Lesson Content

Client disclosure practices for AI-assisted work.

Disclosure approaches vary by client expectation and project type: Proactive disclosure – informing clients when AI tools will be used in production, establishing this as part of the engagement scope; Methodology transparency – including AI tool use in the project methodology description without requiring client approval of individual tool choices; Reactive disclosure – disclosing AI use when specifically asked. Agencies and freelancers should establish a consistent disclosure policy and communicate it in client agreements, not improvise per-project. Some clients specifically request or prohibit AI tool use – establishing this in the initial brief prevents misalignment.

Team AI use policies.

A team AI use policy for commercial production: defines which AI tools are approved for commercial use and in which project types; specifies the commercial use verification requirements before using AI tools on client work; establishes quality review and approval requirements before delivering AI-assisted content; defines disclosure and documentation requirements; and addresses confidentiality (client work should not be submitted to AI tools that use inputs for training if the client's work is confidential – verify Firefly's data use policy at adobe.com/legal/terms for current terms on input data use).

Documentation requirements for commercial AI projects.

Documentation for commercial AI production: terms verification date and summary (when commercial terms were verified and what they state); content review completion (who reviewed the content and when, what checklist was applied); client communication records (when and how AI use was disclosed, client acknowledgment if applicable); and asset provenance records (which assets were AI-generated, which were manually created, which were licensed from external sources). Documentation creates professional accountability and supports any future questions about the project's production methodology.

Quality governance for commercial AI production.

Quality governance standards for commercial AI production: AI-generated assets meeting the same quality threshold as manually created assets; accuracy verification for any text content before commercial delivery; brand compliance review against client brand standards; legal and compliance review for regulated content categories; and final approval from the account lead or creative director before commercial deployment. Quality governance ensures professional accountability at every step of AI-assisted commercial production.