Shine a light on AI practices with AI Usage Classifications™
You cannot govern what you cannot see
What is the AI Usage Classification™ Standard
Language that highlights Human & AI collaboration
Like nutrition labels, AIUC badges reveal the level of Human-AI collaboration level for any content created, backed by an industry Code of Practice.
The Problem
-
Shadow AI - Untracked usage across teams
-
Auditability gaps - Regulatory pressure mounting
-
Disclosure anxiety - Fear of reputation damage
-
Language chaos - No standard terminology
The Solution
A simple, non-judgmental framework. Five clear classifications. Universal adoption. AIUC is the standard that turns AI transparency from a compliance burden into a trust-building asset.
See the
AI Usage Classifications
in action (click to view)
Note: The examples above are provided for demonstration purposes only. They illustrate how AI Usage Classification badges can be applied across different types of content and scenarios, and do not indicate verified authorship or provenance.
Who is it for
Governing Bodies
The AI Usage Classification (AIUC) standard gives regulators, associations and peak bodies a straightforward way to define and communicate what responsible AI use looks like for their industry or members. It supports clear expectations, consistent disclosure, and greater accountability.
AI Usage Classifications
Nuanced language supporting AI usage transparency, distributing AI risk management across the organisation, and enabling robust governance across all AI-driven activities.
Protect Your Reputation
Although many assume that AI is in use everywhere, individuals and organisations found to be using it without disclosure have faced significant criticism. Nuanced disclose not only avoids overstating the originality of something created with AI, but also recognises the scale of human judgement and input.
Simplify Compliance
Global regulatory frameworks demand disclosure but lack clear guidance on how to deliver it. Adopting AI Usage Classifications not only fills the gap with minimal internal investment, but organisations also benefit from public reinforcement of the practice to drive consistent and compliant behaviour.
Understand AIs Limitations
Although AI has come a long way, its reliability in providing situationally aware content, unbiased analytics and secure code is still being tested. Transparent classification ensures that both internally and externally, appropriate levels of diligence are being applied over created artefacts, content, and products.
Our
Mission
Shaping a future where creators and consumers can confidently understand and communicate how AI was used, fostering trust and empowering people to discern originality, and appreciate the layered value of human and AI collaboration without judgement.
Our experience with AIUC has encouraged meaningful collaboration across our teams and reinforced the importance of accountability in how AI is used. It represents forward thinking innovation, grounded in integrity.
Anita Pages-Oliver, CEO
Sense Recruitment
The team at AIUC care deeply about the impact of AI on society, business and the lives of individuals.
We need clarity as users and consumers of AI and AI content.
We need easy to understand best practices for adopting AI and AIUC make it happen.
Cam Alliot, CEO
The Growth Engine
The team at AIUC care deeply about the impact of AI on society, business and the lives of individuals.
We need clarity as users and consumers of AI and AI content.
We need easy to understand best practices for adopting AI and AIUC make it happen.
Cate Rocchi, Managing Director
Perth Media
