Operating ProcedureExecution layer

AI-Assisted Edit Review Gate (QA)

A checklist with 7 steps: Define the acceptance criteria for the representative brief before any edit begins.

By InnovaAI ResearchPublished

checklist

AI-Assisted Edit Review Gate (QA)

  1. 01

    Define the acceptance criteria for the representative brief before any edit begins

    List required formats, resolution, duration, and brand elements. This gives editors and reviewers a shared target, reducing rework loops.

  2. 02

    Run the brief through the AI-assisted editor's automated pass

    Use features like silence removal, caption generation, or clip selection to produce a first draft. Tools such as Descript or Submagic can handle repetitive tasks, but the output must be checked against the brief.

  3. 03

    Compare the draft against the acceptance criteria item by item

    Check that all required segments are present, captions are accurate, and the pacing matches the intended tone. Note any deviations for correction.

  4. 04

    Measure the time spent on manual corrections versus the automated pass

    Log editor hours for the AI-assisted draft and for the manual fixes. This quantifies the labor savings and highlights where the tool underperforms.

  5. 05

    Verify format and platform compliance for every deliverable

    Confirm that exports meet the client's specs, whether it's a vertical short for social or a widescreen cut for broadcast. Tools like KinoPipe can handle format conversions in a single pass, but the output must be spot-checked.

  6. 06

    Review the final cut for brand and legal compliance

    Ensure no copyrighted music or unapproved assets slipped in. Given recent lawsuits over AI training data, agencies must confirm they have rights to all elements used in client deliverables.

  7. 07

    Document the correction time and acceptance rate for the brief

    Record the number of deliverables accepted on the first pass and the total editor hours. This data feeds the agency's productivity benchmarks and informs future tool choices.