Typing a sentence and getting an image back still feels a little unreal, but teams use it every day now — mood boards, ad concepts, storyboards, social posts, game assets. The models improved fast; the real skill moved to prompting, curation, and knowing which tool fits which job.
Midjourney still leans artistic. Strong aesthetics out of the box, great for stylized visuals, concept art, and anything where "looks interesting" beats pixel-perfect accuracy. Discord-based workflow annoys some people; fans say the community and style consistency are worth it.
DALL-E inside ChatGPT and Microsoft's ecosystem wins on accessibility. Non-designers can iterate in plain language, edit regions of an image, and drop results into documents without learning a separate app. Photorealism and text-in-image keep getting better, though hands and fine detail can still trip models up.
Flux and open-weight image models appeal to people who want control — local runs, custom fine-tunes, fewer usage caps. Devs and studios pair them with ComfyUI or similar node workflows for repeatable pipelines. You trade convenience for ownership and sometimes raw quality tuning.
Commercial use, copyright, and training data remain messy topics. Read each platform's terms before selling what you generate. Many teams treat AI images as drafts that go through human review, brand checks, and sometimes traditional retouching before they ship publicly.
Practical advice: keep a prompt library, version what worked, and don't fall in love with the first render. The best workflows combine generation with Photoshop, Figma, or video tools — AI gets you 70% there; taste and editing get you the rest.