AI Video VFX Workflow: How to Combine AI With Traditional VFX | Z

The right way to think about AI + VFX

AI generation is powerful because it can create or modify visual information quickly. Traditional VFX is powerful because it gives artists repeatable control over geometry, motion, masks, layers, lighting and final integration.

Putting the two together creates a useful division of labor: AI can solve visual-content problems while the VFX pipeline solves control and integration problems.

That approach is becoming more visible in current industry workflows. A July 2026 SIGGRAPH discussion on AI VFX and generative video centered on “creative control,” while current production examples describe AI being refined inside compositing rather than simply accepted as final output.

The complete AI/VFX pipeline

1. Start with the plate

Before using AI, inspect the original footage. Identify camera movement, lens behavior, exposure changes, depth of field, motion blur, grain and anything that will affect the integration.

For professional work, keep the original plate untouched and work from controlled versions. This makes it possible to compare the AI result against the source at every stage.

2. Track the shot

Tracking provides the spatial information needed to place an AI-generated element into the scene.

Traditional tracking remains valuable even when the generated content itself comes from AI. Current professional VFX training continues to emphasize tracking, stabilization and rotoscoping as core production skills.

3. Roto, key or isolate the subject

AI can assist masking and matting, but an artist still needs to inspect the edges. Hair, motion blur, transparent objects and fine details can reveal mistakes.

Silhouette’s 2026 release, for example, adds AI-assisted masking, matte creation and tracking tools aimed at reducing manual roto work.

The practical workflow is:

The same principle applies to any automated VFX step: use AI for the first pass, then make the final matte production-ready.

4. Generate or modify the element

Once the shot is understood, decide what AI should actually do.

Current AI/VFX examples include turning an empty stadium into a crowd-filled shot while preserving the player and camera, and using AI relighting inside Nuke while maintaining a production compositing workflow.

5. Use depth, masks and references

Generated footage becomes easier to control when you provide spatial information. Depending on the workflow, this can include masks, depth maps, reference frames, tracked points or explicit trajectories.

Recent research is moving in exactly this direction. SIGGRAPH 2026 work such as Go-with-the-Track explores video compositing and motion control using point tracking, while newer generative compositing research focuses on trajectory control and explicit foreground/background representations.

6. Relight and match the generated element

Even a visually impressive generated element can look pasted into the shot if its lighting does not match.

• Match key-light direction.
• Match color temperature.
• Match contrast and black levels.
• Match atmospheric perspective.
• Match depth of field and motion blur.
• Add contact shadows where required.
• Match grain and texture.

AI relighting workflows are already being demonstrated inside professional compositing environments, with emphasis on matching the result back to the original plate and restoring texture or correcting artifacts.

7. Composite and finish

Compositing is where the shot becomes believable. Build the image in logical layers so you can control foreground, generated element, atmosphere, background, reflections and color independently.

Recent research on explicit video layers is also exploring ways to represent foreground and background separately for more controllable insertion and post-editing.

8. QC the final shot

AI artifacts can be subtle. Review the shot frame by frame, especially around faces, hands, object boundaries, reflections and fast motion.

Practical AI + VFX examples

Example 1: Expand a location

Plate → camera track → generate extension → match perspective → composite → grade.

This can be useful for turning a limited physical set into a larger environment while preserving the original foreground performance.

Example 2: Add a crowd

Plate → isolate foreground → generate crowd background → integrate → match lighting → composite.

A current 2026 AI VFX example demonstrates this exact concept with an empty stadium transformed into a crowd scene while retaining the original player and camera work.

Example 3: AI relighting

Original plate → AI relight → restore texture → integrate with original → final grade.

The key is that the AI output is not simply exported and forgotten; it is brought back into the compositing workflow for control and finishing.

Example 4: Generate a concept effect

Use AI to explore a creature, explosion, magical environment or transformation quickly. Once the visual direction is approved, use traditional 2D/3D methods where exact control is required.

When should you NOT use AI?

• When exact geometry is essential.
• When a client needs deterministic frame-by-frame revisions.
• When a hero asset must remain perfectly consistent across many shots.
• When the generated result is harder to clean than creating it traditionally.
• When licensing or confidentiality requirements prohibit the chosen service.

AI is valuable when it reduces production effort. If it creates more cleanup than the original task, it is the wrong tool for that shot.

The Zgian AI/VFX rule

That is the core philosophy we should use across Zgian’s AI/VFX content. It is technically more credible, more useful to professionals and more distinctive than presenting AI generation as a replacement for the entire VFX pipeline.

Frequently asked questions