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Cross-Mapping AI Governance Frameworks
EU AI Act, ISO 42001, and NIST AI RMF overlap but differ. Learn how cross-mapping creates efficiency and reduces compliance risks.
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Evidence Libraries as a Foundation for AI Governance
Regulators demand evidence, not policies. Learn why structured evidence libraries are critical for AI governance and audit readiness.
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Shadow AI and the Visibility Crisis
Most AI use is invisible to IT and boards. Research shows how to close the visibility gap with inventories, discovery, and governance nodes.
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Case Study Lessons: AstraZeneca’s Ethics-Based Audit
A 12-month AstraZeneca study shows how ethics-based auditing works in practice. Culture and structure matter more than tools.
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Tooling Gaps in AI Audits: Why We Need More Than Checklists
Current AI audit tools miss harms, stakeholders, and monitoring. Research shows why infrastructure matters more than tools.
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Internal Audit and AI: Adoption Without Integration
Internal audit is adopting AI tools quickly but without integration. Research shows how to connect adoption to assurance.
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From Audit to Governance in Four Weeks-A Practical Starting Point
From Audit to Governance in Four Weeks: A Practical Starting Point FairByDesign Whitepaper | 2025 Introduction Governance in artificial intelligence (AI) is often seen as overwhelming. Leaders are bombarded with regulations, acronyms, and technical jargon, while real-world AI deployments continue without adequate oversight. Many organizations wait until regulators or investors demand formal evidence, at…
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Obstacles Beyond Technology: Why AI Governance Falters Inside Organizations
Explore why AI governance fails due to ownership gaps, culture, and structure — and how layered solutions address these barriers.
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AI in Hiring Under the EU AI Act: Compliance Risks and Bias Gaps in 2025
Executive Summary Artificial intelligence (AI) is rapidly transforming recruitment and human resources (HR) practices across Europe and globally. Tools such as applicant tracking systems, resume screeners, chatbots, and video interview platforms are now integrated into hiring pipelines that previously relied on human judgment alone. While these systems promise efficiency, they also introduce new risks…
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Bias & Safety Testing Method-Client Handout
Bias & Safety Testing Method FairByDesign | 2025 Introduction Bias and safety testing ensures that AI systems perform consistently across diverse user groups and avoid harmful or misleading outputs. The EU AI Act, GDPR, and NIST AI RMF all stress the importance of testing for fairness, safety, and accountability in AI systems (European Union,…