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Build Your Office of Responsible AI

Identify, triage, and govern every AI use case in your organisation

The EU AI Act requires organisations deploying high-risk AI systems to have governance frameworks operational by August 2026. Most organisations lack the structured approach to classify, assess, and govern their AI portfolio.

S.AI.L builds your Office of Responsible AI — applying best practices from Anthropic's Responsible Scaling Policy, Constitutional AI principles, and EU AI Act requirements to create a governance function that scales with your AI ambition.

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EU AI Act compliant. Anthropic-aligned. Principal-led. Your cloud.

Aug 2026

EU AI Act compliance deadline for high-risk AI systems — organisations must have governance frameworks operational

EU AI Act, Article 113

74%

of enterprises say AI delivered less value than expected — governance gaps are the primary cause

BCG, 2025

2.5–3×

higher ROI when AI transformation is governance-first and principal-led

McKinsey, 2024

€35M

maximum fine for non-compliance with EU AI Act prohibited practices — up to 7% of global annual turnover

EU AI Act, Article 99

How it works

Four-stage delivery process

From AI inventory to sustainable governance — a structured approach to building your Office of Responsible AI

Stage 01

AI Inventory & Risk Classification

Catalogue every AI system in your organisation — internal builds, third-party tools, embedded AI in SaaS products, and emerging use cases. Each system is classified against the EU AI Act's four risk levels and assessed against Anthropic's AI Safety Levels (ASL) framework as a capability overlay. This dual classification identifies both regulatory obligations and technical safety requirements

Stage 02

Triage & Impact Assessment

For high-risk use cases, conduct Fundamental Rights Impact Assessments per EU AI Act Article 27. For prohibited use cases, develop immediate cessation plans. Apply Anthropic's Constitutional AI safety hierarchy — safety and oversight first, then ethics, compliance, and helpfulness — as the decision framework for prioritisation. Document affected populations, deployment timelines, and human oversight requirements

Stage 03

Risk Mitigation & Governance Design

Establish the cross-functional governance structure: AI Ethics Committee with CTO, CRO, Legal, and Business representation. Implement the appropriate conformity assessment pathway — internal self-certification (Annex VI) or third-party assessment (Annex VII, mandatory for biometric identification). Design quality management systems per Article 17, including monitoring dashboards, approval workflows, and incident escalation protocols

Stage 04

Operationalise & Sustain

Embed responsible AI into the operating model — not as an overlay, but as a structural property of how AI is developed, deployed, and monitored. Continuous monitoring covers model drift, bias detection, and performance degradation. Post-market surveillance per EU AI Act requirements. Annual re-assessment against Anthropic's RSP capability thresholds ensures governance evolves as AI capabilities advance. Board-level reporting on AI risk posture

01

AI Inventory & Risk Classification

Catalogue every AI system in your organisation — internal builds, third-party tools, embedded AI in SaaS products, and emerging use cases. Each system is classified against the EU AI Act's four risk levels and assessed against Anthropic's AI Safety Levels (ASL) framework as a capability overlay. This dual classification identifies both regulatory obligations and technical safety requirements

Process steps

  • Catalogue all AI systems: internal, third-party, embedded, and planned
  • Classify each against EU AI Act risk levels: Prohibited, High-risk, Limited, Minimal
  • Apply Anthropic's ASL framework (ASL-1 through ASL-4) as capability assessment overlay
  • Identify which systems fall under Annex III high-risk categories (biometrics, employment, critical infrastructure, etc.)

Outputs

  • Complete AI system inventory
  • EU AI Act risk classification (per system)
  • Anthropic ASL capability assessment
  • Annex III high-risk identification
02

Triage & Impact Assessment

For high-risk use cases, conduct Fundamental Rights Impact Assessments per EU AI Act Article 27. For prohibited use cases, develop immediate cessation plans. Apply Anthropic's Constitutional AI safety hierarchy — safety and oversight first, then ethics, compliance, and helpfulness — as the decision framework for prioritisation. Document affected populations, deployment timelines, and human oversight requirements

Process steps

  • Conduct Fundamental Rights Impact Assessment for each high-risk system (Article 27)
  • Identify affected natural persons, specific risks of harm, and mitigation measures
  • For prohibited use cases: design immediate cessation and transition plans
  • Apply Constitutional AI hierarchy: safety → ethics → compliance → helpfulness

Outputs

  • Fundamental Rights Impact Assessments
  • Prohibited use case cessation plans
  • Constitutional AI safety hierarchy mapping
  • Human oversight requirement specifications
03

Risk Mitigation & Governance Design

Establish the cross-functional governance structure: AI Ethics Committee with CTO, CRO, Legal, and Business representation. Implement the appropriate conformity assessment pathway — internal self-certification (Annex VI) or third-party assessment (Annex VII, mandatory for biometric identification). Design quality management systems per Article 17, including monitoring dashboards, approval workflows, and incident escalation protocols

Process steps

  • Establish cross-functional AI Ethics Committee: CTO, CRO, Legal Counsel, Business leaders
  • Select conformity assessment pathway: Annex VI (self-certification) or Annex VII (third-party)
  • Design quality management system per Article 17: policies, processes, documentation controls
  • Build monitoring dashboards, approval workflows, and incident escalation protocols

Outputs

  • AI Ethics Committee charter and composition
  • Conformity assessment pathway selection
  • Quality management system design
  • Monitoring and escalation framework
04

Operationalise & Sustain

Embed responsible AI into the operating model — not as an overlay, but as a structural property of how AI is developed, deployed, and monitored. Continuous monitoring covers model drift, bias detection, and performance degradation. Post-market surveillance per EU AI Act requirements. Annual re-assessment against Anthropic's RSP capability thresholds ensures governance evolves as AI capabilities advance. Board-level reporting on AI risk posture

Process steps

  • Embed responsible AI reviews into existing development and deployment workflows
  • Deploy continuous monitoring: model drift, bias detection, performance degradation
  • Implement post-market surveillance per EU AI Act requirements
  • Conduct annual re-assessment against Anthropic RSP capability thresholds

Outputs

  • Embedded responsible AI operating model
  • Continuous monitoring framework
  • Post-market surveillance procedures
  • Board-level AI risk reporting

EU AI Act

Risk classification framework

The EU AI Act establishes four risk levels with graduated regulatory requirements. S.AI.L classifies every AI system in your organisation against this framework.

Prohibited

AI practices that are entirely banned under the EU AI Act

Examples

  • Social scoring systems evaluating social behaviour
  • Cognitive behavioural manipulation exploiting vulnerabilities
  • Biometric categorisation inferring sensitive characteristics (sexual orientation, political beliefs)
  • Real-time remote biometric identification in public spaces (with limited exceptions)

Immediate cessation. If your organisation operates any of these systems, S.AI.L designs transition and shutdown plans

High-Risk

AI systems subject to strict mandatory requirements — conformity assessment required before deployment

Examples

  • Biometrics and individual identification
  • Critical infrastructure (digital, road traffic, utilities)
  • Employment: recruitment, promotion, termination, task allocation, performance monitoring
  • Education: student assessment and admission decisions
  • Essential services, law enforcement, migration, and justice

Conformity assessment required (Annex VI or VII). Compliance deadline: August 2, 2026. S.AI.L implements the full governance framework

Limited Risk

AI systems subject to transparency obligations — users must be aware they are interacting with AI

Examples

  • Chatbots and conversational AI systems
  • Deepfake generation and synthetic media
  • Emotion recognition systems (when not prohibited)

Transparency requirements: users must be informed they are interacting with AI. S.AI.L implements disclosure mechanisms

Minimal Risk

AI systems largely unregulated — the majority of current AI applications

Examples

  • AI-powered spam filters
  • Video game AI
  • Recommendation engines (non-manipulative)

No specific regulatory obligations, but voluntary governance is recommended. S.AI.L's governance framework covers all risk levels

Safety framework

Built on Anthropic's safety standards

S.AI.L's governance methodology incorporates Anthropic's Responsible Scaling Policy and Constitutional AI principles as the foundation for responsible AI governance

Responsible Scaling Policy (RSP v2.2)

Anthropic's framework links AI capability assessments to proportional safety requirements. The RSP defines AI Safety Levels (ASL-1 through ASL-4) with escalating safeguards as capabilities increase. S.AI.L applies this framework as a capability assessment overlay alongside EU AI Act risk classification

  • ASL-1: No meaningful catastrophic risk — minimal safety interventions
  • ASL-2: Early signs of dangerous capabilities — enhanced safeguards activated
  • ASL-3: Substantial safety measures — >100 security controls, red-teaming, jailbreak detection
  • ASL-4: Maximum precautions — capability thresholds still under development
  • Proportional Protection: safeguards scale with potential risks using graduated requirements

Claude's Constitution & Constitutional AI

Anthropic's Constitutional AI methodology trains AI systems to reason about ethical principles rather than follow rigid rules. The constitution establishes a clear priority hierarchy that S.AI.L applies as the governance decision framework for your Office of Responsible AI

  • Priority 1 — Safety & Oversight: being safe and supporting human oversight of AI systems
  • Priority 2 — Ethics: behaving honestly and avoiding harmful actions
  • Priority 3 — Compliance: following regulatory and organisational guidelines
  • Priority 4 — Helpfulness: being genuinely useful to users and organisations
  • Hardcoded behaviours: absolute prohibitions (CBRN assistance, harmful content generation)
  • Soft-coded defaults: operator and user-adjustable settings within defined boundaries

Who this is for

Built for the leaders who own the outcome

Chief Executive Officer

Board-level assurance that AI governance meets regulatory requirements, with clear accountability structures and risk reporting

Board of Directors

Oversight framework for AI risk management, with dashboards showing compliance posture and emerging risks across the AI portfolio

Chief Risk Officer

Structured risk classification, continuous monitoring, and conformity assessment processes that integrate with existing enterprise risk management

General Counsel

EU AI Act compliance architecture, Fundamental Rights Impact Assessments, and defensible governance documentation for regulatory inquiries

Ready to build your Office of Responsible AI?

Speak to a Principal Consultant about establishing AI governance that meets EU AI Act requirements, applies Anthropic's safety standards, and scales with your AI ambition

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