AI Act Readiness

EU AI Act Readiness

Operational playbook for EU AI Act compliance readiness — focused on the sprint to demonstrate readiness for the Aug 2026 high-risk AI deadline and ongoing conformity assessments.

When to use this skill vs. eu-ai-act-specialist:

• This skill: assessment imminent; need readiness sprint
• eu-ai-act-specialist: building AI Act compliance program; classifying systems; designing conformity processes

When to use this skill

Key AI Act timelines

The readiness sprint

8-week sprint (high-risk system, conformity assessment prep)

Week 1-2: System classification confirmation; gap analysis
Week 3-5: Documentation buildout (technical file, risk management, data governance)
Week 6-7: Conformity assessment internal dry-run
Week 8: External notified-body engagement / assessment

4-week sprint (GPAI obligations)

Week 1: System classification (provider/deployer/importer/etc.)
Week 2: Documentation prep (model card, training data summary, copyright compliance)
Week 3: Risk assessment + transparency obligations
Week 4: Submission / publication of required information

Critical AI Act areas

Risk classification

Per Article 6 / Annex III, AI systems classify into risk categories:

High-risk system requirements (Articles 9-15, plus 16-22)

GPAI provider obligations (Article 53+)

GPAI with systemic risk (Article 55, models > 10^25 FLOPs training compute)

Additional requirements:

• Model evaluations
• Adversarial testing
• Systemic risk assessment + mitigation
• Serious incident reporting
• Cybersecurity protection

Clarify First

Before running the readiness assessment, confirm these inputs. If any is unknown or vague, ASK — do not assume:

• AI system risk class — high-risk (Annex III), GPAI, or limited-risk (determines whether to run the 8-week high-risk sprint or the 4-week GPAI sprint, and which checklist applies)
• Trigger event — Aug 2026 high-risk deadline, scheduled notified-body conformity assessment, GPAI obligations, or annual review (sets sprint length and scope)
• Your role — provider, deployer, or importer (determines which obligation set is assessed)

Stop rule: ask only the 2-3 that most change the output. If the user says "just draft it," proceed and list your assumptions at the top of the assessment.

Quick start

1. Run readiness score: python3 scripts/ai_act_readiness_score.py --config ai-system.yaml
2. Check GPAI obligations (if applicable): python3 scripts/gpai_obligation_checker.py --model model.yaml
3. Pick sprint length based on score + system risk class
4. Execute sprint per references/ai-act-readiness-checklist.md

Common AI Act readiness failures

• Misclassification: deploying system as "limited-risk" when it's actually "high-risk" (Annex III)
• Risk management as one-time: AI Act requires continuous risk management
• Data governance gaps: training data without representativeness analysis
• Logging missing: post-market monitoring requires logs you don't have
• Human oversight theater: oversight that can't actually intervene
• GPAI training data summary missing: required since Aug 2025
• No conformity assessment plan: assuming notified body assessment is automatic
• AI literacy training skipped: required for staff working with AI systems

Tooling

References

• ai-act-readiness-checklist.md — full punch list per requirement
• high-risk-system-readiness-playbook.md — high-risk-specific deep prep

Related skills

• ra-qm-team/eu-ai-act-specialist — deep AI Act program management
• ra-qm-team/iso42001-ai-management — ISO 42001 AIMS (companion AI governance)
• ra-qm-team/audit-prep/aims-audit — AIMS audit-prep variant
• ra-qm-team/audit-prep/gdpr-audit-prep — GDPR overlay for AI processing personal data
• ra-qm-team/audit-prep/compliance-readiness — multi-framework readiness