# AI text in images: why it goes wrong and how to get clean type

[Canonical HTML page](https://gradiently.design/guide/ai-text-in-images)

The picture is lovely. The sign in it says OPEM DALIY. Here is why image generators still stumble over letters, and the simple change in method that ends the problem.

## The short version

- AI text in images goes wrong because image generators draw letters as shapes made of pixels rather than typing characters.
- Newer image models handle short, large words much better than older ones, but long phrases, small print and unusual names still fail often.
- Text inside a generated image cannot be edited, translated or reliably read by screen readers.
- The dependable method is to generate the image with no text and add the words afterwards as a real type layer.
- Asking the generator for calm, empty space where the words will go makes the type far easier to read.

**AI text in images** goes wrong because an image generator does not type. It paints pixels that statistically resemble letters, learned from a vast number of pictures, so it can produce a convincing O followed by a slightly wrong N. Short words in large letters now often come out right; long phrases, small print and names usually do not. The reliable fix is to stop asking for text in the image at all: generate the picture without words, then add them as real, editable type.

## Why image generators get letters wrong

A text model works with words and characters. An image model works with pixels. When you ask for a café sign that says “Open daily”, the image model has to draw the shapes of those letters in the right order with nothing that checks spelling. It has seen countless signs, so it knows roughly what one looks like, which is why the result is often close but wrong in one or two places.

- **It draws, it does not spell.** There is no step where each letter is checked against the word you asked for.
- **Small text has too few pixels** for the model to get the details of each letter right.
- **Longer phrases multiply the risk.** Each extra letter is another chance for a mistake.
- **Unusual words and names** appear rarely in its training images, so it has less to go on.
- **Fonts are approximate.** You can ask for a serif, but not for your brand typeface.

## What has improved, and what still fails

Recent models are far better at text than those of a few years ago. A single bold word on a poster is often spelt correctly first time. That progress is real, but it changes the odds rather than the method, and it does not fix the problems that come from text being part of the picture.

| Task | Generated text | Real type layer |
| --- | --- | --- |
| One large, common word | Often right | Always right |
| A full sentence | Frequently has errors | Always right |
| Small print, dates, prices | Unreliable | Always right |
| Your brand font | Approximated at best | Exact |
| Change a word later | Generate again | Click and type |
| Translate into another language | Generate again | Swap the text |
| Read by a screen reader | Only through alt text | Can be real text in HTML or PDF |

Generated text is a gamble that improves each year. A type layer is a certainty that does not need to.

## How to get clean type every time

Separate the jobs. Let the generator make the picture, and let a design tool handle the words. This is how professional designers have always worked with photographs, and it suits AI imagery just as well. The difference between the two kinds of tool is laid out in [AI image generators vs design tools](https://gradiently.design/guide/ai-image-generator-vs-design-tool).

1. **Ask for no text** Add a line such as “no text, no letters, no signage, no logos” to every image prompt.
2. **Ask for room** Describe where the words will go: “keep the top third calm and uncluttered”, or “leave plain sky on the left”.
3. **Generate at the right shape** Request the format you will use, such as 4:5 for a 1080×1350 post or 16:9 for a 1280×720 thumbnail.
4. **Add the words as type** Place the image in a design tool and set your headline in a real font. [Fonts for social media](https://gradiently.design/guide/fonts-for-social-media) helps you choose.
5. **Check contrast where the words sit** Contrast changes across an image, so check the exact area behind each line.

```text
Morning light over a quiet harbour, pastel sky, small boats in the lower third.
The upper half is open sky with no detail, suitable for a headline.
No text, no letters, no numbers, no signs, no logos, no watermark.
Aspect ratio 9:16.
```

An image prompt that plans for type. The open sky becomes the place for the words.

## Making the words read on any background

Adding text as a layer solves spelling. It does not automatically solve legibility, because a busy or uneven background can still swallow the words. The usual fixes are moving the text to a calmer area, darkening or lightening the image behind it, or choosing a heavier weight. [Readable text on photos](https://gradiently.design/guide/readable-text-on-photos) and [type on busy backgrounds](https://gradiently.design/guide/type-on-busy-backgrounds) cover the techniques in detail.

A portrait post reading Open daily from eight where the busy background makes part of the line hard to read

Real type, spelt right, but the background runs straight through it and the line breaks up.

The same post with a calmer, higher contrast area of the background behind the words, which read clearly

The same words with the background making room: calmer and higher in contrast behind every letter.

Gradiently is built for the right hand version. Words are always real text, and a Mark knows where they are: its calmest, best contrasting region moves behind the text, colours near the letters deepen or lift, and Auto ink picks light or dark type for each line from the Mark's own palette. There are no boxes, shadows or blur, and you choose how strongly the background responds. The method behind it is explained in [text on a gradient](https://gradiently.design/guide/text-on-gradient).

## If you already have an image with bad text

### Tempting but risky

- Regenerating until the spelling is right
- Editing single letters by hand in a photo editor
- Leaving it and hoping nobody notices
- Adding more words to cover the mistake

### Reliable

- Remove or cover the generated text area
- Use the image as a background only
- Set the words again as a type layer
- Keep the type out of the busiest parts

Most image editors can remove a small area of text and fill it from its surroundings. Once the bad lettering is gone, treat the picture as a background and add the words properly. Then write alt text, since screen readers cannot read words that exist only as pixels; [colour contrast and accessibility](https://gradiently.design/guide/color-contrast-accessibility) covers the rest of the accessibility basics.

## FAQ

### Why does AI misspell words in images?

Image generators draw letters as pixel shapes learned from pictures. Nothing checks each letter against the word you asked for, so spelling errors slip in, especially in long or small text.

### Which AI image generator is best at text?

Newer models handle short, large words much better than older ones, but none is fully reliable for sentences, small print or names. Adding text as a real layer afterwards always works.

### How do I add text to an AI image?

Generate the image with no text and with calm space where the words will go, then place it in a design tool and set the words as editable type.

### Can I edit the text in an AI generated image?

Not as text. You can remove the area in an image editor and set new words on top, but the original letters are pixels, not characters.