Responsible AI Guidance for Businesses
This document is a voluntary guidance resource produced by the New Zealand Ministry of Business, Innovation and Employment (MBIE) to help businesses implement trustworthy AI practices. It outlines three core layers of guidance: understanding your purpose for AI, establishing good business foundations (such as governance, procurement, and risk management), and managing specific AI considerations like data, modeling, and generative AI outputs. The framework aligns with international OECD AI principles while accommodating domestic values including Māori data sovereignty and New Zealand legal requirements.
Summary and content fields are drawn from the document text and are pending editorial review.
Who issued it
Who it governs
This document is for New Zealand businesses, sole traders, non-profits, and individual professionals seeking guidance on how to safely and responsibly adopt or develop artificial intelligence.
What the document contains
The document covers principles, practical tips, scenarios, and checklists for businesses using, deploying, or developing AI systems. It addresses organizational governance, risk management, legal obligations under New Zealand law, cybersecurity, privacy, stakeholder engagement, data modeling, and generative AI deployment.
It does not create legally binding mandates or sector-specific licensing laws, instead serving as a voluntary advisory framework that points to existing legislation.
- The guidance is a voluntary resource designed to help New Zealand businesses realize AI benefits responsibly.
- Effective AI integration builds on existing business functions like governance, cybersecurity, procurement, and legal compliance.
- Organizations must implement robust risk management processes, including maintaining risk inventories and conducting stakeholder impact assessments.
- Generative AI usage requires careful attention to prompt inputs, output verification, hallucination risks, and human-in-the-loop decision-making.
- Data quality and ethical sourcing—including respect for intellectual property rights and Māori data sovereignty—are critical for reliable AI performance.
· About · What is this Guidance? · Who is this Guidance for? · Why use this Guidance? · How should it be used? · Navigating the Guidance · Understanding your ‘why’ for AI · Good business foundations for responsible AI · Supporting capabilities · AI system specific considerations · Continuing the conversation · Appendix One: Glossary · Appendix Two: Checklist resources · Appendix Three: Options to ethically source datasets including copyright works · Appendix Four: Other Guidance and resources
How it scores
Each score is backed by a quote verified against the document text. Editorial review has not yet confirmed them.
Accountability
4/5Clear responsibility for AI outcomes
It is helpful to clearly document who is in charge of what, so everybody knows their role.
Governance and accountability
screening score · 2026-10-24
Fairness
3/5Non-discrimination and equitable treatment
Upholding requirements to avoid discrimination on sex, race, and other protected grounds in protected areas
Compliance and legal obligations
screening score · 2026-10-24
Human Dignity
3/5Respect for the inherent worth of persons
designing systems that respect the rule of law, human rights and democratic values
What is this Guidance?
screening score · 2026-10-24
Human Oversight
4/5Humans remain in control of consequential decisions
If an AI system is helping to make big decisions – like those about money, health, or the law – a person should always be involved.
Human-in-the-loop decision-making
screening score · 2026-10-24
Transparency
4/5Openness about how AI systems work and are used
Being clear builds trust and helps avoid problems. You can share information on what your AI systems do, how they work, and what risks they might have.
Transparency
screening score · 2026-10-24
Enforcement
1/5Consequences and compliance mechanisms with real force
This type of breach is a criminal offence attracting substantial financial penalties and potential imprisonment.
Compliance and legal obligations
screening score · 2026-10-24
Impact Assessment
4/5Required assessment of an AI system's risks/impacts before or during use
Conducting a stakeholder impact assessment can help with also identifying who is impacted and possible mitigations.
Risk management
screening score · 2026-10-24