How do you assess a skill when the tool keeps changing?
Review cycles, and what “current” has to mean for a qualification in a field that moves faster than its assessment.
AI Qualifications and Quality Assurance
We assess judgement, not output.
Anyone can get an answer. We assess whether you can explain it, verify it and stand behind it.
AI Qualifications and Quality Assurance
We assess judgement, not output.
Anyone can get an answer. We assess whether you can explain it, verify it and stand behind it.
What we actually assess.
Learners will be expected to explain their process, verify results and remain accountable for their own work.
01
Explain the process
Say what you asked, why you asked it that way, and what you did with what came back.
02
Verify the output
Check the claim against something real before it leaves your hands.
03
Own the decision
The work carries your name. Accountability does not transfer to the tool.
Assessed by a human at every level. Criteria references are indicative while the specification is in development.
From everyday use to governance.
Three planned levels, each building practical competence and accountable AI practice.
01
Level 1
An introduction to safe, informed and responsible use of everyday AI tools.
02
Level 2
Confident, applied use of AI in workplace communication, research and service.
03
Level 3
Evaluation and governance of AI within business functions and projects.
Three audiences.
One of them can act today.
Different goals, different timing. Explore what’s possible for you.
AUDIENCEWHAT YOU WILL BE ABLE TO DOWHAT YOU CAN DO TODAY
Learners
Build your verified AI capability from the ground up.
Build an accessible record of verified AI capability, from essential literacy to specialist practice.
Nothing to enrol in yet
Check back soon for learner qualifications.
Approved centres
Deliver qualifications with confidence and quality.
Deliver AIQQA qualifications once the delivery model has been tested.
Nothing to apply for yet
Application opportunities coming soon.
Employers
Make better hiring and development decisions.
Understand what a candidate’s AI evidence actually means when recruiting and developing talent.
Vision
A trusted AI qualifications and skills infrastructure: a system in which a learner can build an accessible record of verified AI capability, an employer can understand what that evidence means, and the public can rely on transparent, human-accountable assessment.
Trust first
Build credibility and dependable operations before we scale.
- 01
Trust first
Build credibility and dependable operations before we scale.
- 02
Human judgement
Value responsible human oversight of AI use, not output alone.
- 03
Employer relevance
Use structured industry input without letting any partner control standards.
- 04
Inclusive progression
Create accessible entry points and a clear route toward specialist practice.
- 05
Evidence over claims
Ground decisions and public statements in evidence, not hype.
- 06
Continuous currency
Design review cycles that keep pace with a fast-moving field.
What we are working through.
We will publish our thinking as the specification develops, rather than after it is finished.
Help shape what trusted AI competence looks like.
Employers can help shape our qualifications now, through structured input, ahead of any formal launch. We also welcome interest from AI practitioners, educators and prospective delivery partners.
Employers can also ask to join the AI Industry Advisory Council.