How will multimodal AI search affect reputation management?

Multimodal AI – engines that process and generate images, video, and audio alongside text – is rolling out across the major providers and changes what reputation programs have to manage. Image search becomes AI image understanding: the engines describe and contextualize images of executives, products, and locations, which means image SEO (alt text, structured data, captioning) becomes AI reputation work. Video processing pulls from transcripts but increasingly from visual content as well: a brand’s video presence shapes how the engines describe it in ways YouTube SEO alone does not capture. Audio content – podcasts, interview clips, earnings calls – is processed for content rather than just attendance, which means what is said in audio venues now influences AI synthesis. The reputation discipline expands accordingly: image-level work, video-level work, audio-level work, all paired with strong entity signals that the multimodal engines can use to disambiguate. The principles do not change; the footprint widens.