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GOVERNMENT empowers New South Wales Government To Deliver Exceptional Services for its Citizens with AI

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Accelerate the speed to build models



Higher prediction accuracy



More personalized and targeted programs

New South Wales is a major global and Asia-Pacific cultural hub. Home to a diverse population of 7.7 million people, NSW is Australia’s oldest and largest state. It is also an economic powerhouse, with an economy larger than Hong Kong, Malaysia, and Singapore. By using, the NSW Government was able to achieve its goal of promoting the use of data and information to improve its services and to benefit its citizens.




As the NSW Government wanted to build out its data practice and initiatives, they needed to enable its analysts to draw upon data science and automatic machine learning platforms to help find answers, pinpoint solutions and use data to create better services for all.

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Using data and a cutting-edge platform like Driverless AI helps us better fulfill our mission to improve outcomes for the citizens of NSW We did an extensive evaluation of automatic machine 'earning platforms and selected Driverless AI because of its accuracy, and the ability for us to significantly accelerate the speed of our model development. It also enables us to generate explainable results rather than having results a black-box This is an impressive technology which will help our team deliver exceptional services to our citizens."

Ian Opermann, Chief Data Scientist at NSW Department of Customer Service


By using, the NSW Department of Customer Service was able to improve the accuracy of its predictive models and empower its team of data scientists to build models faster. This allowed them to deliver more personalized and targeted programs to the citizens of NSW with improved services, policies and innovations. Programs such as the Active Kids program, which supports families by providing vouchers to put towards sport and active recreation costs each year, can be better supported with Driverless AI because it can now predict factors that cause families to miss out on these activities, target these factors and support increased participation.