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AI Governance

Business owner reviewing AI use across sales, meetings, marketing, finance and customer service, highlighting the need for visibility before AI governance

Business owner reviewing AI use across sales, meetings, marketing, finance and customer service, highlighting the need for visibility before AI governance

Shadow AI: Your Business Is Already Using AI. Do You Know Where?

Shadow AI may already be operating in your business. Learn how to discover which AI tools your team uses, what data they share and where the opportunities and risks are.

10 min read

Infographic titled “Secure AI Coding Agents: 6 Principles for Safer Outcomes,” showing an AI agent behind a security shield surrounded by six principles: separate identities, limit access, protect trust boundaries, control high-impact actions, keep agent configuration immutable, and log all activity. The central message reads, “Good architecture makes mistakes less dangerous.”

Infographic titled “Secure AI Coding Agents: 6 Principles for Safer Outcomes,” showing an AI agent behind a security shield surrounded by six principles: separate identities, limit access, protect trust boundaries, control high-impact actions, keep agent configuration immutable, and log all activity. The central message reads, “Good architecture makes mistakes less dangerous.”

AI Agent Security Risks: Why Coding Agents Keep Breaking Trust Boundaries

AI coding agents have had a difficult few months for security. In July, researchers demonstrated that a public GitHub issue could manipulate an agent into retrieving information from a private repository. Another piece of research showed how symbolic links could undermine the approval controls used by six different coding assistants. Separately, developers have reported coding agents executing destructive database operations without adequately signaling the consequences. Thes

8 min read

Infographic showing four places AI adoption can create new data exposure: inference location, prompt and context data leaving the organisation, vendor training and fine-tuning, and third-party subprocessors or embedded AI features. It illustrates data flowing from internal systems through a user to external AI providers, with continuous governance controls across the entire flow

Infographic showing four places AI adoption can create new data exposure: inference location, prompt and context data leaving the organisation, vendor training and fine-tuning, and third-party subprocessors or embedded AI features. It illustrates data flowing from internal systems through a user to external AI providers, with continuous governance controls across the entire flow

AI Data Sovereignty: Where Does Your Data Go When It Passes Through an AI Model?

Most organisations know exactly which data centre region their core platform lives in. Almost none can answer the same question for AI. Here's where your data actually goes the moment it touches an AI model, and why the answer matters more than most governance frameworks currently account for.

7 min read

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