Our mission for introducing AI into aXcelerate is to empower training organisation teams to drive operational excellence.

At aXcelerate, we believe AI should be used to empower educators and training organisation staff to have more time to focus on what they’re passionate about – delivering high-quality training that sees learners succeeding in the world of work.

Our team has always been led by the HEART values – honesty, empathy, acceptance, respect and trust. We will continue to use these values to guide our approach to AI.

As we move forward, we’re committed to working in partnership with our clients and partners to achieve this vision for implementing AI in aXcelerate.

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Our AI Principles

Our approach reflects ASQA's Principles for the Responsible Use of AI in VET – governance, human oversight, secure information handling, equity, and alignment with training products.

AI should empower educators, individuals and teams to achieve their goals

AI should be used to streamline processes, empowering individuals and teams to work smarter, boost productivity with confidence and achieve their goals efficiently.

People are accountable for decisions

Generative AI tools should be used in ways that are open to challenge and retain human agency and accountability for decisions. People always have choice, control and accountability over the role of AI in their work. AI should always be used in a safe, accessible, fair and respectful way.

We are committed to safety and security

We prioritise safety and security in our AI approach, ensuring that all stakeholders utilising generative AI tools in aXcelerate benefit from robust privacy and data protection measures.

We are committed to transparency

We commit to maintaining transparency regarding our partnerships, security, and data collection, protection and management practices. Our AI partners do not use your data to train their models.

Ai for training providers

AI considerations and best practices

AI can be a powerful tool, and it’s important to know how to use it well.

Accuracy

AI-generated outputs and results are not perfect, and must be checked for accuracy. AI uses artificial intelligence algorithms and data collected from the internet. There is a possibility of inaccuracies, omissions, algorithmic bias or misleading outcomes due to the complexities and limitations of AI technologies. All outputs generated by AI in aXcelerate should be checked by humans.

Using generative AI in Online Assessments

aXcelerate’s generative AI capabilities have limitations. It’s important to ensure you are not solely relying on AI-generated question outputs without checking and considering ASQA’s Principles of Assessment. Human judgement, empathy and nuanced decision-making remain essential in the assessment and lesson authoring process.

Validity

You must ensure that assessment tasks and methods match assessment requirements.

ASQA example: If assessing a practical skill such as keyboarding, questions about how a keyboard operates may not be valid as this knowledge is not required in order to carry out the task. Instead, use questions that demonstrate knowledge of why the student is doing the task in a particular way.

AI consideration: If an assessor inputs a PDF on keyboarding, the AI generator may output a question about how a keyboard operates. The assessor needs to take this into account and review the instructions they are inputting, as well as review and adjust the output.

Reliability

Training organisations should have a well-designed assessment system that includes measures to minimise variation between assessors. Training organisations should also develop evidence criteria to judge the quality of performance in order to help assessors make consistent judgements about competence. Where evidence criteria includes model answers, assessors need to be involved in choosing to use or overwrite AI-generated suggested responses.

Your responsibilities

You should exercise your own judgement and discretion when using AI-powered tools. AI-generated outputs can be inaccurate or incomplete, so it's essential to review and verify them before making any decisions, taking actions, or relying on them for critical matters. You remain responsible for any decisions you make and any outputs you accept, edit, publish, or act on.
You are responsible for the information you input into AI features. You should only input information you are authorised to use for this purpose, and you should ensure your use of AI features is lawful and consistent with your own obligations, including your obligations to your learners and under the VET Quality Framework and applicable privacy laws.
Where AI features process personal information, learner information for example, you remain responsible for meeting your obligations under the Privacy Act 1988 (Cth) and the Australian Privacy Principles. This includes where sensitive information, such as health or disability information, is involved, which attracts stricter handling requirements.
AI features can suggest assessment questions and marking feedback. These are suggestions. The assessment judgement remains the decision of a qualified assessor, and you remain responsible for meeting your obligations as a registered training organisation.
You are responsible for deciding which AI features to enable for your organisation, and which of your users can access them.
You should let others know when you're using or presenting AI-generated outputs. aXcelerate does not currently indicate when an output is AI-generated within the platform.
aXcelerate's AI features are built on Amazon Bedrock. Your use of them is subject to aXcelerate's Terms of Use and to the AWS Responsible AI Policy, which prohibits uses including deception, harassment, harm or abuse of a minor, and attempts to circumvent safety controls.

View aXcelerate's Beta Program: Additional Terms and find out more about our Beta Programs.

For guidance on your RTO's AI governance obligations, see ASQA's Principles for the Responsible Use of AI in VET.

Data usage and privacy

aXcelerate's AI features are powered by Amazon Bedrock, a fully managed AWS service that provides access to leading AI models. AI processing takes place within aXcelerate's own AWS environment, hosted in the AWS Asia Pacific (Sydney) region, so your data is processed in Australia.

Your data is not used to train AI models. Information you provide to an AI feature is sent to Amazon Bedrock only to process that request and return a result. It is not retained by the underlying model providers and is not used to train or improve their models.

aXcelerate's AI features work in different ways depending on the task, but most features follow the same general pattern:

You provide an input. Depending on the feature, this might be text or a document you supply (for example, source content for generating assessment questions), or existing information in your aXcelerate account that the feature draws on to complete the task (for example, a learner submission to be marked, or your own content used to answer a learner's question).
The input is sent to Amazon Bedrock, along with context about the task you want to complete.
Bedrock returns an output based on that input and context.
The output is returned to you in aXcelerate – for example, as draft assessment questions, suggested marking feedback, a generated template – for you to review, edit, or accept.

The specific inputs and outputs depend on the feature you are using. In most cases, AI outputs are suggestions for you to review – they are not applied automatically without your involvement. Some features, such as AI Learner Support, respond directly to learners without staff review before sending. You control whether these features are enabled.

To learn more about how we protect your data, visit the aXcelerate Trust Centre.

Visit aXcelerate's Terms of Use to learn more about your data in aXcelerate as a current client.

Using AI in aXcelerate