Multimodal AI

A practical guide to understanding what multimodal AI is and what it means for product and UX design.

What multimodal AI can process and generate beyond text, how it expands what is possible in product design, and what teams need to consider when working with it.

22 May 20264 min read

What it is

Multimodal AI refers to AI glossarySystemA system is a collection of interconnected components that work together to achieve a specific function or outcome.Open glossary term that can glossaryProcessA process is a defined sequence of steps used to achieve a specific outcome.Open glossary term and generate more than one type of glossaryDataData is raw information collected and stored for analysis, processing, or decision-making.Open glossary term — such as text, images, audio, and video — rather than being limited to a single modality.

A multimodal glossaryModelA model is a system or representation used to process data and generate outputs, often trained to perform specific tasks.Open glossary term might accept a photograph and a question as input and return a text description, analysis, or answer. Or it might generate an image from a text description, transcribe speech to text, or analyse a video.

Early language glossaryModelA model is a system or representation used to process data and generate outputs, often trained to perform specific tasks.Open glossary term were text-only. Modern guideFoundation ModelsWhat foundation models are, how they differ from traditional software, and what product and design teams need to know when building on top of them.Open guide like GPT-4o, Claude, and Gemini can glossaryProcessA process is a defined sequence of steps used to achieve a specific outcome.Open glossary term images alongside text, and some can generate images or audio as well.

This expands what is possible in product design significantly. AI glossaryFeatureA feature is a specific piece of functionality within a product that delivers value to users. It represents something users can do or experience as part of the overall product.Open glossary term can now understand screenshots, analyse charts, read documents with visual formatting, interpret photographs, and respond to voice input.

When to use it

Understand when multimodal glossaryCapabilityCapability refers to an organisation’s ability to perform a specific function or deliver a particular outcome.Open glossary term add real value. They are most relevant when:

They are less relevant when:

Users need to share images, documents, or audio as part of their interaction with the AI

The task involves visual information that would be difficult to describe in text

You are designing voice or audio-driven features

The output needs to include generated images or visual content

Accessibility improvements through audio or visual AI are a priority

The interaction is purely text-based and no other modalities are involved

Key takeaway

Multimodal AI opens up new interaction patterns that were not possible with text-only models. Understanding the capabilities helps you design features that use them appropriately.

How it works

Understand the basic mechanism. Multimodal glossaryModelA model is a system or representation used to process data and generate outputs, often trained to perform specific tasks.Open glossary term are trained to glossaryProcessA process is a defined sequence of steps used to achieve a specific outcome.Open glossary term and relate different types of input. For image understanding, the model learns to represent images in a way that can be connected to language — allowing it to describe, analyse, and reason about visual content.

Different modalities are handled through different components within the glossaryModelA model is a system or representation used to process data and generate outputs, often trained to perform specific tasks.Open glossary term glossaryArchitectureArchitecture refers to the structure and organisation of a system, including how components interact and are designed.Open glossary term, but the language model serves as the central reasoning engine that connects them.

Generating images works differently — it typically uses separate generative glossaryModelA model is a system or representation used to process data and generate outputs, often trained to perform specific tasks.Open glossary term, such as diffusion models, rather than the language model itself.

What this means for designers and product teams. Multimodal glossaryCapabilityCapability refers to an organisation’s ability to perform a specific function or deliver a particular outcome.Open glossary term introduce new glossaryInteraction DesignInteraction design is the practice of designing how users interact with a product, focusing on behaviour, flow, and responsiveness. It ensures interactions are intuitive, efficient, and meaningful.Open glossary term possibilities — image upload, voice input, visual output — and new design challenges around how users understand and interact with these modalities.

The quality and glossaryReliabilityReliability is the ability of a system to consistently perform as expected without failure.Open glossary term of multimodal glossaryFeatureA feature is a specific piece of functionality within a product that delivers value to users. It represents something users can do or experience as part of the overall product.Open glossary term varies. Image understanding is generally strong. Complex visual reasoning, charts, and handwritten text are more variable. Testing with real-world inputs from your users is essential.

What to look for

Focus on:

Capability fit — whether the multimodal capability actually improves the user experience for the specific task

Input quality sensitivity — how well the model handles low-quality, unusual, or varied inputs

Output quality — whether generated images or audio meet the required standard

Privacy implications — whether image or audio inputs raise data handling concerns

Accessibility — whether multimodal features are designed to work for users with different needs

Where it goes wrong

Most issues come from: Multimodal glossaryFeatureA feature is a specific piece of functionality within a product that delivers value to users. It represents something users can do or experience as part of the overall product.Open glossary term that are technically impressive but do not clearly serve a user need are a distraction.

Adding multimodal features because they are possible rather than because they are useful

Insufficient testing with the actual range of inputs users will provide

Ignoring the privacy implications of handling images, audio, or video

Overestimating the reliability of visual reasoning on complex or specialised content

What you get from it

Understanding multimodal AI gives you:

A clearer picture of what AI features can now accept and generate

Better ability to identify opportunities for multimodal interaction design

More informed decisions about when multimodal capabilities add genuine value

A basis for evaluating and testing multimodal feature quality

Key takeaway

Multimodal AI expands the design space significantly. The question is not just what it can do, but where it genuinely improves the experience.

FAQ

Common questions

A few practical answers to the questions that usually come up around this method.

What is multimodal AI?

Multimodal AI refers to glossarySystemA system is a collection of interconnected components that work together to achieve a specific function or outcome.Open glossary term that can glossaryProcessA process is a defined sequence of steps used to achieve a specific outcome.Open glossary term and generate more than one type of glossaryDataData is raw information collected and stored for analysis, processing, or decision-making.Open glossary term — such as text, images, audio, or video — rather than being limited to text alone. A multimodal model might accept an image and a question as input and return a text answer, or generate an image from a text description.

Which AI models support multimodal input?

Most leading guideFoundation ModelsWhat foundation models are, how they differ from traditional software, and what product and design teams need to know when building on top of them.Open guide now support text and image input. GPT-4o, Claude, and Gemini all accept images alongside text. Audio and video glossaryCapabilityCapability refers to an organisation’s ability to perform a specific function or deliver a particular outcome.Open glossary term are available in some glossaryModelA model is a system or representation used to process data and generate outputs, often trained to perform specific tasks.Open glossary term and expanding rapidly. Checking current documentation from the model provider is the best way to confirm what is supported.

Is image generation the same as multimodal understanding?

No. Image understanding — where the glossaryModelA model is a system or representation used to process data and generate outputs, often trained to perform specific tasks.Open glossary term analyses and reasons about an image you provide — uses a different mechanism from image generation — where the model creates a new image. Many products combine both, but they are separate glossaryCapabilityCapability refers to an organisation’s ability to perform a specific function or deliver a particular outcome.Open glossary term and are often handled by different models.

What are the privacy implications of multimodal AI?

Significant. When users upload images or audio, those inputs may contain sensitive information — faces, locations, personal documents, medical glossaryDataData is raw information collected and stored for analysis, processing, or decision-making.Open glossary term. Clear policies about how that data is handled, stored, and used are essential for any product that accepts non-text inputs.

How reliable is AI image understanding?

It is strong for common, clear images — photographs, diagrams, text in standard formats. It is less reliable for specialised content, low-quality images, complex charts, handwritten text, and images from niche domains. Test with real user inputs rather than ideal examples.

Quick take

Multimodal AI can understand and generate more than just text — and that fundamentally changes what AI features can do.

Related Services

Artificial Intelligence