Multimodal AI

What is multimodal AI?

Multimodal AI is a form of generative AI that uses a combination of images, voice, text, video, and more to make predictions or generate entirely new content. It goes beyond the more common and prominent type of AI, which is single-modal and relies primarily on text.

The technology will have a growing impact on customer experience (CX) because it enables more robust communication with customer support interfaces. Multimodal AI moves seamlessly among various communication modes, making interactions more seamless.

For example, a customer who is trying to describe a problem he’s having with a certain item to a chatbot can instead upload a photo of the issue and receive feedback from the chatbot based on that image. With more modes of communication input, AI-powered tools are better informed and better able to meet customers’ needs.

There are many use cases where multimodal AI can have powerful effects, including virtual agents and knowledge management. Multimodal AI can make virtual agents much smarter and more versatile than their single-modal counterparts, since agents can pull from a greater data set of information. The same goes for knowledgebases, which expand their reservoir or knowledge with a multimodal approach.

Multimodal AI is poised to play an increasingly larger role in CX as generative AI adoption grows.