Autism AI Pre-Assessment

The Challenge

Autism assessment can be a lengthy and resource-intensive process for children, families and clinicians. Before a formal assessment takes place, clinicians need to gather and interpret substantial information about a child’s development, behaviour and support needs. This can create additional demands on already stretched clinical services and contribute to delays in families receiving appropriate assessment and support. AI-assisted pre-assessment tools have the potential to streamline this early information-gathering stage, but they must first demonstrate that they are practical for families to use and that their outputs reliably align with established clinical assessment methods. This project will address that evidence gap by testing an AI pre-assessment tool with children and young people aged 3–17 and their families in a real-world clinical setting. The key challenge is to determine whether the technology can provide useful, reliable information while remaining acceptable and easy for families to use as part of the assessment pathway.

The Solution

This six-month pilot will evaluate an AI-enabled autism pre-assessment tool with approximately 10–20 families recruited through a specialist clinic. Participants will create secure accounts and use the tool before undergoing established clinical assessment processes. The project will evaluate two critical dimensions. First, implementation outcomes will examine usability, acceptability and the experience of using the tool, including qualitative interviews with parents and carers. Second, clinical reliability will be assessed by mapping the tool’s outputs against formal clinical assessments to determine how closely the AI-generated information aligns with clinician findings. Led by clinician-researcher Jaimie, the multidisciplinary team includes autism and NDIS expertise, a research assistant, a research student and technical support for participant authentication and secure access. The pilot is intentionally limited to one clinic to establish an evidence base and refine the approach before seeking future funding to test the technology across additional clinics and hospital settings.

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