An automated workflow that transforms manual video creation processes into streamlined AI-powered content production. Uses ChatGPT for scripts, ElevenLabs for voiceovers, and Hailuo/Kling for video generation with CapCut for final assembly.
Marketing teams need a steady flow of short video for social, ads and product launches, but traditional production means scripting, booking talent, recording voiceover, shooting or sourcing footage and editing. Each step waits on the previous one. Small teams either publish less video than they would like or rely on stock clips that look like everyone else's content.
An AI video production workflow chains generative tools into a single pipeline. A creative brief goes in, a custom GPT drafts the script and shot list, ElevenLabs produces the voiceover, video models such as Hailuo, Kling or Veo generate scenes, and CapCut assembles a first cut. The marketing team reviews and refines the draft rather than coordinating every stage by hand.
A marketer submits a brief through a form with the product, audience, tone, length and call to action; n8n or Make.com picks it up and starts the run.
A custom GPT trained on brand guidelines writes the script and a scene-by-scene shot list with visual prompts, which a team member approves or edits.
ElevenLabs renders the narration from the approved script using a licensed stock voice or a voice the business has consent to use.
Each scene prompt is sent to a video generation model, and the clips are collected along with the audio, captions and brand assets.
The clips are assembled into a timeline in CapCut, and the draft is returned to the team for review, re-generation of weak scenes and final export.
A marketing team inputs a creative brief into their automation system. The workflow generates scripts using a custom GPT, creates voiceovers with ElevenLabs, generates video scenes with AI tools, and assembles the final cinematic video automatically, with a person reviewing the final cut.
ChatGPT Custom GPT, ElevenLabs, Hailuo/Kling/Veo, CapCut API, n8n/Make.com automation
Advertising claims in AI-generated videos are still the business's claims, so scripts must be checked for accuracy under the Australian Consumer Law before publishing. Check each video model's commercial-use terms, and be cautious about prompts that imitate identifiable people, brands or copyrighted characters; ownership of purely AI-generated material under the Copyright Act 1968 is not settled, so avoid relying on exclusivity. If a real person's voice or likeness is used, get written consent. Some platforms require AI-generated content labels, and disclosing synthetic presenters is good practice for trust.
This solution requires careful evaluation of cost-benefit ratio. Consider implementation only after thorough analysis and risk assessment.
It removes much of the assembly work, but someone still needs editorial judgement. The pipeline produces a rough cut; a person checks pacing, fixes awkward scenes, confirms claims and decides whether the result is good enough to publish. Many teams find their editor shifts toward creative direction and quality control.
Each generative tool behaves differently, and getting consistent brand-quality output takes iteration. Time goes into prompt libraries, style references, API integration, error handling when a model fails and building approval steps. The workflow also needs testing across several real briefs before the team can trust it for regular production.
Ownership depends on each tool's terms and on Australian copyright law, which generally protects works with human authorship. Content with substantial human input into scripts, selection and editing is on firmer ground. Review the licence terms for every model in the pipeline and avoid prompts that copy existing works.
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