AI Act Readiness & Governance
Turn regulatory uncertainty into structured governance.
EU AI Act
IEEE CertifAIEd
The EU AI Act is the first comprehensive horizontal AI regulation, in force, with extraterritorial scope. We help organisations move from an unknown AI landscape to a documented, classified, and governed one. Our assessment instruments are mapped to the IEEE CertifAIEd criteria and, for Saudi Arabia, to SDAIA’s AI Adoption and National AI Risk Management Frameworks, with PDPL registration and transfer risk assessment built into the scope.
AI Act Readiness & Governance
Prepare AI systems for governance, classification, risk management, and compliance.
EU AI Act · SDAIA
The Challenge
Most organisations do not know what AI they are actually using.
The EU AI Act requires organisations to map their AI systems, classify them by risk tier, implement documentation and governance controls, and manage third-party AI exposure. Penalties for non-compliance reach €35 million or 7% of global annual turnover, whichever is higher. In Saudi Arabia, SDAIA’s AI Adoption Framework and National AI Risk Management Framework set the equivalent expectations, layered over the PDPL and the NCA controls.
The challenge is not knowing what the regulation says. The challenge is understanding how it applies to the specific AI systems your organisation operates, internal tools, analytics platforms, embedded third-party AI, and vendor solutions, and building the governance structure to manage them.
Our AI Act Readiness service gives you that visibility, that structure, and that governance model. Our assessment instruments are mapped to the IEEE CertifAIEd criteria, so AI-ethics rigour is built into the assessment itself rather than added as a certification exercise.
“Compliance is the artefact.
Governance is the asset.”
The deliverable is not a report. It is a governance model that operates.
Regulatory Scope
In force across the EU and with extraterritorial scope. Applies to organisations placing AI systems on the EU market, regardless of where they are headquartered. In Saudi Arabia, SDAIA’s frameworks, the PDPL and the NCA controls apply — building to the EU AI Act clears the bar on system governance but does not deliver Saudi compliance.
Ethics Criteria
IEEE CertifAIEd Criteria
Our AI Act instruments are mapped to the IEEE CertifAIEd criteria — transparency, accountability, algorithmic bias and privacy — so ethics rigour is part of the governance structure itself, not an add-on.
What We Assess
Six governance areas. Covered comprehensively.
Our AI Act Readiness engagement covers the full governance lifecycle, from initial AI landscape visibility to the controls, documentation, and accountability structures that make governance operational.
AI Landscape Visibility
Establish a complete and current inventory of every AI system in use across the organisation, internal tools, analytics platforms, embedded third-party AI, and vendor-supplied solutions. Visibility is the precondition for everything that follows.
Risk-Based Classification
Classify each AI system under the EU AI Act’s four-tier risk framework: unacceptable risk, high risk, limited risk, and minimal risk. The classification determines the compliance obligations that apply, and who is accountable for them. For Saudi deployments, we classify against SDAIA’s risk framework in parallel.
Compliance & Control Readiness
Evaluate existing controls, documentation, conformity assessment readiness, and technical obligations against EU AI Act requirements. Identify gaps with sufficient precision to close them, not just to acknowledge them. Where the PDPL applies, registration and transfer risk assessment are part of the scope.
Responsible AI Governance
Build the accountability structures, approval processes, monitoring mechanisms, and human oversight controls that the EU AI Act requires, mapped to the IEEE CertifAIEd ethics criteria so that governance goes beyond minimum compliance.
Vendor & Third-Party AI Oversight
Assess the AI embedded in vendor platforms and third-party systems, where AI Act obligations still apply even when the organisation does not directly control the model. Build vendor assessment and oversight protocols into the governance model.
Future-Proof AI Adoption
Build the governance structure that governs the next AI system before it goes live, not just the ones already in use. A repeatable assessment and approval framework ensures AI adoption does not outpace AI accountability as the technology continues to evolve.
Ethics Criteria We Map To
IEEE CertifAIEd Criteria
IEEE CertifAIEd is the IEEE’s AI-ethics assessment programme; certification under it is performed by IEEE Authorized Assessors. Unlike internal ethics frameworks or self-assessments, it provides an internationally recognised methodology that carries weight with stakeholders, oversight bodies, and regulators.
Our AI Act Readiness instruments are mapped to its four criteria, so the ethics dimension is an integrated layer of the governance model rather than a separate add-on. The result is an AI Act deliverable that goes beyond minimum compliance to produce substantive, ethics-grounded governance.
Transparency – AI systems are explainable and their decision logic can be communicated to affected stakeholders.
Accountability – Clear accountability chains for AI outcomes, including when those outcomes are adverse or unexpected.
Algorithmic Bias – Identification and mitigation of unfair patterns in AI outputs that affect individuals or groups differently.
Privacy – Assessment of data handling practices in relation to AI systems, aligned with GDPR requirements.
What You Gain
The outcomes that hold up.
AI Act readiness done properly delivers more than regulatory compliance. It delivers a governance operating model that holds up to auditors, regulators, your own board, and the next AI system your organisation adopts.
Clarity
A complete, current picture of every AI system your organisation uses, and what each one means for compliance.
Control
Governance structures, approval processes, and monitoring mechanisms that make AI oversight operational, not aspirational.
Confidence
A defensible position grounded in internationally recognised frameworks, not internal self-assessment.
Trust
Stakeholder, investor, and customer confidence built on visible, documented, ethics-grounded AI governance.
Ready to Begin
Let's map your AI landscape and build the governance model.
Every engagement begins with a consultation to understand your organisation’s AI footprint, regulatory context, and governance objectives. From there, we scope the engagement to what your organisation actually needs.