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When to apply

Apply Criterion 6 during the Discovery and Alpha phases to capture potential solutions, new and existing, that the service could use to solve problems.

Foster a culture of sharing experiences with other agencies, build on the learnings taken from them and align to common platforms, patterns and standards throughout the Service design and delivery process.

Off

Scenario 1

Personal information in correspondence
Scenario 2

Security classified government information
Scenario 3

Cultural sensitivity and intellectual property
Scenario 4

Assessing applications
Scenario 5

Procurement processes

Additional resources

AI in government
Read government policies and initiatives on the safe, responsible use of AI in the APS.
Australia's AI Ethics Principles
Understand the ethical principles guiding responsible AI development and use in Australia.
GovAI
Access learning resources and tools for AI testing and exploration.
AI in Government Fundamentals course
Build foundational knowledge of AI in government through this self-paced online course offered by the APS Academy.
AI and Machine Learning Community of Practice
Online community for government personnel interested in AI, machine learning, deep learning and neural networks. Anyone with a gov.au email address can register for an APS Professions platform account.
Information Management for Records Created Using AI Technologies
National Archives of Australia guidance on identifying and managing Commonwealth records created by or relating to AI.
Engaging with AI
Cyber.gov.au advice for secure AI system development and deployment.
Privacy Guidance for AI Products
Learn how to manage privacy risks when using commercially available AI tools with the resource from the Office of the Australian Information Commissioner.
Protective Security Policy Framework
Access government guidance on safeguarding people, information and assets, including considerations for AI systems under the PSPF.

Off

- AI in government
  Read government policies and initiatives on the safe, responsible use of AI in the APS.
- Australia's AI Ethics Principles
  Understand the ethical principles guiding responsible AI development and use in Australia.
- GovAI
  Access learning resources and tools for AI testing and exploration.
- AI in Government Fundamentals course
  Build foundational knowledge of AI in government through this self-paced online course offered by the APS Academy.
- AI and Machine Learning Community of Practice
  Online community for government personnel interested in AI, machine learning, deep learning and neural networks. Anyone with a gov.au email address can register for an APS Professions platform account.
- Information Management for Records Created Using AI Technologies
  National Archives of Australia guidance on identifying and managing Commonwealth records created by or relating to AI.
- Engaging with AI
  Cyber.gov.au advice for secure AI system development and deployment.
- Privacy Guidance for AI Products
  Learn how to manage privacy risks when using commercially available AI tools with the resource from the Office of the Australian Information Commissioner.
- Protective Security Policy Framework
  Access government guidance on safeguarding people, information and assets, including considerations for AI systems under the PSPF.

To successfully meet this criterion, agencies will need to:
- ‘build once, use many times’
- design for a common, seamless experience
- reuse data where possible.
Apply Criterion 6 during the Discovery and Alpha phases to capture potential solutions, new and existing, that the service could use to solve problems.
Foster a culture of sharing experiences with other agencies, build on the learnings taken from them and align to common platforms, patterns and standards throughout the Service design and delivery process.
- What could be aligned with on the Australian Government Architecture?
- What platforms, patterns and standards could the service reuse?
- What are the alternatives to building from scratch?
- Which agencies run similar services that could be built upon?
- How can new or bespoke components be made for future reuse?
- What data do we already collect, and can it be repurposed?

Assurance research series: 01

Solution

Technology

Often digital projects involve innovating with technologies that are unfamiliar or untested, which can affect delivery confidence.

Strategies to elevate confidence include iterative deployment strategies that build capability and confidence. Other areas for attention include interfaces with legacy systems, including the ways new systems interact with, or replace, aging legacy systems, while maintaining essential services.

Aging legacy systems can affect the system stability upon which the transformation may be reliant.

Legacy system dependencies need thorough analysis.
Assumptions about legacy data coherence and consistency can be particularly problematic, especially for projects involving transfer to cloud services.

More generally, the solution needs to conform to the technical architecture of the business area.

For commercial off the shelf software, the degree of fit with business requirements and degree of change that will be required to software or service can reduce delivery confidence.
For AI-based transformation, detailed understanding of how artificial intelligence (AI) will be used within the business environment is essential, as is consideration of human rights, privacy and ethics implications, particularly for AI.

Consideration should be given for AI solution reliability and safety, and the transparency, explainability and contestability of decisions made using AI solutions. For reference, the Australian Government has developed Australia’s AI Ethics Principles which are foundational to Australia’s safe and responsible adoption of AI.

The policy for the responsible use of AI in government builds on this foundation and aims to ensure that government plays a leadership role in embracing AI for the benefit of Australians.

Delivery Confidence Assessment (DCA) tolerances

High

In-house expertise in the technology. Ability to challenge supplier expertise.

Off

Medium high

Significant in-house familiarity with the technology

Off

Medium

Some in-house familiarity with the technology.

Off

Medium low

Low in-house experience with the technology. Largely reliant on supplier capability.

Off

Low

No in-house familiarity with the technology. Complete reliance on contractor expertise.

Off

In-house expertise in the technology. Ability to challenge supplier expertise.
Significant in-house familiarity with the technology
Some in-house familiarity with the technology.
Low in-house experience with the technology. Largely reliant on supplier capability.
No in-house familiarity with the technology. Complete reliance on contractor expertise.

Your responsibilities

To successfully meet this criterion, you need to:

‘build once, use many times’
design for a common, seamless experience
reuse data where you can

Solution context

Because digital solutions are highly interconnected, delivery confidence can be impacted by organisational, procedural, policy, regulatory and human system interdependencies.

Delivery confidence can be:

Improved when there is evidence of strong alignment with technical architecture, policy and standards, and active management of interdependencies beyond the project’s control.
Reduced where important factors are outside the project’s control, particularly where policy or legislative reform is required, or where delivery and operational responsibilities are in separate agencies.

Solution

Technology

Delivery Confidence Assessment (DCA) tolerances

Your responsibilities

Solution context

DCA tolerances

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