Artificial Intelligence in Government

Navigating the risks and seizing the opportunities to unlock public sector potential with AI

As governments rapidly adopt AI, ensuring its responsible and effective use is paramount. To support AI adoption and ensure public trust, governments must implement strong frameworks for transparent, ethical, and unbiased AI, reducing risks while enhancing decision-making, services, and operations for all.

Following the June 2024 National AI Assurance Framework agreement, and the DTA’s piloting of its own APS-specific framework, the Artificial Intelligence in Government Conference provides a crucial platform to explore how robust assurance frameworks—aligned with national and state initiatives—can rebuild trust and guide the safe, ethical, and effective use of AI.

Bringing together federal and state leaders, the conference focuses on aligning assurance frameworks, improving AI literacy, ensuring reliable decisions, and integrating risk assessments without stifling innovation. Attendees will gain policy knowledge, best practices for risk mitigation, and discover how to drive ethical, transparent AI innovation to enhance government operations.

Your event experience

• Gain support from key figures involved in the development and implementation of assurance frameworks and technical standards
• Hear from leading AI thinkers and practitioners from government, academia, and the private sector
• Enjoy structured networking opportunities and connect with like-minded peers, fostering valuable relationships and knowledge-sharing
• Hear from a diverse mix of organisations about their AI journeys, including successes, challenges, and lessons learned.
• Walk away with a toolkit of practical strategies you can implement in your organisation.

Who will attend

Senior leaders from Federal and State government, including, but not limited to:

• Chief Data, Information & Technology Officers
• Those working in:
  • Artificial Intelligence
  • Data Governance and Strategy
  • Data Analytics
  • Data Privacy & Ethics
  • AI Policy
  • Data Science & Information Architecture
  • Digital Transformation