<!-- source: openspec/changes/publish-legal-bundle/research/02-ai-governance-counsel.md -->

# Terms of Service — AI Governance & EU AI Act Counsel Memo

**Client:** Rapoport Studio SRL (Moldova)
**Surface:** `rapoport.studio/terms` (EN controlling; RU and RO mirrors)
**Author:** AI Governance & EU AI Act Counsel (research role)
**Date:** 2026-05-13
**Status:** Research and draft. All draft clauses are tagged `[DRAFT — requires AI-regulation counsel review]`. Not legal advice.

---

## 1. Executive summary

1. **The studio's AI Act role is principally *deployer*, with a narrow latent *provider* exposure.** Forge, Maestro, and Muse are operated by the studio's internal team to produce client deliverables. Clients never receive direct API access, never run the agents themselves, and the agents are not placed on the EU market under the studio's name as standalone AI systems. That is the textbook deployer fact pattern. The latent provider risk lives in the moment the studio (a) lets a client press a button that runs Forge/Muse autonomously on their material, or (b) markets the agents as a product. The ToS must lock the current "mediated service" posture so the studio does not silently slip into provider obligations.
2. **The single biggest AI-specific contractual exposure is *hallucinated code shipped to a client that the studio's human team did not catch*.** The disclaimer must do three things at once: (a) describe how outputs are generated, (b) describe what the studio reviews and what it does not, (c) explicitly allocate residual-error risk to the client once a defined acceptance window expires. A blanket "AI can be wrong, not our problem" clause is unenforceable post-*Moffat v. Air Canada* — the studio is the more knowledgeable party, courts will not let it disclaim the entire accuracy duty.
3. **Sub-processor disclosure must name Anthropic and OpenAI by name and link to their *current* commercial terms.** Anthropic's commercial terms (effective 2025-06-17) prohibit training on Customer Content; OpenAI's API default is also no training on business data. Both retain inputs for ~30 days for abuse monitoring by default. ZDR agreements are available from both and should be a roadmap item, not a ToS promise, until they are signed.
4. **Article 50 transparency obligations bite from 2026-08-02.** For the studio's current scope, the load-bearing carve-out is the *human review / editorial control* exemption for AI-generated text. Because Pavel and named specialists review every deliverable before it ships, the studio likely qualifies for the text-disclosure exemption. The ToS should record this human-review fact as a contractual commitment, not just a policy.
5. **Article 4 AI-literacy obligation is *already* in force (since 2025-02-02) for both providers and deployers.** This is operational, not contractual — but the ToS can usefully reference the studio's internal AI-usage policy (currently being drafted under `establish-studio-legal-baseline`) to demonstrate compliance posture.
6. **Forge/Maestro/Muse are minimal-risk, not high-risk, under Annex III.** Code generation as an internal tool is not in any Annex III category. The studio does not need Article 8–15 high-risk obligations. The 2026-08-02 enforcement of high-risk rules is largely orthogonal — but the ToS should still note risk classification to forestall client questions.
7. **Three operational gaps must close before the ToS goes live:** (a) signed ZDR or equivalent written confirmation from Anthropic (and OpenAI when used) covering client engagements; (b) a written internal AI-usage policy at v1.0, not v0.1; (c) a documented human-review protocol that maps to the ToS's "material outputs" carve-out.

---

## 2. AI clause inventory

The AI Governance counsel contributes the following clauses. Numbering aligns to the draft structure for cross-reference with the Commercial Lawyer and Privacy specialist.

| # | Clause | Purpose |
|---|---|---|
| AI-1 | **Definitions — AI Systems vs. AI-Generated Output vs. Studio AI Tools** | Disambiguate three distinct concepts so downstream clauses do not collide. |
| AI-2 | **Description of Studio AI Tools** | Name Forge, Maestro, Muse; describe each in one sentence; declare operating model (studio-internal use, no client API access). |
| AI-3 | **AI-Generated Output ownership and license** | Refine the Commercial Lawyer's IP clause for the AI-specific case: client owns AI-generated deliverables as part of the deliverable bundle; studio retains all rights in the AI Tools themselves. |
| AI-4 | **Sub-processor disclosure — AI model providers** | Name Anthropic and OpenAI; link to their commercial terms; declare zero-training and retention posture; commit to update the list on change. |
| AI-5 | **Hallucination, non-determinism, and accuracy disclaimer** | The headline disclaimer. Survives *Moffat*-style scrutiny by being specific about what the studio reviews and what residual risk the client accepts. |
| AI-6 | **Human review protocol** | The contractual commitment that backs the hallucination disclaimer. Describes review depth per deliverable type. |
| AI-7 | **Output verification responsibility split — acceptance window** | After the acceptance window, the client owns subsequent reliance on the deliverable. Before, the studio carries the warranty. |
| AI-8 | **Training-data carve-out** | Explicit ban on studio using client material to train models; pass-through of vendor zero-training commitments. |
| AI-9 | **EU AI Act compliance statement** | Studio's role (deployer); risk classification (minimal/limited); Article 50 transparency posture; Article 4 literacy posture. |
| AI-10 | **Article 50 transparency disclosures** | (a) Studio discloses to client that deliverables include AI-generated content; (b) client undertakes, when re-publishing deliverables to its own end-users in scope of Art. 50(4), to make any further disclosure required. |
| AI-11 | **Prohibited use of AI-generated deliverables by client** | No resale as a standalone AI product; no training a competing model on the deliverables; no laundering AI work as un-disclosed human work in regulated contexts (legal, medical, financial advice). |
| AI-12 | **AI tool action logging — studio audit obligation and client access** | Studio retains logs of Forge/Maestro/Muse actions on client material for N months; client may request copies. |
| AI-13 | **AI incident response — notification and remediation** | Defined in/out scope, notification SLA, remediation classes (revert, retest, replace). |
| AI-14 | **Reservation of provider-role escalation** | If the studio ever exposes Forge/Maestro/Muse as a direct-access product to the client, additional terms apply. Closes the "silent slip to provider" gap.

---

## 3. Key drafting recommendations (clause by clause)

### AI-1 — Definitions

Three distinct concepts, three distinct labels. Confusing them is the most common error in tech-services ToS. Recommended labels (English controlling):

- **"Studio AI Tools"** — Forge, Maestro, Muse, and any successor agents operated by the studio's internal team. The studio retains all IP, no client license is granted. Tools are not "placed on the market" within the meaning of the EU AI Act.
- **"AI-Generated Output"** — material (code, written drafts, plans, documentation) produced wholly or partly by Studio AI Tools and incorporated into the deliverables.
- **"Deliverables"** — the full output of an engagement, which may include AI-Generated Output, human-authored material, and third-party material. Ownership and license terms are governed by the IP clause (Commercial Lawyer).

The split matters because downstream Article 50 obligations, training carve-outs, and IP rules attach differently to each.

### AI-2 — Description of Studio AI Tools

A short, plain-English paragraph naming each tool, what it does at the highest level, and (this is the load-bearing bit) the operating model: *the studio's team operates these tools; the client does not directly invoke them*. The plain description is also a defensive move — it ages well, and reads as good-faith disclosure if a regulator looks.

### AI-3 — AI-Generated Output ownership (AI-specific edges)

Refine, don't duplicate, the Commercial Lawyer's IP clause. AI-specific edges to add:

- **Output uniqueness disclaimer.** Per peer practice (Vercel v0): AI-Generated Output may not be unique; identical or substantially similar output may be produced for other customers from independent prompts. The studio is not in breach if a third party receives similar AI output.
- **Vendor pass-through.** The studio's right to assign AI-Generated Output to the client is conditional on the model provider's terms. Anthropic's commercial terms (Section B) assign Anthropic's "right, title and interest (if any)" in Outputs to the customer; OpenAI's API terms do the same. The studio passes through that assignment to its client.
- **Third-party material in output.** AI-Generated Output may resemble third-party copyrighted code or text in the training data. The studio commits to *reasonable* review but cannot warrant absolute non-infringement. Allocate the residual third-party-claim risk via the indemnity clause (Commercial Lawyer).

### AI-4 — Sub-processor disclosure (model providers)

Named, dated, and linked. Recommended structure:

| Provider | Used for | Commercial-terms link | Training on customer content? | Default retention |
|---|---|---|---|---|
| Anthropic | Primary model layer (Claude API) for all three tools | anthropic.com/legal/commercial-terms | No (Section B, effective 2025-06-17) | ~30 days for abuse monitoring (separate DPA) |
| OpenAI | Occasional secondary model layer | openai.com/policies/business-terms | No by default (API) | 30 days default for abuse monitoring |

Coordinate with the Privacy specialist — they own the broader sub-processor list. This table is the *AI-specific* subset. Commit in the ToS to publish updates (e.g., add a model provider) with N days' notice; that satisfies the Privacy specialist's standard sub-processor-update clause and discharges the AI-side transparency duty cleanly.

### AI-5 — Hallucination disclaimer

The disclaimer must be granular to survive *Moffat*-style scrutiny. Specifically:

1. Acknowledge that LLM outputs are non-deterministic and may include fabricated facts, syntactically valid but semantically wrong code, or hallucinated citations.
2. Describe what the studio *does* — human review of material outputs before delivery (cross-reference AI-6).
3. Describe what the studio *does not* — line-by-line audit of every token, formal proof of correctness, guarantee against subtle defects.
4. Allocate residual risk to the client *only after the acceptance window* (cross-reference AI-7) and *only for issues consistent with the level of review committed*.

Peer practice is uniformly weaker than this. Vercel v0 and Cursor both rely on broad "as is" disclaimers paired with sole-risk language. Those clauses are at risk under *Moffat* and the developing Australia/UK/Canada case law. The studio's stronger move is to be specific about what it reviewed; that specificity is also the studio's actual differentiator (curated team, human-anchored).

### AI-6 — Human review protocol

The contractual hook for AI-5. Defines:

- **Material outputs.** Code merged into the client's main branch, written deliverables shipped under the studio's name, plans presented as final. Defined positively.
- **Non-material outputs.** Throwaway drafts, exploration sketches, internal-discussion artifacts. These are excluded from the human-review commitment but also excluded from the studio's warranty.
- **Review depth.** Code: human reviewer reads the diff, runs the tests, exercises the changed surface. Written deliverable: human reviewer reads end-to-end, edits for accuracy. Plans: human reviewer validates against scope.
- **Review actor.** Pavel personally for high-stakes deliverables; named specialists for lower-stakes deliverables. The client may request the review actor on file.

The clause is the studio's exemption ticket under Article 50(4) for AI-generated text: "human review or editorial control" with "editorial responsibility" attached. By contractualizing it, the studio creates the evidence trail a regulator (or a downstream claimant) would look for.

### AI-7 — Verification responsibility split

After the deliverable is accepted (or after a defined acceptance window expires without rejection), subsequent issues fall outside the AI-specific warranty. This is operationally crucial for Forge-generated code: a subtle bug that surfaces six months later in production cannot pull the studio back into unbounded liability. Couple with the Commercial Lawyer's general warranty clause.

Acceptance window suggestion: 14 days for code, 30 days for written deliverables. Tunable per engagement.

### AI-8 — Training-data carve-out

Two-direction commitment:

1. **Studio side.** Studio does not use client material to train, fine-tune, or evaluate any model.
2. **Vendor pass-through.** Studio uses model providers that, by commercial-terms default, do not train on customer content (Anthropic, OpenAI). Studio commits to maintain this property as a procurement criterion — adding a new model provider that does train on customer content requires client notice and consent.

The pass-through is verifiable: Anthropic's Section B (Customer Content) explicitly prohibits training; OpenAI's API default is the same. If the studio later moves to a ZDR contract with either, that becomes an upgrade, not a fix.

### AI-9 — EU AI Act compliance statement

A short, factual section that states the studio's role and posture. Operative content:

- **Role:** Deployer of AI systems operated for the studio's own service delivery. Not a provider — Studio AI Tools are not placed on the EU market under the studio's name as standalone AI systems.
- **Risk classification:** The Studio AI Tools are minimal/limited risk AI systems within the meaning of the AI Act; none falls within an Annex III high-risk category (no biometric, employment, education, critical-infrastructure, law-enforcement, justice, or migration use).
- **Article 4 AI literacy:** In force since 2 February 2025. Studio commits to maintain an internal AI usage policy and training for personnel operating the Studio AI Tools.
- **Article 50:** Applies from 2 August 2026. See AI-10.
- **Re-classification trigger:** If the studio's posture changes (e.g., Forge is offered as a direct-access client product, or a use case lands in Annex III), the studio will notify the client and update this section.

### AI-10 — Article 50 transparency disclosures

The clause has two halves because the studio's deliverable is a *content product* that may be re-published by the client.

**First half — studio-to-client disclosure.** The very existence of this ToS clause discharges it: the client is on notice that deliverables include AI-Generated Output. No further per-deliverable disclosure is needed inside the studio-client relationship.

**Second half — client-to-end-user disclosure.** If the client re-publishes deliverables to its own end-users *and* the deliverable is text on a matter of public interest *and* the human-review-and-editorial-responsibility exemption does not apply (e.g., the client's redistribution strips the editorial review), then Article 50(4) places the disclosure obligation on the *deployer who publishes*. That is the client, not the studio. The ToS records this allocation cleanly.

The client also assumes the deepfake/synthetic-content disclosure obligations under Article 50(4) for any image/audio/video the studio delivers that is artificially generated and falls within Article 50's scope.

### AI-11 — Prohibited uses by the client

Specifically:

- No resale of AI-Generated Output as a standalone AI product (e.g., spinning up a SaaS that pipes the studio's code as its sole feature).
- No use of AI-Generated Output to train, fine-tune, or evaluate a competing model.
- No use of AI-Generated Output in regulated contexts (legal advice, medical advice, financial advice provided to retail clients, life-safety automation) without disclosing the AI origin to the regulated-context's regulator or end-user, where law requires.

These are AI-specific edges on top of the Commercial Lawyer's general acceptable-use clause; do not duplicate, refine.

### AI-12 — Logging and client audit right

Studio commits to retain reasonable logs of Forge/Maestro/Muse actions on client material — at minimum: tool runs initiated, repositories touched, PRs opened, model provider invoked, approximate token cost. Retention period: 12 months default (tunable). Client may request a copy on reasonable notice; the studio supplies what it has.

The clause is a credibility move. Anthropic's commercial customers do not get model-provider-side logs that match this format, so the studio supplies its own log layer (which already exists — `forge-run`, `forge-step`, `forge-tool-call`, `forge-output` entities, plus the orchestra journal for Maestro).

### AI-13 — AI incident response

Defines:

- **Scope.** A "Forge-generated PR" or other Studio AI Tool action that causes client-environment harm (production breakage, data loss, regression).
- **Notification SLA.** As soon as practicable, and in any event within 48 hours of the studio becoming aware. Aligns with typical DPA security-incident SLAs the Privacy specialist will set.
- **Remediation classes.** Revert (default, if reversible); retest and re-deliver; replace (if the AI-Generated Output itself is the root cause and human-reviewable rework is needed).
- **Cost allocation.** Studio bears remediation cost when the incident traces to inadequate human review per AI-6; client bears cost when the incident traces to client-side environment changes or post-acceptance reliance.

### AI-14 — Reservation of provider-role escalation

The structural clause that prevents the studio from silently sliding into "provider" status. If the engagement adds direct-API access to Studio AI Tools, autonomous-execution against client systems without studio review, or branded resale of the agents, additional terms apply. The current ToS only covers the *mediated* operating model.

---

## 4. Draft clause text

> All drafts below are tagged `[DRAFT — requires AI-regulation counsel review]`. English controlling per the ToS language clause owned by the Commercial Lawyer.

### 4.1 AI-Generated Output ownership

> **[DRAFT — requires AI-regulation counsel review]**
>
> **AI-Generated Output.** Certain Deliverables are produced wholly or partly by the Studio AI Tools described in Section [X]. We refer to such material as "**AI-Generated Output**". To the extent that the Studio holds any rights in AI-Generated Output that is incorporated into the Deliverables, the Studio assigns those rights to the Client as part of the Deliverables, on the terms of Section [IP clause cross-reference], and subject to (a) the Client's compliance with these Terms and (b) the underlying model providers' terms of service.
>
> The Client acknowledges that, due to the nature of large language models, AI-Generated Output may not be unique. The same or substantially similar output may be produced for other customers from independent prompts. The Studio does not warrant uniqueness of AI-Generated Output and is not in breach of these Terms by reason of a third party receiving similar output.
>
> The Client further acknowledges that AI-Generated Output may, in limited cases, resemble third-party copyrighted material present in the training data of the underlying models. The Studio commits to reasonable human review (Section [AI-6 cross-reference]) to mitigate this risk, but does not warrant absolute non-infringement. Allocation of residual third-party-claim risk is governed by the indemnity clause (Section [Commercial Lawyer cross-reference]).
>
> The Studio retains all right, title, and interest in the Studio AI Tools themselves, including any prompts, system instructions, model configurations, orchestration logic, and operational artifacts used to operate them. No license to the Studio AI Tools is granted to the Client.

### 4.2 Hallucination, non-determinism, and accuracy disclaimer

> **[DRAFT — requires AI-regulation counsel review]**
>
> **Nature of AI-Generated Output.** The Studio AI Tools are powered by large language models, which generate output by probabilistic prediction rather than deterministic computation. The Client acknowledges that AI-Generated Output may:
>
> (a) be non-deterministic — the same input may produce different outputs on different runs;
> (b) include factual statements that appear authoritative but are inaccurate or fabricated ("hallucinations");
> (c) include code that compiles and superficially functions but contains subtle defects, security weaknesses, or edge-case failures;
> (d) include citations, identifiers, or references that do not correspond to any real source.
>
> **What the Studio reviews.** Before delivering AI-Generated Output as part of a Material Deliverable, a member of the Studio's human team reviews the output to the depth committed in Section [AI-6, Human Review Protocol]. Review depth is calibrated to deliverable type; the Studio does not guarantee a line-by-line audit of every token of AI-Generated Output or a formal proof of correctness.
>
> **What the Client accepts.** The Client accepts that, notwithstanding the Studio's review, AI-Generated Output may contain residual defects. The Studio's warranty for AI-Generated Output is the warranty stated in Section [warranty cross-reference]; outside that warranty, AI-Generated Output is provided on an "as reviewed" basis. After the acceptance window described in Section [AI-7], subsequent reliance on the Deliverable is at the Client's discretion and risk to the extent set out in that Section.
>
> This Section does not exclude or limit any liability that cannot be excluded or limited under applicable law, and is to be read together with the limitation-of-liability clause (Section [Commercial Lawyer cross-reference]).

### 4.3 Training-data carve-out

> **[DRAFT — requires AI-regulation counsel review]**
>
> **No training on Client Material.** The Studio will not use Client Material — including code, briefs, written content, data, credentials, or any other material the Client provides — to train, fine-tune, evaluate, or benchmark any artificial-intelligence model operated by the Studio or by any third party.
>
> **Model-provider zero-training commitments.** The Studio operates the Studio AI Tools through commercial accounts with the model providers disclosed in Section [Sub-processor disclosure]. As of the effective date of these Terms:
>
> (a) **Anthropic** (primary model provider) commits, under its Commercial Terms of Service (Section B, Customer Content; effective 2025-06-17), not to train models on customer content submitted via its commercial API.
> (b) **OpenAI** (occasional secondary model provider), under its standard API terms, does not train models on inputs or outputs submitted via the API by default.
>
> The Studio commits to maintain this zero-training property as a procurement criterion. Adding a model provider whose default terms permit training on customer content would require prior notice to the Client and the Client's consent.
>
> Each model provider may retain inputs and outputs for a short period for the purpose of detecting abuse and enforcing usage policies, as described in the respective provider's terms. The Studio is in the process of obtaining zero-data-retention coverage where available; until then, the model providers' default abuse-monitoring retention applies.

### 4.4 EU AI Act transparency disclosure

> **[DRAFT — requires AI-regulation counsel review]**
>
> **EU AI Act posture.** The Studio is established in Moldova and provides services to clients in Moldova, Romania, the European Union, and Israel. For services that fall within the territorial scope of Regulation (EU) 2024/1689 (the "EU AI Act"):
>
> (a) **Role.** The Studio acts as a *deployer* of AI systems within the meaning of Article 3(4) of the EU AI Act. The Studio operates the Studio AI Tools under its own authority and for the purposes of its own service delivery; the Studio AI Tools are not placed on the Union market under the Studio's name as standalone AI systems, and the Client does not receive direct operational access to them.
>
> (b) **Risk classification.** The Studio AI Tools are classified by the Studio as minimal- or limited-risk AI systems. None falls within an Annex III high-risk category.
>
> (c) **AI literacy (Article 4).** The Studio maintains an internal AI usage policy and trains personnel operating the Studio AI Tools, as required by Article 4 of the EU AI Act (in force since 2 February 2025).
>
> (d) **Transparency on AI-generated content (Article 50).** This Section serves as the Studio's disclosure to the Client that Deliverables may include AI-Generated Output, including AI-generated text. Where the Client publishes Deliverables to its own end-users, the Client is the deployer of the AI-generated content within that downstream relationship; the Client is responsible for any further disclosure required by Article 50 in respect of that downstream publication, except to the extent the Studio's human review and editorial control over the AI-Generated Output qualifies for the exemption under Article 50(4) and that exemption travels with the Deliverable.
>
> (e) **Reservation of role escalation.** If the Studio's operating model changes such that the Studio would qualify as a *provider* of an AI system under the EU AI Act in respect of the Client (for example, if the Studio offers direct-access use of the Studio AI Tools to the Client as a standalone product), additional terms will be agreed before such use begins.

### 4.5 AI incident response

> **[DRAFT — requires AI-regulation counsel review]**
>
> **AI Incident.** An "AI Incident" means a malfunction, error, or unintended consequence arising from the operation of a Studio AI Tool on Client Material that causes, or is reasonably likely to cause, harm to the Client's systems, data, or operations. Examples include: a Forge-generated pull request that, after merge, introduces a regression in the Client's production environment; a Maestro-routed action that affects the Client's project tracker incorrectly; or a Muse-generated written deliverable that contains a material factual error discovered post-delivery.
>
> **Notification.** Upon the Studio becoming aware of an AI Incident, the Studio will notify the Client without undue delay and in any event within forty-eight (48) hours, providing: a description of the Incident, the affected Client Material, the Studio AI Tool involved, and the Studio's initial assessment of remediation options.
>
> **Remediation.** The Studio will, at its expense for AI Incidents traceable to inadequate human review under Section [AI-6]:
>
> (a) revert the affected change where reversal is technically feasible;
> (b) re-perform the work to the human-review depth specified for the relevant deliverable type, and re-deliver;
> (c) where the AI-Generated Output itself is the root cause and human-reviewable rework is required, replace the affected portion of the Deliverable.
>
> The Studio's liability for AI Incidents is governed by, and capped by, the limitation-of-liability clause (Section [Commercial Lawyer cross-reference]). AI Incidents traceable to Client-side environment changes, post-acceptance reliance outside the acceptance window (Section [AI-7]), or use of the Deliverable outside its intended scope, are at the Client's cost.

---

## 5. EU AI Act exposure analysis

### 5.1 Role classification

The studio operates AI agents (Forge, Maestro, Muse) *internally* to produce client deliverables. Clients do not receive direct API access; they receive only the *outputs* (code, text, plans), mediated by a human team.

| Test under Article 3 | Studio's position |
|---|---|
| Does the studio "develop an AI system… and place it on the market"? (Provider, Art. 3(3)) | No. Forge/Maestro/Muse are internal infrastructure, not placed on the EU market under the studio's name as products. |
| Does the studio "put the AI system into service under its own name"? (Provider) | Borderline — but "putting into service" implies first availability to the end user. The end user of the AI system *is the studio itself*; the client is the end user of the *deliverable*, not the system. The studio does not put the AI system into service for the client's use. |
| Does the studio "use an AI system under its authority"? (Deployer, Art. 3(4)) | Yes. Squarely. |
| Could the studio become a provider under Article 25 (substantial modification of a third-party AI system)? | Not on current facts. Wrapping Anthropic's API with a system prompt and a tool loop is not a "substantial modification" of the underlying GPAI model in the Article 25 sense. The studio is a downstream user of Claude, not a re-issuer of a modified model. |

**Conclusion.** The studio is a **deployer** of AI systems. The latent provider risk lives in a future operating-model change (see AI-14).

### 5.2 Risk classification

Annex III categories: biometrics; critical infrastructure; education; employment, workers management, and access to self-employment; access to essential private and public services; law enforcement; migration, asylum, and border control management; administration of justice and democratic processes.

Forge, Maestro, Muse fall outside every category. They are general-purpose internal automation. Even when used to draft a deliverable destined for a client in a regulated sector, the AI system itself is not the regulated component — the client's downstream use is. Subject to the AI Act's general transparency rules (Article 50) and AI literacy obligation (Article 4); no high-risk regime obligations.

### 5.3 Obligations applicable to the studio (deployer, minimal/limited risk)

| Obligation | Source | Applies to studio? | Notes |
|---|---|---|---|
| AI literacy | Art. 4 | Yes, in force | Operational: internal policy + training. Cross-reference `_legal/policies/ai-usage-policy.md`. |
| Transparency: AI interaction disclosure | Art. 50(1) | Marginal | The Studio AI Tools do not interact directly with the client; only the studio's human team does. Disclosure handled via ToS AI-2 and AI-10. |
| Transparency: deepfake disclosure | Art. 50(4) | If deliverable includes generated image/audio/video | Reserved in AI-10. |
| Transparency: AI-generated text disclosure | Art. 50(4) | Yes, but human-review exemption likely applies | The studio's human-review protocol (AI-6) is the exemption vehicle. |
| Conformity assessment, registration, technical documentation | Art. 16+, Annex IV | No | These are provider/high-risk obligations. |
| Logging | Art. 12 (high-risk) | No legally; yes contractually | Operational AI-12 commitment is voluntary credibility, not regulatory. |
| Human oversight | Art. 14 (high-risk) | No legally; yes contractually | Same — AI-6 is the contractual hook. |

### 5.4 Gaps (operational, not contractual)

A contract cannot cure these; the studio needs to do them:

1. **AI literacy training and policy.** v0.1 draft exists under `establish-studio-legal-baseline`; needs to reach v1.0 before the ToS goes live so AI-9(c) is truthful.
2. **Documented human-review protocol.** Currently embedded in operational practice ("Pavel reviews"); needs to be written down at the level of "what review depth applies to each deliverable type" so AI-6 is verifiable.
3. **ZDR or equivalent written commitments.** Currently relying on Anthropic's default commercial terms. For client engagements with EU-based clients in mildly sensitive sectors (legal, HR-adjacent), a signed ZDR uplift is the prudent move.

---

## 6. Open questions for human counsel

1. **Acceptance window length.** Should the AI-specific acceptance window in AI-7 be aligned with the general acceptance clause owned by the Commercial Lawyer, or shorter? Proposal: 14 days for code, 30 days for written deliverables. Confirm or override.
2. **"Material Deliverable" definition.** Should this be a separate defined term used across the ToS, or local to the AI clauses? Recommend separate defined term to avoid drift with the Commercial Lawyer's general scope-of-services clause.
3. **Sub-processor change notice period.** What notice does the studio commit to give the client before adding a new model provider? 30 days is the typical DPA value (Privacy specialist territory). Confirm we align here.
4. **Article 50 client-side disclosure shifting.** AI-10 places the downstream disclosure burden on the client. Confirm this is enforceable in Moldova/Romania/Israel/EU jurisdictions; consider a softer "the parties acknowledge that the client is the deployer for downstream publication" rather than an outright shift.
5. **Indemnity for third-party IP claims arising from AI-Generated Output.** GitHub Copilot Business and Cursor both offer (or have offered) some form of IP indemnity for paid tiers. The studio could (a) decline indemnity entirely, (b) match GitHub's "commercially reasonable defense" posture, or (c) cap indemnity at fees paid for the affected deliverable. Recommend (c) for v1; revisit when engagement values rise. Commercial Lawyer owns the actual clause, but the AI-specific carve-out posture is a yes/no decision here.
6. **High-stakes deliverable carve-outs.** Should the ToS prohibit use of AI-Generated Output in specifically enumerated regulated contexts (legal advice for the client's own customers; medical-decision automation; etc.), or rely on the general prohibited-use clause? Recommend explicit enumeration to forestall *Mata v. Avianca*-style fabricated-citation incidents from the studio's chair.
7. **RU/RO translations of "AI-Generated Output" and "Studio AI Tools".** The translated versions must not drift in meaning. Recommend the controlling-English clause makes clear that the EN definitions govern in interpretive disputes.
8. **Mandatory vs. negotiable.** Which of the 14 clauses are non-negotiable studio policy (AI-4, AI-5, AI-6, AI-8, AI-9) and which can be tuned per engagement (AI-7 window length, AI-12 retention period, AI-13 SLA)? Recommend the non-negotiable set is locked at ToS level; the rest move to the Statement of Work template.

---

## 7. Sources

All URLs accessed 2026-05-13 unless otherwise noted.

- [Article 50 — EU Artificial Intelligence Act](https://artificialintelligenceact.eu/article/50/) — Authoritative consolidated text of the transparency obligations for providers and deployers; deepfake and AI-generated-text disclosure rules; human-editorial-control exemption. Effective 2 August 2026.
- [Article 4 — EU Artificial Intelligence Act](https://artificialintelligenceact.eu/article/4/) — AI literacy obligation for providers and deployers; in force since 2 February 2025.
- [Annex III — EU Artificial Intelligence Act](https://artificialintelligenceact.eu/annex/3/) — High-risk system categories; confirms none cover ordinary developer-tool use of LLMs.
- [Implementation Timeline — EU Artificial Intelligence Act](https://artificialintelligenceact.eu/implementation-timeline/) — Phased enforcement schedule (Feb 2025, Aug 2025, Aug 2026, Aug 2027); used to date the studio's compliance posture.
- [European Commission — Article 50 Implementation Guidelines](https://digital-strategy.ec.europa.eu/en/library/draft-guidelines-implementation-transparency-obligations-certain-ai-systems-under-article-50-ai-act) — Draft Commission guidelines on Article 50 transparency implementation.
- [Anthropic Commercial Terms of Service](https://www.anthropic.com/legal/commercial-terms) — Effective 2025-06-17. Section B prohibits training on Customer Content; assigns Anthropic's rights in Outputs to the customer. Core sub-processor citation for AI-4 and AI-8.
- [Anthropic Privacy Center — ZDR coverage](https://privacy.claude.com/en/articles/8956058-i-have-a-zero-data-retention-agreement-with-anthropic-what-products-does-it-apply-to) — Last updated 2026-03-16. Defines ZDR scope; user-safety classifier results retained even under ZDR.
- [OpenAI Enterprise Privacy](https://openai.com/enterprise-privacy/) — Business data ownership and no-training-by-default for API; 30-day default retention for abuse monitoring (cross-checked via summary because direct fetch was blocked).
- [Vercel AI Product Terms](https://vercel.com/legal/ai-product-terms) — Effective 2026-03-31. Peer-practice baseline for hallucination disclaimer, human-review clause, output ownership; weaker than recommended drafting under *Moffat*.
- [Cursor Terms of Service — analysis](https://terms.law/ai-output-rights/cursor/) — Sections 1.3 (no training), 1.4 and 14 (warranty disclaimer), 5.3 (output ownership), 1.7 (auto-execution sole-risk). Peer baseline for auto-execution caveats relevant to Forge.
- [GitHub Copilot Terms — additional products and features](https://docs.github.com/en/site-policy/github-terms/github-terms-for-additional-products-and-features) — Effective 2026-04-27. Routing layer for Business/Enterprise vs. Individual; informs the indemnity posture decision.
- [GitHub Copilot Product Specific Terms — March 2026 PDF](https://assets.ctfassets.net/8aevphvgewt8/1Y0gmEkMnAs8W6N4ai2R1g/694c0ae359902dc0700454333ad15c44/GitHub_Copilot_Product_Specific_Terms_-_2026_03_05_-_FINAL.pdf) — Current Copilot product-specific terms; reviewed for IP indemnity language and ownership of Suggestions.
- [Freshfields — EU AI Act unpacked #22 (Provider vs. Deployer)](https://technologyquotient.freshfields.com/post/102k1kz/eu-ai-act-unpacked-22-key-considerations-for-employers-as-deployers-vs-provide) — Practitioner analysis of the provider/deployer line; supports the studio's deployer classification.
- [A&O Shearman — Deployers and Providers interplay](https://www.aoshearman.com/en/insights/ao-shearman-on-tech/zooming-in-on-ai-4-what-is-the-interplay-between-deployers-and-providers-in-the-eu-ai-act) — Article 25 reclassification analysis; informs the "reservation of provider-role escalation" clause (AI-14).
- [Pitch Law — Provider vs Deployer under the AI Act](https://www.pitch.law/knowledge-base/provider-vs-deployer-ai-act) — Dual-role analysis informing the studio's borderline cases.
- [Augment Code — EU AI Act and AI-Generated Code](https://www.augmentcode.com/guides/eu-ai-act-2026) — Practical analysis of why standard coding assistants do not trigger Annex III high-risk obligations.
- [FBT Gibbons — AI Chatbots, Hallucinations, and Legal Risks](https://fbtgibbons.com/ai-chatbots-hallucinations-and-legal-risks/) — Survey of *Moffat v. Air Canada* and related case law; foundation for the granular-disclaimer recommendation in AI-5.
- [IAPP — Hallucinations in LLMs: technical challenges, systemic risks and AI governance implications](https://iapp.org/news/a/hallucinations-in-llms-technical-challenges-systemic-risks-and-ai-governance-implications) — Background on hallucination as an inherent property of LLMs; supports the disclaimer's framing.
- [Tech and Media Law — AI Hallucination Liability for Startups](https://techandmedialaw.com/ai-hallucination-liability/) — 2025 jurisprudence summary informing the responsibility-allocation framing.
