FAIrMind is a global advisory firm helping organisations design, implement and audit Responsible AI Governance — fluently across six regulatory landscapes, anchored in international standards, and integrated with the enterprise risk and continuity programmes that already protect the business.
From AI inventories and use-case classification to model risk frameworks, board reporting and audit-ready evidence. We translate principle into policy, and policy into operational control.
AI does not sit alone. We integrate AI risk into the broader ERM lens — taxonomies, appetite, KRIs, control libraries — using ISO 31000, COSO ERM, and the IIA's Three Lines model as the common operating language.
Operational, technological and AI-induced disruption demand continuity that holds up under pressure. We build BCMS programmes aligned to ISO 22301, with AI-aware impact analysis, dependency mapping and rehearsed response.
Risk-tiered obligations for prohibited, high-risk, GPAI and limited-risk systems. Conformity, technical documentation and post-market monitoring.
The certifiable management-system standard for AI: policy, leadership, planning, lifecycle controls, and continual improvement.
Guidance on integrating AI-specific risk into ISO 31000 — process, principles, and the connective tissue between AI and ERM.
Govern · Map · Measure · Manage. The voluntary US framework that operationalises trustworthy AI characteristics across the lifecycle.
Central Bank of the UAE expectations on AI use within licensed financial institutions — model governance, fairness and accountability.
Singapore's evolving framework for agentic AI systems — autonomy, tool-use, and the governance practices that scale with capability.
The umbrella risk-management standard — principles, framework and process — into which AI risk must fit cleanly.
Integrating risk with strategy and performance — the framework most boards and audit committees expect to see referenced.
The certifiable BCMS standard — impact analysis, recovery strategies, exercise programmes — extended to AI-induced disruption.
The frameworks differ. The fundamentals don't. We help leaders satisfy regulators in every jurisdiction without re-building the programme each time.
Designed and rolled out an end-to-end AI governance framework spanning the client's offices in the Americas, European Union and South-East Asia. The work covered AI inventory and use-case classification, policy and operating model, lifecycle controls, and the assurance evidence the business needed to satisfy diverse regulators and enterprise customers under one coherent programme.
Built a single, coherent resilience architecture for a UK firm whose product line is AI-driven. Connected enterprise risk management, AI-specific risk and the business continuity programme so they share taxonomy, appetite, controls and reporting — eliminating the gaps and duplication that typically appear when these disciplines run in parallel silos.
Designed and built a multi-modal underwriting tool for a fintech client — bringing together conversational AI for applicant interaction, computer vision for document and identity verification, and machine learning for credit-risk scoring. Delivered with the governance, model risk and explainability controls that regulated lenders require around production AI.
Maturity assessment, AI inventory, use-case classification and gap analysis against the frameworks that apply to you.
Operating model, policies, risk taxonomy, control library and governance forums — designed to fit your organisation, not a template.
Roll-out across the three lines, training and change, tooling integration, evidence and reporting that withstand scrutiny.
Internal audit support, certification readiness, regulatory horizon-scanning and continuous improvement of the programme.
If your board, regulators or customers are asking sharper questions about AI than your programme can currently answer — that is the moment we are built for. Tell us where you are; we'll respond within two business days.