What is multimodal AI?
Multimodal AI is AI that can take in or produce more than one kind of content, such as text, images, audio, and video, within the same system.
A text-only AI tool can read and write words. Multimodal AI can handle several types of input and output: it might read a photo, listen to a voice note, look at a chart in a PDF, or generate an image or speech as well as text. The word modality simply means a type of content, such as text, images, or sound.
In practice, this means someone can photograph a whiteboard after a meeting and ask an assistant to turn it into typed notes, upload a screenshot of an error message and ask what it means, or share a chart and ask for the main trends in plain words. A field technician could take a picture of a piece of equipment and ask which part is shown.
Multimodal abilities vary between tools and models. One may read images but not create them; another may accept audio but not video. The quality of understanding also depends on the input: blurry photos, handwriting, dense tables, and complex diagrams are more likely to be misread, and a model can describe details in an image that are not actually there.
The same care applies as with text. Descriptions of images, readings of charts, and figures pulled from screenshots should be checked against the original, and images of people, documents, or customer data are covered by the same privacy rules as any other information shared with an AI tool.
An example
An employee photographs a printed receipt and asks an assistant to pull out the vendor, date, and total for an expense report.