ISO Standards and AI in practice
Artificial Intelligence is transforming industries, but with innovation comes responsibility How do we make sure AI systems are safe, ethical, and trustworthy?
Artificial Intelligence is transforming industries, but with innovation comes responsibility How do we make sure AI systems are safe, ethical, and trustworthy?
Artificial Intelligence is transforming industries, but with innovation comes responsibility How do we make sure AI systems are safe, ethical, and trustworthy? One of the most effective tools is the family of ISO standards. These are globally recognised rules and guidelines that set common benchmarks for quality, safety, and responsibility.
For AI, ISO standards go beyond technical checklists. They work together to create a layered system of governance, management, risk control, and impact assessment. This ensures that AI aligns with organisational values, meets legal and ethical expectations, and protects people and society.
ISO standards provide a shared language for organisations worldwide, helping businesses improve the quality and safety of AI systems while increasing efficiency and reducing waste. By aligning to these standards, organisations can build trust with customers, regulators, and stakeholders, as well as reduce risks and liabilities. They also play a vital role in breaking down barriers to international trade and collaboration by offering common benchmarks across borders. For AI in particular, ISO standards provide a practical framework to embed responsible practices across the entire lifecycle of a system, from initial design through to deployment, monitoring, and eventual decommissioning.
Role: Sets the strategic foundation for how AI is governed at board and executive level.
Core Considerations:
Summary: This is the “why and what” layer which ensures AI serves the organisation’s mission while responsibly addressing risks.
Role: Translates board-level strategy into daily practice through an AI Management System (AIMS).
Core Considerations:
Summary: This is the “how” layer which acts as the operational engines that ensures responsible AI is consistently applied across projects.
Role: Provides risk management processes which are tailored to AI and are aligned to ISO 3100.
Core Considerations:
Summary: This is the “what could go wrong” layer which helps organisations anticipate and act on AI risks before they escalate.
Role: Provides a methodology for assessing the impacts of individual AI systems.
Core Considerations:
Summary: This is the “microscope” layers which zooms in on specific Ai systems to understand their real-world effects.
For businesses and governments, ISO standards give confidence that AI is being managed responsibly by clearly defining who does what and why it matters. At the top, boards gain clear governance and accountability structures, ensuring that AI initiatives align with organisational values and strategic goals. Managers benefit from practical processes that allow them to embed responsible practices across daily operations, turning governance commitments into reality.
Regulators gain assurance that organisations are following recognised global best practices, making compliance more transparent and consistent. Finally, society benefits through protection from harm and greater trust, knowing that AI systems are designed and managed in ways that serve the public good.
Commitment and Disclaimer
The Responsible AI Hub provides resources for learning, examples of AI in action and support for responsible AI. Use of these materials does not create any legal obligations or liability with the AICC.
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