Quintant Risk Map
The EU AI Act doesn't ask how you built your AI. It asks how you deploy it.
The only AI risk framework built exclusively for deployers — organisations buying and using AI they didn't build, and now must govern.
The problem
Existing frameworks are built for AI builders — not for deployers.
Most AI risk frameworks start with model training, training data, and system architecture. Most organisations never build a model. They deploy tools built by others. They own risk they didn't create.
EU AI Act Article 26 places 13 obligations on the deployer. No existing framework maps risk specifically to that position.
What deployer-first means
Starts with Article 26, not model training
Every risk maps directly to a deployer obligation — not to a lifecycle phase you don't manage.
Covers vendor dependency risk
Model drift, service withdrawal, provider compliance failure — these are your operational risk, not your vendor's problem.
Calibrated to operational maturity
Different priorities for an organisation with 2 AI tools versus one with 20. The risk map adjusts to where you actually are.
KNF and CEE context
Calibrated against supervisory expectations in Poland and Central Europe — not just generic EU guidance.
Architecture
48 risks. 6 control zones.
Organised by what you can actually control as a deployer — not by AI lifecycle phases you don't manage.
Use Case Classification
Did you correctly classify this AI under the EU AI Act? Are you aware of your obligations?
High-risk misclassification
Shadow AI classification gap
Vendor Dependency
What happens when the AI vendor changes something you rely on?
Model drift without notice
Provider AI Act compliance failure
Data & Integration
What data are you feeding into AI you don't control?
Personal data leakage via prompts
GDPR Article 22 violation
Human-AI Interface
How do your people interact with AI output?
Automation bias
Workflow theatre
Regulatory Compliance
Which Article 26 obligations are you not meeting?
No AI system inventory
AI literacy obligation not evidenced
Operational Continuity
What breaks if the AI fails, hallucinates, or is withdrawn?
Process dependency without fallback
Audit trail absence
Your risk profile
Not every risk applies to every organisation equally.
The Quintant Risk Map is calibrated across two dimensions: AI operational maturity (T1–T3) and regulatory intensity (low/mid/high). A 9-cell priority matrix surfaces the 7 risks that matter most for your specific profile.
First AI deployments — 1–3 tools, no governance structure
Informal governance — 4–10 tools, informal AI lead
Formal risk function — active high-risk AI, dedicated governance
Typical risks by maturity tier
First deployments, no governance
· High-risk AI misclassification
· Shadow AI outside any classification
· Personal data leakage via prompts
· No AI system inventory
Informal governance, 4–10 tools
· Model drift without vendor notification
· Automation bias in operational decisions
· GDPR Article 22 exposure (automated decisions)
· AI literacy obligation not evidenced
Formal risk function, active high-risk AI
· Provider AI Act compliance failure
· Process dependency without fallback
· Missing audit trail for AI-assisted decisions
· Workflow theatre — oversight that isn't real
Embedded in
Quintant Risk Map powers two engagements.
Engagement
AI Risk Model
Your organisation's risks — mapped, ranked, and explained. Quintant Risk Map provides the taxonomy; AI Risk Model delivers your specific profile.
Engagement
Readiness Sprint
Article 26 readiness in four weeks. Quintant Risk Map is the risk classification backbone used throughout the Sprint.