AI governance
AI governance — frameworks and patterns.
Policy, classification, disclosure, audit log, approvals.
AI governance
Coming soonRICS 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.
10 min readPreview
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.
5 min readRead article
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- 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.