Foundational Concepts
Multimodal AI
AI that can work with multiple types of input — text, images, audio, video — not just text alone.
Definition
Early AI models could only handle one type of data. Multimodal AI breaks that constraint, allowing a single model to understand and reason across text, images, audio, video, and documents simultaneously. This unlocks use cases that text-only AI cannot handle: extracting data from scanned invoices and handwritten notes, analysing product images alongside their descriptions, or summarising a video meeting. Multimodal capability is now standard in leading models.
Why this matters for your business
Multimodal AI significantly expands the range of operational processes that can be automated — particularly any workflow that currently involves processing paper documents, images, or audio recordings.
Related Terms
Large Language Model (LLM)
A type of AI trained on vast amounts of text that can read, write, summarise, and reason with language.
Foundation Model
A large AI model trained on broad data that can be adapted for many specific tasks.
Artificial Intelligence (AI)
The broad field of building computer systems that can perform tasks usually requiring human intelligence.
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Disclaimer
This definition is provided for educational and informational purposes only. It represents a general explanation of a technical concept and does not constitute professional, technical, or investment advice. Artificial intelligence is a rapidly evolving field; terminology, techniques, and capabilities change frequently. Coaley Peak Ltd makes no warranty as to the accuracy, completeness, or currency of the information provided. Nothing on this page should be relied upon as the sole basis for commercial, technical, legal, or investment decisions without independent professional advice.
Document reference: ISO_webpage_knowledge-base_glossary_v1
Last modified: 29 March 2026
Knowledge Base·Foundational Concepts·Multimodal AI