Practical governance and delivery for AI management systems — enabling innovation while managing risk, transparency, accountability, and compliance. Designed to support ISO 42001 implementation, aligning to NIST AI RMF and the EU AI Act, while remaining focused on real-world AI oversight.
Speak to a SpecialistMost clients start with an AI Governance Readiness Assessment (typically 1–2 weeks) to clarify scope, AI inventory, key risks, and a pragmatic implementation roadmap.
Assess current governance maturity, obligations, and control gaps against ISO 42001 principles and Annex A themes.
Deliverables: gap report, priority risks, quick wins, implementation roadmap
Typical duration: 1–2 weeks
Build an AI system inventory and classify use-cases by risk, criticality, data sensitivity, and impact.
Deliverables: AI register, classification model, ownership/RACI, approval thresholds
Typical duration: 1–3 weeks
Assess risks (bias, privacy, security, safety, explainability) and define practical controls and guardrails.
Deliverables: AI risk register, control catalogue, mitigation plan, residual risk sign-off pack
Typical duration: 2–4 weeks
Define governance roles, decision rights, policies, and procedures that fit your delivery and product lifecycle.
Deliverables: AI governance policy suite, operating model, approval workflow
Typical duration: 3–6 weeks
Strengthen dataset controls: provenance, quality, consent, retention, lineage, access, and training data suitability.
Deliverables: dataset governance controls, data quality checks, lineage approach
Typical duration: 2–6 weeks
Define governance across development, testing, release gates, monitoring, drift detection, transparency, and change control.
Deliverables: lifecycle gates, testing strategy, monitoring KPIs, rollback playbooks
Typical duration: 3–8 weeks
Independent assurance of AI governance effectiveness, readiness for certification, and executive review materials.
Deliverables: audit plan, audit report, findings & corrective actions, management review pack
Typical duration: 1–2 weeks
Hands-on support to implement controls, organise evidence, coach teams, and support certification audits.
Deliverables: implementation tracker, evidence index, audit coaching, closure support
Typical duration: 6–14 weeks
A structured approach that creates real governance (not paperwork) and embeds AI oversight into delivery, operations, and decision-making.
Define scope, build the AI register, set ownership, and classify use-cases.
Assess AI risks, validate obligations, and prioritise controls using a pragmatic roadmap.
Deploy policies, workflows, lifecycle gates, monitoring, and evidence structures.
Assurance checks, internal audit, management review, and continuous improvement.
Choose the engagement that matches your current AI maturity. We align with leading practices and support ISO 42001 readiness while staying focused on practical delivery, transparency, and oversight.
A short, structured session to establish a baseline and highlight priority risks.
Ideal for: leadership alignment
You get: Indicative maturity view + key decision points
Duration: 30–60 minutes
A structured assessment covering inventory, risk, gaps, and an implementation roadmap.
Ideal for: Scaling AI, preparing for compliance
You get: AI register + 90-day roadmap
Duration: 3-4 weeks
Build and embed governance into the AI lifecycle — policies, controls, and monitoring.
Ideal for: enterprise AI adoption
You get: operating model + lifecycle controls
Duration: 6–14 weeks
For ongoing oversight, we also offer AI Governance Assurance (internal audit, management review support, and continuous improvement).
Delivered by experienced practitioners focused on practical governance, evidence, and measurable oversight.
Controls tailored to real AI risks (bias, privacy, security, safety) and your operational context.
Where needed, we align AI governance with information security and business resilience for a consistent control environment.
We keep documentation minimal and focus on the evidence auditors and executives actually need.
