EXECUTIVE LEADERSHIP
COMMUNICATION
One programme at three resolutions. Executives navigate five phases; the application is structured as seven pillars; the engine underneath executes the nine-stage pathway. Nothing is renamed between layers — each is the same work viewed at a different depth.
Align · Control · Prioritise · Deliver · Assure
Strategy · readiness · value
Data · governance · risk · privacy
Use cases · value · feasibility · AI risk
Platform · pilots · evaluation · adoption
Evidence · monitoring · attestations · compliance
Strategy · Data · Governance · Portfolio · Platform · Delivery · Assurance
Readiness baseline & investment case.
Lineage, quality & architecture fit.
Policy, risk register & oversight.
Use-case scoring & prioritisation.
Vendor & technology selection.
Pilots, evaluation & adoption.
Evidence, monitoring & attestations.
Stage I — IX · the Corporate pathway detailed below
I — Enterprise Readiness Audit
15 questions across data lineage, retention, access control, incident history and vendor exposure, scored into a readiness baseline.
II — Data Architecture Review
Connector inventory, schema drift and lineage gap analysis, with live probes against your actual warehouses.
III — Governance Stand-Up · IV — Privacy & Security Deep Dive
AI acceptable-use policy, committee charter, model inventory and vendor register — then DPIAs, FRIAs and threat modelling for high-risk use cases.
V — BU-Level Use-Case Portfolio
Score every candidate use case on business value, data readiness, time-to-pilot and EU AI Act risk penalty.
VI — Platform Decision
Build vs buy on inference, evals and observability — driven by the use cases that actually scored.
VII — Pilot Deployment · VIII — Centre of Excellence
Contained pilots with eval harness, human-in-the-loop and kill-switch, then a repeatable rollout playbook, training tracks and RACI.
IX — Continuous Compliance
Quarterly attestations, drift alerts, vendor reviews and a signed Article 9 pack export.
A nine-stage pathway that converts ad-hoc AI experiments into a regulator-ready program — with a verifiable audit chain a board, an auditor, and the EU AI Act will all recognise.
Every stage of the pathway converges on artefacts you can hand to legal, the board, or an external auditor — versioned, hashed, and timestamped.
Organisation-wide policy covering permitted use cases, prohibited content, incident reporting, employee acknowledgement.
Membership, decision rights, escalation path, meeting cadence — the cross-functional body that owns AI risk.
Every model in production: owner, purpose, training-data summary, last evaluation date, EU AI Act risk tier.
Catalogue every AI vendor touching your data with risk tier, DPA status, sub-processor chain, retention terms.
15 questions across data lineage, retention, access control, incident history, vendor exposure.
Connector inventory, schema drift, lineage gap analysis. Live probes to your actual warehouses.
AI Acceptable Use Policy, AI Committee charter, Model inventory, Vendor & DPA register.
DPIAs, FRIAs for high-risk use cases, threat modelling, secrets and PII scanning of training data.
Score each candidate use case across business value, data readiness, time-to-pilot, and EU AI Act risk penalty.
Build vs buy on inference, evals, observability — driven by the use cases that actually scored.
Three pilots with eval harness, human-in-the-loop, kill-switch, weekly review. Real users, contained blast radius.
Repeatable rollout playbook, training tracks, RACI for net-new use cases, prompt & eval registry.
Quarterly attestations, drift alerts, vendor reviews, signed Article 9 pack export.
Each stage is a structured Q&A. We synthesise the policy, charter, and inventory from your answers — you review and sign.
Drop DPAs, board minutes, training data manifests. Every file is hashed and pinned to the audit chain at upload time.
Read-only connectors to Snowflake, GitHub, Salesforce, Databricks. Probes verify lineage, retention, and access claims.
One click produces the regulator-ready bundle: cover memo, evidence index, hash manifest, signed timestamps.
Every candidate use case is scored across business value, data readiness from your live connectors, shipping speed, and EU AI Act risk penalty. The ranker re-runs as your pathway progresses.
Your Snowflake shipments and exceptions tables contain 18 months of high-quality labelled data. Low regulatory overhead. Revenue protection est. USD 240–480k per year.
340-page SOP library already indexed in Confluence. Retrieval-grounded agent cuts supervisor handover time ~35%. Advisory output, not directive — risk stays low.
High business value but classified high-risk under EU AI Act Annex III. Requires FRIA, human-oversight design, and Article 14 documentation — recommended only after Stage IV.
Article 9 · 10 · 13 · 14 · 27
Trust services criteria
AI management system
Govern · Map · Measure · Manage
Healthcare safeguards
Fed Reserve AI & model risk
Data Protection Act 2019
Personal Data Protection Act 2022
Digital Operational Resilience Act + CTPP oversight
“We replaced a six-month consultancy engagement with a 90-day pathway and walked into our SOC 2 audit with every artefact already hashed and signed. The auditor asked for the vendor register first — we had it open in another tab.”
Twelve minutes, fifteen questions, no card. You'll know within the hour whether your data stack can take an AI program — and exactly which gaps to close first.