Generative AI in Injury and Disability Schemes: Enhancing Schemes’ Support

Rapidly evolving generative Artificial Intelligence (AI) is transforming service delivery across the insurance and public sector landscape. With its ability to synthesise large datasets, generate tailored content, and streamline workflows, generative AI presents both significant opportunities and practical challenges for injury and disability schemes. These schemes, often complex, highly regulated, and centred on human wellbeing, benefit from more intelligent, efficient, and personalised services. AI can be a powerful enabler of these facets.

This presentation shares insights from collaborative research led by the GIPC Injury and Disability Working Group, in partnership with the Young Data Analytics Working Group (YDAWG) of the Data Science and AI Practice Committee (DSAIPC). Drawing on surveying and a consultation process with scheme actuaries, administrators, and digital strategy leads, our work maps the landscape of current and emerging applications of generative AI across Australian injury and disability schemes and what the future of AI might look like in these schemes.

In considering this pathway from current use to potential advancements, key focus areas include:

Scheme processes
How schemes are trialling or deploying generative AI in real-world contexts, for example automating claims correspondence, summarising medical reports, supporting customer service interactions, and enhancing triage processes for psychological and complex injuries.

Operational Benefits
Examination of how generative AI is improving and could further improve areas such as internal efficiency, reducing administrative burden on case managers, and enabling faster, more informed decisions, particularly in high-volume or high-complexity areas of claims management.

Fraud Detection and Analytics
Exploration of how AI is supporting predictive analytics and fraud prevention efforts, such as use of natural language models to flag anomalies and synthesise disparate claim data.

Challenges and Guardrails
Considerations of AI limitations and risks, such as the need for human oversight, risk of bias in large language models, data privacy considerations, and potential regulatory and ethical pitfalls.

Actuarial Involvement
How actuaries are increasingly being called on to help to shape AI strategy; leveraging actuarial capabilities to ensure AI implementations are aligned with scheme goals, ethical standards and societal impact. Critical in designing use cases, assessing data readiness, evaluating AI model performance and fairness and bridging technical and strategic domains.

Future Outlook
Insights into how scheme actuaries can leverage early successes and key lessons learned in the broader application of AI to enable further development and advancement of more adaptive and client-centred scheme models, supporting early intervention, tailoring recovery pathways, and enabling better data sharing across health, employment, and compensation systems.

Our presentation is aimed to equip scheme professionals with a balanced understanding of how generative AI can be further leveraged to move its use from beyond hype, to become a powerful enabler of sustainable, client-centred schemes. It will also highlight key opportunities for actuaries to lead in this space, by applying actuarial rigour, advancing ethical data use, and helping shape sustainable, transparent, and human-centred systems.