Practical AI governance, fitted to your organisation
AURA 3.0 engagements help organisations move from AI principles and policies to governed, evidenced and operational practice — delivered as a workshop, targeted specialist engagement, 90-day implementation, fractional governance service or multi-year maturity partnership.
Four engagement pathways
Every engagement is tailored to your AI ambitions, maturity, industry, regulatory environment, risk appetite, operating model and priority use cases. Most organisations begin along one of these pathways.
Exploring AURA
- Executive Introduction
- Governance Health Check
- CxO Governance Workshop
- Recommended implementation roadmap
Indicative package $12,000–$20,000 · please enquire
Needing Minimum Viable Governance
- Governance Health Check
- Executive alignment
- 90-day MVG implementation
- PMO & project team training
- Initial assurance review
Indicative package $75,000–$120,000 · please enquire
Operationalising existing governance
- PMO Activation
- Augmented-role design
- Testing & assurance uplift
- Organisational change integration
- Evidence automation
Indicative package $100,000–$200,000 · please enquire
Progressing to enterprise-scale & agentic governance
- Two-year maturity partnership
- Quarterly maturity reviews
- Board reporting
- Agentic readiness assessments
- Independent assurance
Indicative package $96,000–$368,000 over two years · please enquire
Ten core engagements
From a half-day executive introduction to a two-year maturity partnership. Select an engagement to see its scope, outputs and indicative pricing — or download the full catalogue as a PDF to share internally.
AURA Executive Introduction
A practical introduction to AURA 3.0 for executives, governance leaders, transformation teams and organisations beginning their AI governance journey. It explains why policies and principles alone are insufficient, and how AURA converts governance expectations into accountable work, controls, evidence, approval decisions and operational assurance.
Topics
- What AURA 3.0 is and the six AURA layers
- Layer 0 and the organisational foundations of safe AI
- The AURA governance and evidence spine
- Assist, Augment, Automate and Agentic maturity
- Minimum Viable Governance and use-case governance
- Roles, accountabilities and decision rights
- Evidence, gates, monitoring and assurance
- Practical next steps for the organisation
Outputs
- Tailored presentation
- Initial maturity discussion
- Priority issues and opportunities
- Recommended next steps
- Executive summary of findings
AURA CxO Governance Workshop
A role-based workshop for Board members, executives and senior governance leaders, covering up to eleven executive and governance roles selected by the organisation — from Board committees and the CEO through CRO, CISO, CFO, CDO, CHRO and General Counsel. Each participant examines what governed AI means for their responsibilities, decisions, exposures and assurance obligations.
Topics
- Executive accountability for AI
- Decision rights, escalation and risk ownership
- Human authority and intervention
- Vendor and third-party responsibility
- Workforce and role impacts
- Board-level evidence and reporting
- Release and operational assurance
- Agentic AI boundaries
- What each executive should ask to see
Outputs
- Executive accountability map
- Governance decision map
- Role-specific questions and responsibilities
- Initial Board and executive reporting requirements
- Agreed priority actions
AURA for Your Role
A role-specific workshop showing how AI changes a participant's responsibilities, workflows, decisions, controls and evidence obligations — configurable across the nineteen AURA augmented-role variants. The emphasis is not simply on using generative AI tools: it examines how the role changes when AI assists, augments, automates or performs bounded agentic activity.
The workshop addresses
- How AI affects the role
- Activities that can be assisted, augmented or automated
- Decisions that must remain human
- New risks, failure modes and required controls
- Evidence the role must produce
- New collaboration and escalation pathways
- Skills and capability development
- Changes to role descriptions and performance expectations
Outputs
- Role-specific AURA workbook
- Current-state and future-state activity map
- Human and AI responsibility map
- Role guardrails, evidence and decision requirements
- Personal capability development plan
- 30, 60 and 90 day role action plan
Augmented Roles and HR Integration
A multi-week engagement with Human Resources, People and Culture, organisational design, business leadership and risk teams to adapt the nineteen-role AURA augmented-role catalogue to your organisation — turning general discussion about AI workforce impact into defined responsibilities, role expectations, capability pathways and governance arrangements.
Scope
- Select relevant AURA role variants
- Analyse and update existing role descriptions
- Map current and future responsibilities
- Define human authority, accountability and restricted AI activities
- Develop capability and training pathways
- Update performance objectives
- Define supervision and escalation requirements
- Identify workforce transition impacts and align with change plans
Outputs
- Organisation-specific augmented-role catalogue
- Updated role descriptions
- Responsibility and accountability matrices
- Human and AI activity maps
- Capability and training matrix
- Role transition plans
- Governance and consultation recommendations
- Implementation roadmap
AURA PMO Activation
A 90-day engagement that embeds practical AI governance into portfolio, program and project management. The PMO becomes a key operational point for AI inventory, classification, control, delivery oversight, evidence collection, gating, reporting and escalation.
Scope
- Assess current portfolio and PMO practices
- Identify AI initiatives and establish an initiative register
- Add AI governance to intake and prioritisation
- Introduce risk classification and minimum evidence requirements
- Establish project and release gates; adapt templates
- Update governance forums and escalation pathways
- Establish portfolio-level AI reporting
- Train PMO and delivery leaders; pilot on selected initiatives
Outputs
- PMO AURA operating model
- AI portfolio inventory
- Intake and classification process
- Governance and gate model, updated templates
- Evidence requirements
- Portfolio dashboard design and escalation model
- Pilot implementation
- 12-month PMO roadmap
AURA Minimum Viable Governance Implementation
Governed AI in 90 days. A focused implementation establishing the minimum viable governance required to move from fragmented AI use or controlled pilots to a governed organisational capability. This is not a policy-writing exercise — it establishes the operating controls, accountabilities, evidence and workflows required to govern real AI use cases.
Typical 90-day structure
- Days 1–30 · Identify and design: confirm scope, assess current state, identify priority use cases, establish inventory, define classification, confirm accountabilities, design MVG
- Days 31–60 · Build and pilot: configure workflows and templates, implement controls, establish evidence requirements, pilot governance, train owners and delivery teams, establish reporting
- Days 61–90 · Operate and stabilise: run governance forums, test release and approval gates, review evidence quality, resolve gaps, establish monitoring and escalation, confirm the next maturity phase
Outputs
- AURA MVG operating model and governance charter
- AI inventory and risk classification method
- Responsibility model and control catalogue
- Evidence and assurance model
- Use-case templates and gate criteria
- Governance reporting
- Implementation backlog
- 12-month maturity roadmap
AURA Full Maturity Partnership
A part-time partnership of up to two years that helps the organisation progress through the AURA maturity model — from uncontrolled use, through controlled pilots and governed delivery, to operational assurance, enterprise-scale governance, and adaptive and agentic governance. The engagement provides continuity while internal capability, governance, evidence automation and assurance practices mature.
Services may include
- Quarterly maturity assessments and governance coaching
- Board and executive reporting
- Priority use-case reviews and control uplift
- Evidence automation and vendor governance
- Assurance reviews, incident and escalation support
- Policy and operating model updates
- Training and capability development
- Annual planning and agentic AI readiness reviews
- Independent challenge and quality assurance
Delivery models
- Strategic advisory: 2 days per month — indicative two-year fee $96,000
- Fractional AURA lead: ~1 day per week — indicative two-year fee $184,000
- Embedded maturity partner: ~2 days per week — indicative two-year fee $368,000
The engagement can be reviewed and renewed quarterly or every six months.
AURA for Organisational Change and AI
A specialist engagement addressing the workforce, behavioural, leadership and organisational impacts of AI — bringing organisational change into the governance model from the beginning, rather than treating adoption as a communications activity at the end.
Scope
- Stakeholder and workforce impact analysis
- Role, capability and accountability impacts
- Adoption readiness, trust and resistance
- Consultation requirements
- Learning and capability pathways
- Behavioural guardrails and leadership alignment
- Change risks, measures and transition planning
Outputs
- AI change impact assessment and stakeholder map
- Role impact analysis
- Adoption risk assessment
- Change strategy and leadership action plan
- Training and communication roadmap
- Adoption measures
AURA for Testing and AI Assurance
A specialist engagement helping testing, quality engineering, model evaluation, risk and assurance teams define how AI systems should be tested and evidenced. Traditional functional testing is necessary but insufficient for many AI systems.
Scope
- AI test strategy; model and system evaluation
- RAG and grounding evaluation
- Hallucination and failure testing
- Bias and fairness considerations
- Security and prompt-injection testing
- Data, permission and human oversight testing
- Tool and agent boundary testing
- Regression testing, runtime monitoring, evidence retention
- Release gate criteria
Outputs
- AURA AI test strategy
- Risk-based test catalogue
- Evaluation requirements and release criteria
- Assurance evidence model
- Defect and issue taxonomy
- Runtime test and monitoring requirements
- Testing maturity roadmap
AURA for Project Teams
A practical engagement for project managers, product owners, business analysts, architects, developers, testers, change managers, Agile teams and governance participants — showing teams how to deliver AI initiatives using AURA without creating a separate and disconnected governance process.
Scope
- AI use-case definition and risk classification
- Requirements, specifications and control requirements
- Delivery backlog integration with AURA epics and stories
- Evidence requirements and human oversight
- Vendor responsibilities
- Testing, evaluation and governance gates
- Operational readiness, handover and monitoring
Outputs
- Project-specific AURA delivery plan
- Tailored epics and stories
- Responsibility map
- Control and evidence matrix
- Gate plan and AI test requirements
- Operational readiness checklist
- Project governance dashboard
Targeted AURA services
Focused sprints and reviews that address a specific question or gap. All fees indicative — please enquire.
AI Governance Health Check
A rapid assessment of current governance maturity, gaps and priority risks.
5–10 days · $10,000–$20,000
Use-Case Discovery Workshop
The structured five-pass method: starting with work, pain points, delays, rework and control burden — not with AI technology.
2–5 days · $4,000–$10,000
Boardroom Challenge Session
An independent challenge session testing whether Board and executive claims about governed AI are supported by evidence.
1–3 days · $2,000–$6,000
Vendor & Third-Party AI Governance Sprint
Establishes the division of responsibility between the organisation, cloud providers, software vendors, AI vendors and implementation partners.
5–10 days · $10,000–$20,000
Agentic AI Readiness Review
Assesses whether you have the authority controls, identity controls, tool boundaries, monitoring, intervention and assurance required for agentic AI.
5–10 days · $10,000–$20,000
Evidence & Assurance Automation Sprint
Designs how governance and delivery tools can produce real-time evidence, metrics, gate decisions and assurance reporting.
10–20 days · $20,000–$40,000
Proof at the Gate Review
An independent review before pilot approval, production release or expansion of an AI use case.
2–5 days · $4,000–$10,000
AI Inventory & Classification Sprint
Finds known and previously unidentified AI use, establishes an inventory and applies an initial risk classification.
5–15 days · $10,000–$30,000
Fractional Head of AI Governance
Experienced AI governance leadership without establishing a full-time role immediately.
2–8 days/month · $4,000–$16,000 monthly
Train the Trainer
Builds internal capability to deliver AURA workshops, role training and governance onboarding using approved materials.
5–10 days · $10,000–$20,000
Configured to your organisation
Each AURA engagement can be configured by sector, regulatory environment, organisation size, business unit, AI maturity, selected roles and use cases, delivery methodology, technology platform, vendor environment, governance model, required artefacts and level of implementation support. Delivery can be on site, remote or hybrid — as a standalone workshop, fixed-scope sprint, embedded implementation, fractional leadership service or ongoing maturity partnership.
AURA does not replace your existing governance, risk, delivery, technology, security, change, testing or assurance disciplines. It connects them. The result is AI that is not only approved, but governed, evidenced, auditable and capable of being operated safely.
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