sits beside it. When a client asks for a change months later, nobody has to search Slack history.
Finally, review the library every quarter. Models update, and a prompt that worked well in spring may produce a different look after a version change. Retest the top prompts, replace those that drift and note the model version used where the tool shows it. This small routine keeps output consistent while tools keep moving.
How Alien Road applies AI image generation
In a typical engagement, discovery starts with the client’s brand guide and a sample of their last few months of creative. We note which formats repeat, which take longest and where image quality lets the brand down. That tells us which workflow stages need the most attention.
Setup includes the brief template, a prompt and reference library tuned to the brand, a tool choice that matches the client’s licences and legal position, and the review checklist. Designers own the edit and typography stages, and generated files are archived with their prompts in a shared folder.
We measure hours per asset, rounds of revision and channel performance of generated versus traditional creative. Reports show where the workflow saves time and where a photo shoot or illustrator is still the better choice.
Where to start this week
Write a one-page brief template with five fields: purpose, channel and size, mood, must-include, must-avoid. Use it for the next three image requests, even if the brief is filled in by the same person who will design.
Then set your stopping rule and start an archive folder where every final image sits next to its prompt and settings. These two habits alone tend to cut the back-and-forth more than switching to a newer model.
Keep reading: Graphic Design · AI Marketing