AI systems, while transformative, can perpetuate or create biases that undermine fairness and trust. This article explores the types, consequences, and best practices for identifying and mitigating AI biases to ensure responsible governance.
As AI technology advances, global regulators are intensifying efforts to ensure responsible development through frameworks like the EU’s Artificial Intelligence Act. Companies face complex compliance landscapes across regions, needing to balance transparency, innovation, and adaptability to stay competitive.
The AI Act adopts a risk-based approach, imposing stricter legal obligations on AI systems based on their risks to health, safety, and fundamental rights. Harmonised standards are in development to ensure compliance and promote common safety and reliability criteria across the EU.
In December 2025, the Spanish Agency for the Supervision of Artificial Intelligence (AESIA) released guidance to support providers of high-risk AI systems in complying with the EU AI Act. This includes technical resources, checklists, and templates, which will be regularly updated to reflect evolving standards.
The European Commission has launched two stakeholder consultations under the EU AI Act, focusing on copyright obligations for General Purpose AI providers and the establishment of AI regulatory sandboxes. Stakeholders are invited to provide feedback by early January 2026 to help shape these important frameworks.
Testing artificial intelligence is essential to ensure the reliability, safety, and compliance of modern AI systems. Rigorous testing helps prevent errors, reduce biases, and build user trust in AI deployments.
Leonel Garciga, the U.S. Army’s Chief Information Officer, has issued a memorandum to ensure artificial intelligence products comply with records management, privacy protections, and the Freedom of Information Act. The memo details requirements for managing AI-generated records and mandates annual training for Army personnel on information security and records management.
The 1970 Fair Credit Reporting Act (FCRA) established essential definitions and accountability in credit reporting to protect consumers and ensure transparency. As AI systems increasingly impact critical sectors, a similar governance framework is needed to prevent errors that can significantly affect individuals’ lives.
The AI Act establishes a regulatory framework for AI systems in the EU, evolving through guidelines and standards to facilitate compliance. It requires member states to designate authorities to monitor AI use and includes provisions for general-purpose AI, emphasizing transparency and risk management.
Many risk management and compliance (R&C) functions are costly and labor-intensive, struggling to keep pace with business and technology. However, the responsible use of AI is unlocking new opportunities for efficiency and growth, transforming R&C teams into strategic advisors.
