Insights
AI & Machine Learning
Our latest thinking on ai & machine learning.
Enterprise AI Model Risk Management: A Governance Framework
As AI models move beyond finance into clinical triage, workforce planning, and supply chain allocation, traditional model risk frameworks require fundamental reinterpretation for non-financial risk leaders.
Enterprise AI Supply Chain Risk: A Governance Framework
As AI capabilities are increasingly consumed through layered third-party relationships, enterprises need a principled governance framework to identify where strategic vulnerability hides inside seemingly routine vendor arrangements.
Enterprise AI Inference Cost Governance: A Framework for Sustainable Scaling
As AI moves from pilot into production, inference costs become the dominant financial liability—and only a structured governance framework can keep that liability aligned with business value.
AI Memory Governance: Managing Context Across Enterprise AI Systems
As organisations deploy AI systems across multiple functions, governing what those systems remember, share, and validate has become one of the most consequential and least-addressed problems in enterprise AI strategy.
Enterprise RAG Governance: A Senior Leader's Framework
Enterprise RAG governance is a board-level responsibility, not an engineering detail — and organisations that treat it as such will produce AI outputs that are auditable, reliable, and fit for regulated environments.
Enterprise MLOps Operating Model: Governing the Model Lifecycle
Most organisations treat model deployment as the finish line, yet the greatest operational risk in enterprise AI emerges long after a model goes live.
Enterprise AI Observability: The Operating Model Leaders Need
Enterprise AI observability is the structured discipline of monitoring, auditing, and acting on AI model behaviour after deployment — and it demands board-level accountability.
Enterprise Prompt Governance: An Operating Model for AI at Scale
As AI systems proliferate across business functions, the prompts that instruct them become a form of organisational policy — and governing them demands a structured operating model, not individual improvisation.
The AI Business Case Paradox: Why ROI Frameworks Fall Short
Traditional ROI frameworks systematically undervalue transformational AI investments by measuring the wrong things at the wrong time.