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AI Governance, Risk & Responsible AI

The framework, controls and evidence base that make AI use defensible to a board, an auditor and a regulator.

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Milestone based, or time and materials for evolving scopeDELIVERY MODEL

The problems this practice exists to solve

No complete picture of where AI is already being used
Uniform controls that either block low-risk use or under-govern high-risk use
Boards asking questions about AI that management cannot answer
Obligations emerging faster than internal capability
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HOW THIS PRACTICE IS ORGANISED

5 specialist areas

Pick the one that matches your problem, or search the full list below.
AI Governance FoundationsAI system inventory and use-case registerAgent GovernanceAgent registry with owner, purpose, permissions and versionAI Assurance & TestingTest plan and adversarial test executionRegulatory AlignmentObligation mapping for the applicable jurisdictionsAI Assurance OperationsIncident process, roles and reporting templates

Every service in this practice

Every service, grouped by sub-practice
AI Governance FoundationsExplore AI Governance Foundations ›
AI Governance & ComplianceThe framework, controls and evidence base that make AI use defensible to a board, an auditor and a regulator.Responsible AI ControlsPractical implementation of fairness, transparency, accountability and human oversight controls in delivered systems.AI Ops, Governance & GatewayOperational governance of AI systems in production, including access gateway, usage policy enforcement and monitoring.AI System Inventory & DiscoveryA complete, maintained register of every AI system in use across the organisation, including embedded and vendor-supplied capability.Shadow AI Discovery & RemediationIdentification of unsanctioned AI tool use across the organisation, with risk assessment and a route to sanctioned alternatives.AI Use-Case Register & Intake ProcessA governed intake process through which every proposed AI use case is recorded, assessed and approved before development.AI Risk Classification & TieringClassification of each AI system by autonomy, data sensitivity, decision impact and access, driving the controls that apply to it.Algorithmic Impact AssessmentStructured assessment of the potential impact of an AI system on individuals, groups and the organisation, with mitigations.Model Card & System Card DocumentationStandardised documentation of each model and system covering purpose, data, limitations, evaluation results and approved use.Model Registry & LineageCentral registry recording every model version, its training and evaluation data, its approvals and its deployment history.AI Asset Criticality MappingAssessment of which AI systems are business-critical and what the consequence of their failure would be.AI Dependency MappingMapping of the models, data sources, vendors and infrastructure each AI system depends on.AI Portfolio ReportingConsolidated reporting on the AI estate covering value delivered, risk exposure, cost and compliance status.
Agent GovernanceExplore Agent Governance ›
Agent Registry & Agent Identity ManagementRegistration and identity management for every agent as a distinct non-human actor with an owner, a purpose and a permission set.Autonomy-Tiered Governance DesignA governance model with different controls at each level of agent autonomy, replacing uniform controls that either block low-risk agents or under-govern high-risk ones.Agent Permission & Blast-Radius DesignDefinition and limitation of what each agent can reach and change, so the consequence of failure is bounded by design.Agent Approval & Release GatesFormal gates an agent must pass before it is granted production access or an increase in autonomy.Agent Behaviour MonitoringContinuous monitoring of agent actions against expected behaviour, with alerting on deviation.Agent Kill-Switch & Containment DesignThe technical and procedural ability to suspend an agent immediately and contain the effect of its recent actions.Agent Accountability & Ownership AssignmentNamed human accountability for every agent in production, with defined responsibilities and review obligations.
AI Assurance & TestingExplore AI Assurance & Testing ›
AI Red TeamingStructured adversarial testing of AI systems to find harmful, non-compliant or incorrect behaviour before users or regulators do.Prompt Injection & Jailbreak TestingTargeted testing of a system's resistance to instruction injection through user input, documents and retrieved content.Bias, Fairness & Disparate-Impact TestingMeasurement of whether an AI system produces materially different outcomes across groups, with documented findings and mitigations.Explainability & Interpretability ImplementationImplementation of the technical means to explain why a model or agent produced a particular output.AI Transparency & User Disclosure DesignDesign of how and where users are told they are interacting with AI and what it can and cannot do.Third-Party & Supply-Chain AI Risk AssessmentAssessment of AI capability embedded in vendor products and services, and the risk it introduces.Vendor AI Due DiligenceStructured evaluation of an AI vendor's models, data handling, security, evaluation practice and contractual commitments.Training-Data Provenance GovernanceControls establishing where training and fine-tuning data came from, what rights attach to it and how it is retained.Copyright & IP Risk Assessment for GenAI OutputsAssessment of intellectual property and copyright exposure arising from generative AI outputs and the controls that reduce it.ISO/IEC 42001 ReadinessGap assessment and preparation for certification against the ISO/IEC 42001 artificial intelligence management system standard.ISO/IEC 42001 Implementation & Certification SupportFull implementation of the AI management system, internal audit, corrective action and support through external certification audit.
Regulatory AlignmentExplore Regulatory Alignment ›
NIST AI Risk Management Framework AlignmentMapping of the organisation's AI controls to the NIST AI Risk Management Framework with gap remediation.EU AI Act Readiness & Conformity AssessmentClassification of AI systems under the EU AI Act and preparation of the technical documentation and conformity evidence required.Australian Voluntary AI Safety Standard AlignmentAssessment and implementation against Australia's voluntary AI safety guardrails.NSW AI Assurance Framework CompliancePreparation of the assessment and evidence required by the New South Wales AI Assurance Framework for government-facing systems.Australian Federal AI Policy ComplianceAlignment with Commonwealth policy for the responsible use of AI in government, including accountability and transparency obligations.Saudi SDAIA AI Ethics Principles ComplianceAlignment of AI systems with the Saudi Data and Artificial Intelligence Authority's AI ethics principles.Saudi NDMO Data Governance ComplianceImplementation of the National Data Management Office's data governance and classification requirements.Saudi PDPL ComplianceAssessment and implementation of controls required by the Saudi Personal Data Protection Law.UAE AI Charter, DIFC & ADGM ComplianceAlignment with the UAE AI Charter and the data protection regimes of the DIFC and ADGM financial free zones.AI Procurement & Contract Clause DraftingDevelopment of AI-specific contractual positions covering IP, liability, data use, evaluation rights and exit.
AI Assurance OperationsExplore AI Assurance Operations ›

What we deliver

AI system inventory and use-case register
Risk classification and tiering model
Governance framework, forums and decision rights
Control library with evidence requirements
Board and executive reporting pack
Capability uplift and handover

The outcomes that follow

A complete and maintained view of the AI estate
Controls proportionate to actual risk
Answers available when the board asks
A defensible position with regulators
Faster approval for low-risk AI use
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How every engagement runs

01Discoverconfirm objectives, stakeholders, constraints and success measures
02Assessreview current systems, data, controls and delivery readiness
03Designprepare the target design, backlog, governance and implementation plan
04Validatetest the priority requirements through a prototype, pilot or controlled design review
05Implementconfigure, integrate, test and deploy the approved solution
06Enabletrain users, transfer knowledge and establish operating procedures
07Optimisemonitor adoption, performance, cost, quality and improvement opportunities
BUILT FORGovernment agencies and regulated public-sector bodiesBanks, insurers, superannuation funds and professional-services firmsHealthcare providers, aged-care operators and NDIS businessesUtilities, energy and resources operators
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OUR CUSTOMERS

What our customers say

Real feedback from the organisations we build with — what changed, in their words.

All customer stories
Reconciliation that took our team nine days now closes in three — with a full audit trail on every match. It changed how the board sees AI.
Finance ManagerGCC Construction Group, Dubai
Site teams stopped digging through folders. They ask the assistant, they get the clause with a citation, and they move on.
Project DirectorTier-One Contractor, Sydney
The anomaly models flag outliers the week they appear, not at quarter-end. We stopped two overruns before they hit the P&L.
Commercial DirectorProperty Developer, Dubai

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