| name | eu-ai-act-roles-oliver-schmidt-prietz |
| description | Determines the organization's role (provider, deployer, importer, distributor, or quasi-provider) and assesses Art. 25 quasi-provider risk of the EU AI Act. This skill should be used when the user asks to "determine AI Act roles", "check if we are provider or deployer", "assess quasi-provider status", "check Art. 25 substantial modification", "check value chain responsibilities", or mentions "Betreiber", "Anbieter", "wesentliche Veränderung", or finetuning implications under the AI Act.
|
| metadata | {"author":"Oliver Schmidt-Prietz","license":"AGPL-3.0","version":"2026.03.16"} |
EU AI Act Role Determination
Determine the organization's role under the AI Act (Regulation (EU) 2024/1689) — provider (Anbieter), deployer (Betreiber), importer, distributor, or quasi-provider — and assess Art. 25 quasi-provider risk.
LEGAL DISCLAIMER
IMPORTANT NOTICE
This assessment provides structured guidance based on the EU AI Act (Regulation (EU) 2024/1689) and Commission value chain guidance. It does not constitute legal advice. Final role determinations should involve qualified legal counsel with AI Act expertise.
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When to Search the Web
On activation — search for:
EU AI Act Commission guidance provider deployer roles value chain [current year]
EU AI Act Art. 25 substantial modification guidance latest
For finetuning assessment — search for:
EU AI Act finetuning substantial modification technical standards [current year]
EU AI Act open source model modification provider status
For value chain obligations — search for:
EU AI Act provider deployer responsibility allocation guidance [current year]
EU AI Act Art. 25(2) original provider support duty interpretation
Workflow: Ask Questions ONE AT A TIME
Phase 1: Context Gathering (Adaptive Intake)
Prior Assessment Context (optional):
"If you have previously run another EU AI Act skill, you may paste the Assessment Context block here. This pre-fills several fields and avoids redundant input."
If context is provided, pre-populate applicable fields and skip to confirmation. If any field conflicts with user answers, flag the inconsistency.
Batch 1 — Open-ended question (single prompt):
"Let's determine your organization's role under the EU AI Act."
You can answer in your own words — a short paragraph or bullet points. I'll ask follow-up questions only if needed.
Describe your organization's relationship to this AI system: how you obtained it, what you do with it, whether you've modified it, and how it reaches users.
Coverage Analysis (internal — do not show this table to the user):
After the user responds, silently extract these 4 fields from their natural-language answer:
| # | Field | Normalized values |
|---|
| 1 | System acquisition | Self-developed · Commissioned · Purchased/licensed · Open-source · Third-party component |
| 2 | Organizational relationship | Developing for others · Deploying under own authority · Distributing · Importing · Integrating · Multiple |
| 3 | Market status | Already on EU market · First placement · First deployment · Already deployed |
| 4 | Modifications | None · Configuration · Finetuning/retraining · Changed purpose · Own brand · Substantial modification |
Apply generous extraction — e.g., "bought from US vendor" covers System acquisition (Purchased/licensed) + Market status (First placement) + potential Importer dimension. "We finetuned it and sell it under our brand" covers Modifications (Finetuning/retraining + Own brand) + Organizational relationship (Developing for others / Distributing).
Batch 2 — Adaptive follow-up (only if needed):
- If all 4 fields are clearly covered → skip Batch 2 entirely. Confirm extractions: "Based on your description, I've identified: [field summary]. Does this look correct?"
- If 1-2 fields are partially covered → confirm partial extractions: "You mentioned [X] — is this specifically [normalized value]?"
- If 2+ fields are missing → ask about gaps only: "A couple of details I still need: [specific missing fields]"
- Maximum 2 interaction turns for intake.
Information Normalization (internal):
Before proceeding to Phase 2, normalize all extracted information into the 4 structured fields above. If a field remains unclear after Batch 2, mark it as [UNCLEAR — proceeding with cautious assumptions] and note which assumption was made.
Phase 2: Primary Role Determination
Read references/role-definitions.md for full legal definitions.
Apply the decision tree through Art. 3(3)-(7):
ROLE DETERMINATION DECISION TREE
System acquisition + Organizational relationship → Role mapping:
Develops or commissions development + places on market/puts into service
under own name/trademark?
└─ YES → PROVIDER (Anbieter) — Art. 3(3)
Uses AI system under own authority in professional capacity?
└─ YES → DEPLOYER (Betreiber) — Art. 3(4)
Imports AI system from third country to place on EU market?
└─ YES → IMPORTER (Einführer) — Art. 3(6)
Makes AI system available on EU market (not as provider/importer)?
└─ YES → DISTRIBUTOR (Händler) — Art. 3(7)
Integrates AI system into product as manufacturer?
└─ YES → Product manufacturer — Art. 25(3), treated as PROVIDER
Multiple roles: An organization can hold multiple roles simultaneously (e.g., provider of one system and deployer of another). Assess each system separately.
Output after primary role determination:
"Based on your answers, your primary role appears to be [Role] under Art. 3([X]) AI Act.
[Brief reasoning based on answers]"
Role Determination Visual Decision Tree
┌──────────────────────────────┐
│ Did your org DEVELOP or │
│ COMMISSION the AI system? │
└──────────────┬───────────────┘
│
┌── YES ─────────┼─────────── NO ──┐
│ │
▼ ▼
┌──────────────────┐ ┌──────────────────────┐
│ Place on market / │ │ How does your org │
│ put into service │ │ interact with the │
│ under OWN name? │ │ system? │
└────────┬─────────┘ └──────────┬───────────┘
│ │
YES ───┤ ┌──────────────┼──────────────┐
▼ │ │ │
┌────────────────┐ Uses under Imports from Makes available
│ PROVIDER │ own authority non-EU to EU on EU market
│ (Anbieter) │ │ │ │
│ Art. 3(3) │ ▼ ▼ ▼
└────────────────┘ ┌──────────┐ ┌──────────┐ ┌──────────┐
│ DEPLOYER │ │ IMPORTER │ │DISTRIBUTOR│
│(Betreiber)│ │(Einfuehrer)│ │(Haendler)│
│ Art. 3(4)│ │ Art. 3(6)│ │ Art. 3(7)│
└──────────┘ └──────────┘ └──────────┘
Note: Product manufacturers integrating AI → Art. 25(3) → PROVIDER
For sector-specific role determination nuances, see references/sector-guidance-crossref.md. For worked role determination examples, see references/case-studies.md.
Phase 3: Quasi-Provider Risk Assessment (Art. 25)
Only proceed with this phase if:
- The system is high-risk, AND
- The user is not already classified as the original provider
Read references/quasi-provider-scenarios.md and references/substantial-modification.md.
"I will now assess whether your organization could be treated as a new provider under Art. 25 ('quasi-provider'). This applies when certain modifications or actions cause a deployer, distributor, or importer to assume provider obligations."
Scenario 1 — Own Name/Brand — Art. 25(1)(a):
"Have you put your own name, trademark, or brand on the AI system, or do you present it to end users under your own branding?"
If YES → quasi-provider under Art. 25(1)(a). Organization assumes full provider obligations.
Scenario 2 — Substantial Modification — Art. 25(1)(b):
"Have you made a substantial modification (wesentliche Veränderung) to the AI system?"
Read references/substantial-modification.md for the 3-step checklist.
Apply the 3-step determination:
Step 1: Identify the change
"What specific changes were made to the AI system? (technical parameters, data, architecture, deployment context)"
Step 2: Assess foreseeability
"Were these changes foreseen or covered in the original provider's conformity assessment or intended purpose documentation?"
Step 3: Evaluate risk impact
"Did the changes affect compliance with requirements in Chapter III, Section 2 (Art. 8-15), or did they alter the system's risk profile?"
If finetuning is involved → apply graduated assessment from references/finetuning-assessment.md:
| Finetuning Level | Risk of Substantial Modification |
|---|
| PEFT/Adapter (LoRA, QLoRA) | Low — typically does not constitute substantial modification |
| Layer-wise finetuning | Medium — may constitute substantial modification depending on scope |
| Full model retraining | High — likely constitutes substantial modification |
Scenario 3 — Changed Intended Purpose — Art. 25(1)(c):
"Have you changed the intended purpose (Zweckbestimmung) of the AI system from what the original provider specified?"
If YES → quasi-provider under Art. 25(1)(c). A change of intended purpose always triggers provider status for the entity that changed the purpose.
Scenarios 4-5 — Product Manufacturer Integration — Art. 25(3)(a-b):
"Are you a product manufacturer who:"
- "(a) places on the market or puts into service a high-risk AI system together with your product under your own name or trademark?"
- "(b) puts into service a high-risk AI system bearing your name or trademark after it has already been placed on the market?"
If YES to either → provider obligations apply to the product manufacturer.
Art. 25(4) Exception:
"Were the changes you made already foreseen and covered in the original provider's conformity assessment?"
If YES → Art. 25(4) applies — the original conformity assessment remains valid, and Art. 25(1)(b) does not trigger quasi-provider status.
Quasi-Provider Trigger Assessment Decision Tree
┌──────────────────────────────────┐
│ Is the system HIGH-RISK and │
│ obtained from another provider? │
└───────────────┬──────────────────┘
│
NO ────────────┼──────────── YES
│ │
▼ ▼
┌─────────────────┐ ┌──────────────────────────┐
│ Art. 25 does │ │ Check 3 triggers: │
│ not apply. │ └──────────┬───────────────┘
│ Stay in primary │ │
│ role. │ ┌─────────────┼─────────────┐
└─────────────────┘ │ │ │
▼ ▼ ▼
┌────────────┐ ┌────────────┐ ┌────────────┐
│ Own name/ │ │ Substantial│ │ Changed │
│ brand? │ │ modifica- │ │ intended │
│ Art.25(1a) │ │ tion? │ │ purpose? │
└─────┬──────┘ │ Art.25(1b) │ │ Art.25(1c) │
│ └─────┬──────┘ └─────┬──────┘
YES ─┤ YES ─┤ YES ─┤
│ │ │
│ ┌────▼─────┐ │
│ │Art. 25(4)│ │
│ │Foreseen? │ │
│ └────┬─────┘ │
│ YES ─┤── NO │
│ │ │ │
│ No quasi- │ │ │
│ provider │ │ │
│ │ │ │
▼ │ ▼ ▼
┌─────────────────────────────────────┐
│ QUASI-PROVIDER │
│ Full Art. 16 provider obligations │
│ New conformity assessment required │
└─────────────────────────────────────┘
Phase 4: Role Determination Dashboard
## AI Act Role Determination
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Organization: [name]
AI System: [name]
Date: [date]
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Primary Role: [Provider / Deployer / Importer / Distributor]
Legal Basis: [Art. 3(x)]
Quasi-Provider Risk: [None / Low / Medium / High]
Art. 25 Scenario: [N/A / Scenario 1-5 with detail]
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ANALYSIS SUMMARY:
[2-3 sentence summary of role determination reasoning]
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FLAGS:
[e.g., "Finetuning detected — layer-wise modification may trigger Art. 25(1)(b)"]
[e.g., "Purpose change from manufacturer's intended use detected"]
[e.g., "Own branding on third-party system — Art. 25(1)(a) quasi-provider"]
[e.g., "Product manufacturer integration — Art. 25(3) applies"]
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RESPONSIBILITIES:
Original provider support obligation: [Art. 25(2) — must provide technical docs and cooperation]
New conformity assessment required: [Yes / No / Potentially]
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ASSESSMENT CONTEXT (paste into next skill)
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System: [name]
Classification: [from prior assessment or TBD]
Basis: [from prior assessment or TBD]
Role: [role]
Quasi-Provider: [risk level]
Sector: [sector]
Jurisdiction: [list]
Org Size: [size]
Art. 50: [from prior assessment or TBD]
GPAI: [from prior assessment or TBD]
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NEXT STEPS:
→ Run /ai-act-obligations for applicable requirements based on this role
→ Run /ai-act-report to generate formal assessment documentation
→ If quasi-provider risk is Medium/High: seek legal counsel for detailed Art. 25 analysis
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Critical Reminders
- An organization can be both provider and deployer — for different systems or even the same system in different contexts
- Art. 25 quasi-provider is a trap — many organizations unknowingly become providers through finetuning or rebranding
- Art. 25(2) mutual support obligation — even when quasi-provider status triggers, the original provider must cooperate and provide technical documentation
- Intended purpose is the key anchor — any change from the provider's documented intended purpose triggers Art. 25(1)(c)
- Configuration ≠ modification — using a system within the provider's intended configuration range does not constitute substantial modification
- Open-source models — downloading and deploying an open-source model under own brand likely triggers Art. 25(1)(a)
- Search for latest guidance — the Commission is expected to publish detailed Art. 25 guidance
- Jurisdiction-specific employment law — role determination has national employment law implications. Reference references/employment-law-overlay.md Section 3 for per-country works council requirements (DE: BetrVG, AT: ArbVG, FR: Code du Travail, NL: WOR, IT: Statuto dei Lavoratori, ES: Ley Rider) that apply in addition to AI Act role obligations
- Compliance timeline — reference references/compliance-deadlines.md for applicable deadlines based on role and risk tier
