Script to Video with Wan 2.7: Complete AI Creative Workflow

Introduction

I've been experimenting with AI video workflows for over a year, and I kept running into the same problem: most tutorials show you how to generate a random video from a text prompt, but nobody shows you how to go from a written script to a finished, usable video that actually tells a story.

So I built my own workflow.

This guide walks through the exact process I use to turn a script — whether it's a product demo, a social media clip, or a short narrative — into a complete AI-generated video. The core engine is Wan 2.7 for video generation, combined with text planning from Qwen and image creation through Alibaba's Z-Image. The entire workflow runs in a browser and takes about 45 minutes from start to finish.

This isn't a "type a prompt and wait" tutorial. It's a production workflow that treats AI video generation as a creative tool, not a magic button.

TL;DR

• Script to video requires breaking your script into visual beats — don't generate one long video, generate multiple short clips
• Wan 2.7 handles 5-second clips best — plan your script around short, punchy scenes
• The full workflow uses three tools: Qwen for script analysis, Z-Image for reference frames, Wan 2.7 for video generation
• Style consistency across clips is achievable — use a style reference image and consistent prompt templates
• You can test this workflow directly on the Wan 2.7 AI Video Generator — no local setup required

What This Workflow Solves

Most people trying AI video generation hit the same walls:

• Random results — One prompt generates something great, the next generates garbage, and you can't control the difference
• No story structure — Individual clips look good but don't flow together into a coherent narrative
• Style drift — Each clip looks like it was generated by a different model
• Wasted generations — Without planning, you spend most of your time (and credits) on throwaway results

This workflow solves all four by treating AI video generation as a structured production process — with planning, templating, and quality gates at each step.

Workflow Overview

Here's the complete process at a glance:

Script → Scene Breakdown → Reference Images → Video Generation → Assembly → Final Polish
   ↓            ↓                 ↓                   ↓               ↓            ↓
  Write      Split into       Generate          Generate 5s       Combine      Add music,
  script     5-7 scenes      style frame       clips per scene    clips        transitions,
                + prompts       per scene        pick best                      captions

The entire workflow takes about 45–60 minutes for a 30–45 second final video.

Step 1: Write and Structure Your Script

Start with a script that's written for visual delivery, not reading. A script for AI video generation needs to be:

• Short scenes: 5–15 seconds each, which translates to 1–3 AI-generated clips per scene
• Visual descriptions: Instead of "the product is easy to use," write "hands pick up the product, press a button, a screen lights up"
• Active verbs: "walks," "moves," "transforms," "lights up" — Wan 2.7 handles motion best when the prompt describes a clear action

Script Template

Scene 1: [Establishing shot / Hook]
Visual: [What the viewer sees]
Narration/Voiceover: [What's said]
Duration: 5 seconds

Scene 2: [Problem / Context]
Visual: [Action or transition]
Narration/Voiceover: [What's said]
Duration: 5-10 seconds

Scene 3: [Solution / Core message]
Visual: [Key visual moment]
Narration/Voiceover: [What's said]
Duration: 5-10 seconds

Scene 4: [Social proof / Demonstration]
Visual: [Example or demonstration]
Narration/Voiceover: [What's said]
Duration: 5-10 seconds

Scene 5: [Call to action / Close]
Visual: [Final frame]
Narration/Voiceover: [What's said]
Duration: 5 seconds

Example: Coffee Shop Promo Script

Scene 1: Wide shot of a coffee shop interior, morning light streaming through windows
Scene 2: Close-up of a barista pouring latte art
Scene 3: Customer takes first sip, looks satisfied
Scene 4: Counter shot with pastries and coffee cups
Scene 5: Exterior shot with "Open" sign and street view

This script breaks down into 5 scenes, each 5–10 seconds. We'll generate 1–2 Wan 2.7 clips per scene and assemble them.

Step 2: Create Reference Images for Each Scene

This is the step most people skip — and it's the biggest difference between "random AI clips" and "a coherent video."

Before generating video, create a reference image for each scene using an AI image model. This image serves as:

• Visual anchor — Wan 2.7 works best when it has a reference image rather than just text
• Style consistency — All scenes use the same aesthetic, lighting, and color palette
• Composition planning — You can iterate on the image before committing to video generation

How to Create Reference Images

Use Z-Image (Alibaba's image generation model) or another AI image tool. For each scene, write a prompt that describes:

1. The scene composition
2. The lighting and atmosphere
3. The color palette
4. The style (cinematic, product photo, illustration, etc.)
5. Key visual elements

Keep the style description consistent across all scenes. For example, if your video is "warm, cozy, cinematic with golden hour lighting," every scene's prompt should include those same style markers.

Example Reference Image Prompt

Scene 1: "A cozy coffee shop interior, warm wooden tables, morning sunlight streaming through large windows, steam rising from a coffee cup on the counter, cinematic composition, warm amber and brown color palette, photorealistic style, depth of field"

Generate one reference image per scene. Don't move to Step 3 until you're happy with each reference frame.

Step 3: Generate Video Clips with Wan 2.7

Now you have a script broken into scenes and a reference image for each scene. Time to generate video.

Prompt Structure for Wan 2.7

The Wan 2.7 AI Video Generator accepts two inputs: a reference image and a text prompt. The prompt structure I use:

[Motion description], [scene details], [style markers], [quality markers]

For Scene 1 from our coffee shop example:

Image: Reference image of the coffee shop interior Prompt: "Slow dolly-in shot approaching the counter, steam gently rising from coffee cup, warm morning light shifting slightly, cinematic 24fps motion, smooth camera movement"

Generation Tips

• Keep clips to 5 seconds — Wan 2.7 produces the most consistent results at 5-second durations. Longer clips often introduce artifacts or motion inconsistency.
• Generate 3 versions per scene — Run each scene prompt 2–3 times and pick the best one. The first result isn't always the best.
• Focus on one action per clip — If a scene has two actions (e.g., pouring + serving), split into two clips.
• Watch for motion consistency — Objects should move naturally. If the motion looks unnatural, adjust the prompt to be more specific about the motion type and speed.

Common Prompt Adjustments

Issue	Fix
Too much motion, shaky	Add "smooth, slow, steady camera" to prompt
Not enough motion	Add "gentle motion, subtle movement, flowing"
Characters look wrong	Add specific character descriptions to the reference image
Colors are off	Match the reference image style more closely in the image prompt
Scene changes too abruptly	Add "seamless transition, continuous" to the prompt

Step 4: Assemble Your Clips

Once you have all your 5-second clips, it's time to assemble them into a sequence.

Assembly Order

1. Open your video editor (CapCut, DaVinci Resolve, Clipchamp — any basic editor works)
2. Import all generated clips in scene order
3. Trim each clip to the best 3–5 seconds (cut the start and end where the model is "warming up")
4. Add crossfade transitions between clips (0.3–0.5 second fade works best)
5. Match timing to your script narration — clip duration should match the voiceover timing

Timing Guidelines

• 5-second clip → about 3–4 seconds of usable footage after trimming
• For a 30-second video: plan 7–10 clips
• Leave 1-second buffer between clips for transitions

Step 5: Refine and Export

The final pass is where you add polish:

• Speed adjustment — Slow down or speed up clips by 5–10% for better pacing
• Color grading — Apply a consistent LUT or color filter across all clips for visual unity
• Audio — Add background music (royalty-free) and narration if you have it
• Captions — Add text overlays for social media or accessibility
• Branding — Add logo, brand colors, or text overlays if this is for a business

Export Settings

Platform	Resolution	Format	Duration
Instagram Reels	1080×1920	MP4 H.264	15–60s
YouTube Shorts	1080×1920	MP4 H.264	15–60s
TikTok	1080×1920	MP4 H.264	15–60s
Website/YouTube	1920×1080	MP4 H.264	30–120s
For a closer look at how it stacks up against other models, see GPT Image 2 vs Free AI Image Generators.
If you want to test it without installing anything, the free Wan video generator works in the browser.
If you want to test it without installing anything, the free image-to-video generator works in the browser.

Tools Used in This Workflow

Step	Tool	Purpose
Script planning	Qwen (or any LLM)	Analyze and structure the script
Reference images	Z-Image (Alibaba)	Generate style-consistent reference frames
Video generation	Wan 2.7	Generate 5-second video clips from reference + prompt
Video assembly	CapCut / DaVinci Resolve	Timeline editing, transitions, audio
Audio	Artlist / Epidemic Sound	Royalty-free background music

Example Output

Here's what the final result looks like for our coffee shop script:

Final video: 35 seconds, 8 clips assembled

• Scene 1: Exterior wide shot → fade to interior
• Scene 2: Barista pouring latte art (2 clips, different angles)
• Scene 3: Customer reaction shot
• Scene 4: Pastry counter with slow pan
• Scene 5: Exterior with "Open" sign, slow zoom out

The magic is that each individual clip looks polished, and because we used consistent reference images and prompt templates, the overall video feels like one coherent production — not a collection of random AI generations.

Common Mistakes

• Skipping reference images — Text-to-video without a reference image produces wildly inconsistent results. Always generate a reference frame first.
• Making clips too long — 5 seconds per clip. Longer clips introduce motion artifacts and inconsistency. If you need more time, generate multiple clips and stitch them.
• Inconsistent style descriptions — Every prompt must include the same style markers. Change one word (e.g., "warm" → "cool") and the clip looks like it's from a different video.
• No voiceover planning — If you're adding narration, time the clips to match the spoken words. A video with mismatched audio-visual timing is immediately noticeable.
• Generating once and accepting it — AI generation is stochastic. Always generate 2–3 versions per scene and pick the best one.

Best Way to Try This Workflow

If you want to run this exact workflow, you can start with the Wan 2.7 AI Video Generator for video generation. The platform supports image-to-video and text-to-video with Wan 2.7, so you can follow every step in this guide without local setup.

For reference images, you can use any AI image generator. The key is consistency across all scenes — same style, same lighting, same aesthetic.

Related guides

• GPT Image 2 vs Free AI Image Generators: Complete Comparison Guide for 2026
• Krea 2 vs Qwen Image Edit vs Z-Image: Complete Comparison Guide (2026)
• Wan2GP Free Guide: How to Install & Use the Local Wan AI Video Tool

FAQ

What is the script-to-video AI workflow?

It's a structured process that turns a written script into a complete AI-generated video by breaking the script into visual scenes, creating reference images for consistency, generating short video clips with Wan 2.7 for each scene, and assembling them into a final sequence.

Why use short 5-second clips instead of one long generation?

Wan 2.7 produces the most consistent results at 5-second durations. Longer generations often introduce motion artifacts, character inconsistencies, or style drift. Multiple short clips assembled together produce better results than one long clip.

Do I need a powerful computer to run this workflow?

No. Everything runs in a browser. Wan 2.7 is cloud-based — you only need a stable internet connection.

Can I use this workflow for commercial projects?

Yes. Wan 2.7 allows commercial use of generated content. Always check the specific terms of any tool you use, but the Alibaba AI models generally permit commercial applications.

How long does the full workflow take?

After practice, about 45–60 minutes for a 30–45 second video. The first few times will take longer as you refine your process and prompt templates.

What's the difference between Wan 2.7 and other AI video models?

Wan 2.7 excels at motion consistency and prompt adherence compared to many alternatives. It's particularly strong at image-to-video generation — which is why this workflow centers on creating reference images first. You can explore more on the Wan 2.7 product page.

The Bottom Line

The script-to-video workflow turns AI video generation from a random lottery into a repeatable production process. The key insight is simple: don't treat AI as a magic video machine. Treat it as a powerful tool in a structured creative workflow.

Plan your scenes. Create reference images for consistency. Generate short clips and assemble them. The results — even for beginners — are dramatically better than typing a single prompt and hoping for the best.

The tools are accessible, the process is learnable, and the output quality keeps improving. If you've been experimenting with AI video and getting inconsistent results, start with this workflow. It's the closest thing I've found to a reliable production pipeline.

References

• Wan 2.7 AI Video Generator
• Wan 2.7 Image to Video on Pollo.ai
• Alibaba Z-Image AI Image Generator — Alibaba Cloud
• Wan 2.7 Technical Report — arXiv
• AI Video Generation Best Practices Guide — Runway (general reference for AI video workflows)