AI-Ready Operations: Redesigning the Core of Business for the AI Era
Most AI projects stall at the pilot stage. The fix is not more technology. It is redesigning data, governance, teams, and culture for AI.
Perspectives on AI, governance, cybersecurity and digitalisation for boards and executive teams.
Most AI projects stall at the pilot stage. The fix is not more technology. It is redesigning data, governance, teams, and culture for AI.
Most AI pilots never scale. The reason is rarely the technology. It is data, governance, operating models, and unrealistic expectations.
AI expands the attack surface as fast as it creates value. What boards must ask before greenlighting AI adoption.
AI governance has moved from a peripheral concern to a strategic imperative. What boards must do to capture the value and manage the risk.
AI lifts efficiency but carries risks: skill loss, vendor lock-in, and shrinking junior programmes. What boards need to check now.
File uploads and shadow AI expose companies to a growing, often invisible risk of data leaks. What governance needs to deliver now.
MIT research finds 95% of enterprise AI pilots deliver no measurable return. What boards and executive teams should learn from the GenAI Divide.
A global red-teaming competition shows AI agents remain highly vulnerable to attack, with implications reaching all the way to board level.
New research shows AI-generated code often contains security gaps and quality flaws, and sets out what executive teams must verify before production use.
AI agents boost efficiency and open new entry points at the same time: data leaks, shadow IT, social engineering. Governance decides the outcome.