Marek Rucinski

Marek Rucinski

Deputy Commissioner - Head of Data and Analytics, Australian Taxation Office


Marek Rucinski is the Deputy Commissioner of Smarter Data, the ATO’s data and analytics capability. He has strategic responsibility for the development and industrialisation of data, analytics and insights to support the administration of the tax and super systems, government priorities, and deliver value for the Australian community. This role combines the traditional roles of chief data and chief analytics officers in many other organisations. Marek leads the ATO Data and Analytics Professional Stream, is a member of the senior working group for the APS Data Professional Stream, and chairs the APS Data Champions Executive. Marek has driven the evolution of data and analytics capabilities for over 20 years in industry roles and in a consulting services capacity across Australia, Asia and global clients. He has worked in retail, telecommunications, consumer goods, financial services, mining and utilities sectors and now, the federal government. Prior to ATO, Marek was a Managing Director in Accenture and was the Analytics Practice lead for Australia and New Zealand.


We had the pleasure of hosting Marek Rucinski, Deputy Commissioner - Head of Data and Analytics, Australian Taxation Office, for a fireside chat at the Mindfields Automation Summit (MAS) 2023. Below are the key takeaways from the session.

  • Productivity challenges in Australia include an aging population and a need to do more with less. AI is seen as a potential solution to boost productivity, but it requires reimagining entire workflows with AI at the center, moving humans to judgment tasks, and focusing on ethical decisions.
  • Generational differences impact the adoption of AI. Gen Z and Millennials desire hyper-personalized experiences and are comfortable with data sharing.
  • The ATO faces the challenge of adapting to diverse generational expectations. They aim to create adaptable experiences that are digital-first but also accommodate traditional processes.
  • AI is being used to identify and isolate risky behaviors among clients, such as shadow economy activities and superannuation guarantee underpayments, resulting in the discovery of millions in liabilities with a 90% strike rate.
  • In the context of tax fraud prevention, AI, including supervised machine learning models, is being employed to prioritize targets for GST fraud, stopping billions of dollars from leaving the ATO.