Who Owns AI‑Generated Content? A Three‑Step Protocol to Secure Copyright and Commercial IP

Problem background : After delivering AI‑generated graphics or copy, clients often question copyright ownership, causing payment delays. The legal status of AI‑created images, text, and code remains ambiguous, leaving the service provider liable for any infringement.

Core principle : Instead of betting on luck, proactively isolate risk. Run AI‑based scans, have the client sign a risk‑transfer statement, and keep a traceable record so that uncertainty becomes transparency.

Step 1 – AI Risk‑Pre‑Screen Prompt

Target: large language or image models at the final‑delivery review stage.

Input: paste the finished draft into the chat window.

Prompt example (red text in the original):

You are a commercial copyright auditor. Scan the following for:
      1. Fonts / images that appear AI‑stitched or lack commercial license – replace with open‑source alternatives.
      2. Copy containing high‑risk advertising terms (e.g., “最/第一/绝对”) or possible plagiarism.
      3. Code or data that includes unauthorized third‑party libraries or scraped datasets.
      4. Output a revised version plus a "Commercial Risk List" with risk level and replacement source. Do not add any filler text.

Step 2 – Authorization Statement & Record Checklist (Manual Version)

Responsible party: the supplier (乙方) delivering the work.

Attach a document titled AI‑Assisted Commercial Authorization Statement that clearly defines copyright ownership, liability scope, and replacement responsibilities.

Provide links to open‑source material sources and the corresponding commercial license PDFs.

Record a delivery snapshot with a hash value to prevent tampering.

Never rely on oral promises such as “copyright is fine”; always attach the signed statement before sending the final file.

Step 3 – Dispute‑Break‑Circuit Routing (System Configuration)

Integrate with enterprise WeChat (企微) or Feishu approval flow.

When a client raises an objection, automatically freeze the remaining payment and trigger legal review.

Store prompt shortcuts, risk lists, and routing rules in the backend; the process has been tested to run once without interrupting delivery.

Value mapping : By converting “fast delivery, slow payment” into “delivery with attached authorization + risk‑intercept log”, the payment cycle shortens, client disputes drop, and legal review time shrinks dramatically.

Common pitfalls : Skipping the scan and sending raw output leads to breach of contract; overly long statements cause clients to ignore them; using outdated templates can cause regulatory non‑compliance.

Practical tips : Keep the authorization statement under 150 characters, split into three concise sections (copyright, disclaimer, provenance). Use lightweight alternatives for AI‑built filters—font‑library searches, Openverse image sources, and manual keyword cross‑checks—to achieve zero‑cost compliance.

Future outlook : Major platforms (e.g., Tongyi, Wenxin, iFlytek) embed copyright filters but cannot guarantee 100 % compliance; building an independent isolation layer remains essential for commercial AI delivery.