ISO/IEC 42001: What an AI Management System Actually Requires
The first certifiable management system standard for AI: what it covers, how it is structured, and what implementing it realistically involves for your organisation.
Read article →Insights
Perspectives on AI standards, independent review, data communication, and governance, from practitioners working at the intersection of technology and policy.
Navigating AI Concepts and Terminology: Key Takeaways from ISO/IEC 22989
An overview of ISO/IEC 22989, the foundational standard for Artificial Intelligence concepts and terminology, and its importance for organisations.
Read article →From Data to Insight: The Process Most Organisations Skip
Most organisations have more data than they can act on. The bottleneck is rarely collection; it's the structured process of turning raw data into decisions.
Read article →Navigating a Career in AI and Technology: Clarity Over Credentials
Career paths in AI and technology are rarely linear. Building a sustainable career requires self-knowledge, strategic positioning, and a tolerance for ambiguity, not just technical skill acquisition.
Read article →What Makes a Workshop Work: Design Principles for Lasting Impact
Most workshops fail not because the content is weak, but because they are designed around delivery rather than learning. A few structural principles make the difference.
Read article →Learning to Learn: Meta-Skills for a Fast-Changing Landscape
As AI reshapes knowledge work, the capacity to acquire new skills quickly matters more than any particular credential. This piece examines the meta-skills that sustain long-term professional growth.
Read article →Using AI Tools for Personal Productivity: A Practical Framework
How to use AI tools to genuinely improve individual productivity, moving beyond hype to durable habits that hold up in real working environments.
Read article →Making AI Results Legible: Data Visualisation for Decision-Makers
The gap between what an AI model produces and what a decision-maker needs to act on it is wider than most organisations realise. Closing that gap is a communication problem as much as a technical one.
Read article →The Cultural Dimension of AI Standards: What Working in SC42 Teaches You
Standards committees are often thought of as purely technical environments. In practice, they are intensely political and cultural, and understanding that dynamic is essential to using standards effectively.
Read article →The Case for Independent AI Review: Why Vendor Assessments Fall Short
When an AI system is assessed by the team that built it (or the vendor that sold it), the results are structurally limited. Independent review changes that equation.
Read article →ISO/IEC JTC 1/SC42: The AI Standards Subcommittee Your Organisation Needs to Know
Most organisations tracking the EU AI Act are focused on the regulation itself. Fewer are aware of the technical standards being developed beneath it, and why those standards will matter just as much.
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