AI can help you work more efficiently, explore information and ideas, and support better project delivery. Used well, it can complement your engineering expertise and create more time for work that relies on your professional judgement and skills.
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As AI becomes more common in engineering practice, it's important you use it responsibly. The five principles below outline what this looks like in practice and Responsible AI Practice for Engineers provides guidance on applying them in your mahi.
Five principles for responsible AI practice
You remain professionally responsible: AI supports your work but does not replace professional judgement, accountability or duty of care. Consider how its use may affect liability and insurance.
Match controls to risk: Consider the consequences, complexity and uncertainty of the task, and apply stronger oversight, verification and approval when risks are higher.
Protect information: Use approved tools and protect confidential, personal and client information and intellectual property. Understand how data may be stored, accessed and reused.
Check before you rely: Critically review outputs, including assumptions, sources, calculations and compliance with relevant standards and codes. Ensure you have the competence and time to review properly.
Be transparent and keep records: Discuss AI use with clients when it materially contributes to their work or affects their information, methodology or assurance. Record significant use, checks, decisions and approvals.
Responsible AI Practice
AI is another engineering tool. It does not replace professional competence, judgement or accountability. You remain responsible for the advice you provide, the decisions you make, and the work you approve or sign, regardless of whether AI has been used.
Putting AI governance into practice
Understand your responsibilities and approval requirements when using AI. Understand how to how to establish responsibilities, approve uses, protect information, verify work and manage change. Once you've tackled your governance approach, use the accompanying AI Policy Template to support implementation.
Talking with clients about AI
Decide when and how to discuss AI use, information handling, oversight, verification and client expectations. Understand how to explain proposed AI use clearly and proportionately. It supports informed client decisions and should be read alongside Responsible AI Practice for Engineers guidance and your AI Use Policy.
Building leadership support
Build a credible case for why AI is worth exploring, what it may cost, how the risks can be managed and how you will test whether it provides value.
Applying AI in software engineering practice
Apply appropriate controls when AI supports software development or software-enabled engineering systems. Manage AI-assisted coding, design, testing, security, review and documentation throughout the software development lifecycle.
