Make AI usage procurement-safe, auditable and controlled.
Adopt AI without losing control.
AI Governance Policy Pack
- Workflow
- Templates
- Evidence
- Approvals
- Audit log
Adopt AI safely
- Acceptable use policy (AUP)drafting
- R/A/G data classification rulesdrafting
- Human approval gatesdrafting
- Audit trail + immutable logsdrafting
- DPIA templatedrafting
30-second walk-through
Watch AI Governance Policy Pack run on a real engagement.
Recorded inside the BuiltAI app against a redacted client dataset. Same QA gates, same evidence pattern, same approval rhythm you'll get on day one.
Walk-through landing soon
We're recording the AI Governance Policy Packwalk-through against a redacted pilot dataset. Drop us a note if you'd like an early preview.
What gets installed
Productised workflow components
Each item below is delivered as a templated, governed workflow piece - not a bespoke build. Same QA gates apply regardless of which pack you start with.
What we need from you
To run a useful audit and deploy this pack
We don't need everything up-front - but the more of the below we can see early, the sharper the diagnostic and the faster the workflow lands.
- Current AI / IT acceptable-use policy if any
- List of AI services in use (sanctioned or otherwise)
- Procurement / supplier code requirements you need to meet
- One nominated governance sponsor (often legal / compliance)
- Sample contract schedule template you'd want AI clauses inserted into
The pattern
What this pack solves and how it lands
Problem
Teams often know the issue exists, but lack a repeatable workflow, ownership model and reporting structure to control it.
Commercial impact
Unclear ownership and inconsistent evidence create rework, delay, margin pressure and governance risk.
Success criteria
Clear owners, consistent templates, visible status, QA checks and a repeatable reporting rhythm.
Governance controls
Evidence index, assumptions register, QA gates, client approval and professional boundary wording where required.
Outcomes
What "done" tends to look like
Every figure below carries a disclosure label per BuiltAI's governance approach. Actual findings depend on contract value, data quality and commercial-process maturity.
100%
Of AI invocations classified + logged
0
Red-classified data reaching any AI service
1
Procurement-ready disclosure schedule per client
Sits alongside
BuiltAI runs alongside the systems your team already uses - it does not replace them. This pack is built to fit:
- Microsoft 365 Copilot
- Google Workspace
- Internal RAG / custom AI
- Procurement questionnaire workflows
A BuiltAI output, in five seconds
What this pack actually returns.
Every BuiltAI output is scoped to a pack and traced to a source. That's what makes it a governed output, not just an LLM call.
Internal AI use request
Site team asks: can we use a public LLM to summarise this 90-page method statement before tomorrow's site meeting? Document is marked 'commercial in confidence.'
BuiltAI output
Decline (per AI Use Policy §3.2 - confidential docs not permitted on public endpoints). Approved path: route via BuiltAI summarisation workflow, which keeps document inside tenant boundary. Estimated turnaround 6 minutes. Audit row written: requester, doc class, decision, alternative offered.
Governed by: AI Governance Policy Pack v1 - acceptable-use gates
Cited from: BuiltAI AI Use Policy §3.2 + data classification matrix
When procurement asked us how we were governing AI, we sent them the policy pack and the audit log structure on the same day. Conversation went from twelve weeks to two.
Common questions
Buyer FAQs about AI Governance Policy Pack
Do we need this if we're not yet using AI internally?
Yes - especially if you're about to. The Policy Pack lands the rules, classification scheme and approval gates *before* AI use scales. Trying to retrofit governance after AI is widespread is what creates the procurement scramble we see most often.
What's R/A/G data classification, and where does it apply?
Three tiers: Red (no AI - personal data, security-sensitive, regulated), Amber (gated AI use with source-backed review), Green (approved AI use). Classification runs at the upload boundary across every BuiltAI workflow. Rules are published in the Policy Pack for your team to apply.
Will procurement teams accept the AI Schedule?
It's designed for procurement-questionnaire compatibility - covers IP terms, sub-processing, liability cap, training-data exclusion, audit rights and disclosure language. Most procurement teams accept it without negotiation; the rare changes are usually liability cap or disclosure wording.
How it works
Where this pack sits in the engagement model
Step 1 - Discovery
Operational Intelligence Audit™ - fixed-scope, four-week engagement with QA2 sign-off.
Step 2 - Deploy
Controlled workflow deployment - AI-assisted, QA-gated, client-approved before issue.
Step 3 - Embed
Ongoing governance rhythm - monthly board reports, RAG reviews, continuous improvement.
The foundation underneath every other workflow - usually deployed in Step 2 alongside the first pack.
Adjacent workflows
Pairs well with this pack
AI Governance is the audit trail every other pack references - Bidroom uses it for tender models, RAMS for safety drafting, Commercial Control for variation narratives. Pair them when AI sits anywhere on the critical path.
Illustrative scenarioAI Governance FoundationPre-construction team adopting AI tools without classification, approval gates or disclosure language in client outputs.Read the scenarioLong-form on this topic
Read deeper into ai governance.
Frameworks and checklists from the audit playbook - same discipline that the AI Governance Policy Pack workflow installs.
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.
10 min readAI 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 read
Engagement modes
AI Governance Policy Pack sits inside one of three engagement modes.
Indicative ranges - confirmed in the SOW after the discovery call. Full pricing breakdown.
Discovery audit
From a four-figure fixed fee
2 weeks · audit-only
- Most common
Pilot pack
From low five figures
6–10 weeks · AI Governance Policy Pack
Governance retainer
From a four-figure monthly fee
Rolling · 3-month minimum
Ready to scope this pack against your real data?
Book a readiness call. We'll confirm whether this pack, an audit, or a different starting point fits your operation.