Generative AI’s wrong answers look just as convincing as its right ones, and a newer model won’t change that. Mehul Merchant explains the three layers of context, an ontology, a semantic model and a knowledge graph, that give enterprise AI the grounding it needs to be trusted in production.
AI governance for risk and compliance teams is ultimately about operational trust. This blog explores how financial services organisations can move Gen AI systems safely into production through clear policy frameworks, AI risk ratings, observability, lifecycle ownership, audit trails, and APRA-aligned operational controls.
AI governance for risk and compliance teams is ultimately about operational trust. This blog explores how financial services organisations can move Gen AI systems safely into production through clear policy frameworks, AI risk ratings, observability, lifecycle ownership, audit trails, and APRA-aligned operational controls.
AI governance in financial services is ultimately about trust. This practical guide explores how to build Gen AI systems that can move safely into production through accuracy, explainability, operational controls, and compliance validation. From model optimisation to auditability, learn how regulated organisations can build AI systems that users, risk teams, and regulators can confidently rely on.
