• Whole of AI lifecycle

    Whole of AI lifecycle statements apply across multiple AI product lifecycle stages, for ease of use and to minimise content duplication.

    Off
  • Transactional services

    Transactional services lead to a change in government-held records, typically involving an exchange of information, money, licences or goods.  

    Examples of transactional services include: 

    • logging in to a portal or platform
    • submitting a claim
    • registering a business
    • updating contact details
    • lodging a tax return
    • subscribing to newsletters
    • grant applications
    • public consultation submissions. 
    Off
  • Design

    The design statements includes concept development, requirements engineering, and solution design.

    Off
  • Data

    The data statements cover the establishment of the processes and responsibilities for managing data across the AI lifecycle. This stage includes data used in experimenting, training, testing, and operating AI systems.

    Off
  • Train

    The train statements covers the creation and selection of models and algorithms. The key activities in this stage include modelling, pre and post-processing, model refinements, and fine-tuning. It also considers the use of pre-trained models and associated fine-tuning for the operational context.

    Off
  • Evaluate

    The evaluate statements' cover testing, verification, and validation of the whole AI system. It is assumed that agencies have existing capability on test management and on testing traditional software and systems. 

    Off
  • Integrate

    The integrate statements focuses on implementing and testing an AI system within an agency’s internal organisational environment, including with its systems and data.

    Off
  • Deploy

    The deploy statements caters for introducing all the AI technical components, datasets, and related code into a production environment where it can start processing live data.

    Off
  • Monitor

    The monitor statements provides for the operationa and maintenance of the AI system. Monitoring is critical to ensuring the reliability, availability, performance, security, safety, and compliance of an AI system after it is deployed. 

    Off
  • The lifecycles statements 

  • Whole of AI lifecycle: statements 1 - 8

  • Whole of AI lifecycle includes statements that apply across multiple AI product lifecycle stages, for ease of use and to minimise content duplication.

  • The challenges for government use of AI are complex and linked with other governance considerations, such as:

    • the APS Code of Conduct
    • data governance
    • cyber security
    • ICT infrastructure
    • privacy
    • sourcing and procurement
    • copyright
    • ethics practices.

    Across the lifecycle stages, agencies should consider:

    • technology operations – to ensure compliance, efficiency, and ethical standards
    • reference architecture – to provide structured frameworks that guide the design, development, and management of AI solutions
    • people capabilities – having the specialised skills required for successful implementation
    • auditability – enabling external scrutiny, supporting transparency, and accountability
    • explainability – identifying what needs to be explained and when, making complex AI processes transparent and trustworthy
    • system bias – maintaining the role of positive bias in delivering meaningful outcomes, while mitigating the source and impacts of problematic bias
    • version control – tracking and managing changes to information to inform stakeholder decision-making
    • watermarking – to embed visual or hidden markers into generated content so that its creation details can be identified.
  • Notes: 

  • Statement 1

  • Secretaries Digital and Data Committee communique 

    Date: 19 June 2025  

    Strategic Discussion: Strengthening Cyber Security and Building Resilience

    Australian Signals Directorate (ASD) Site Tour

    Members toured the classified operations floor.

    Strengthening Cyber Security and Building Resilience

    ASD and the Department of Home Affairs jointly led a discussion on high-level  threats and the cybersecurity uplift and hardening required to address risks.

    Australian Public Service (APS) Digital Skills Program (Pilot) – Discovery findings and pilot proposal

    Services Australia, in partnership with the Australian Public Service Commission (APSC), established a Whole-of-Government (WofG) Multi-Disciplinary Team (MDT) to undertake discovery work which informed development of a pilot proposal for a campus approach to uplift APS digital skills. Members also endorsed this proposal.

    Adoption of GenAI in Government

    Members discussed the AI in Government Action Plan initiative and current state of AI adoption across the APS, including the importance of leadership in driving confidence, capability and shared solutions across government.

    myGov Investment Pipeline

    The Committee noted and discussed the progress related to the myGov Investment Pipeline, agreed by Government in the 2024-25 Budget, with detail on the initial myGov Investment pipeline initiatives and future opportunities. The Committee was provided an update on the inaugural myGov Strategic Committee meeting, attended by 18 agencies across the Australian Government, held on 16 May 2025. 

    The date for the next SDDC meeting is 25 September 2025.

  • Downloadable resource

    SDDC Communique 19 June 2025

  • Statements

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