AI governance - frameworks and patterns.
Policy, classification, disclosure, audit log, approvals.
AI governance
Why most internal AI tools never ship
The tool that never gets prioritised, the pilot that dies in procurement, the proof of concept that impresses everyone and then sits there. Four mechanisms, none of them technical - and the cases where building anything at all is the wrong call.
AI governance
RICS responsible use - the practical reading for FM, M&E and surveying teams
RICS guidance on responsible AI use is not a checklist - it is a competence framework. We translate the four pillars (data integrity, professional judgement, disclosure, accountability) into the exact policies, gates and audit trails a regulated practice needs.
AI governance
An AI governance baseline procurement teams will accept
What procurement actually want to see - a policy, a classification rule, an audit log and a refusal path. Practical, not theatrical.
Other categories
Browse by topic.
- Commercial controlNotices, instructions, variations, evidence and the monthly commercial rhythm.
- Tender qualityBid intake, clarifications, structure, evidence and QA discipline.
- RAMS & methodTask-based RAMS, evidence chains, golden-thread alignment, approvals.
- Service deskTriage, SLA recovery, ticket QA, knowledge capture.
- Reporting & boardsMonthly cadence, KPI design, board pack assembly, exception logs.
- Contract obligationsClause translation, owners, evidence requirements, compliance log.