Why do some AI image generators struggle with hands and text?

They struggle because hands and text are both incredibly precise things, and AI image generators don't actually understand what they're drawing. These models learn from millions of images, but they learn patterns, not anatomy. A hand can appear in so many positions — gripping, pointing, relaxed, partially hidden — that the model sees a statistical mess rather than a clear rule. Fingers overlap. They bend at weird angles in photos. The training data is full of hands that look like a jumble of skin tones. So the AI produces exactly that: a jumble. Text has the opposite problem. Letters must be exact. An 'R' can't look mostly like an 'R'. But the model doesn't know the alphabet. It sees text as a visual texture, like wood grain or grass. It knows a sign should have squiggly lines on it, but it doesn't know those lines need to spell 'OPEN' in a specific sequence. It's like asking someone who doesn't read Chinese to copy a Chinese sentence by hand — the shapes might be close, but a native speaker would spot the errors instantly. Newer models are getting better at this. They're trained on higher-quality data with explicit labels for hands and text. But it's still a weak spot. If you need an image with readable text, you're usually better off generating the background and adding the text yourself in a design tool.