Will AI Really Reduce the Cost of Brand Films?

Artificial intelligence can now generate images, voices, animations and even complete shots.
One question is therefore coming up more and more often:

If AI makes production faster, will brand films become cheaper?

For an identical result, some tasks do indeed cost less. But in reality, brands are not simply asking for the same film at a lower budget.
AI opens up new possibilities, multiplies formats and makes it possible to create images that were previously out of reach. Savings made at one stage are often reinvested elsewhere.
Films therefore do not necessarily become cheaper. They often become more ambitious.

What AI Is Already Changing at L’Imagerie

At L’Imagerie, we use a wide range of artificial intelligence tools throughout the production process.

They allow us to:

• test voice-overs;
• generate storyboards;
• explore several creative directions;
• evaluate a set design before building it;
• create animatics;
• prepare certain sequences;
• speed up retouching;
• produce motion design elements;
• animate certain images more quickly;
• translate and adapt films;
• generate variations;
• check and validate exports.

These tools are used throughout the creative process, as well as during pre-production and post-production.
The question is therefore no longer whether AI should be used. It is about determining when it brings real value to a project.

Will Videos Become Cheaper?

There is no consensus on this question.

According to Wyzowl’s Video Marketing Statistics 2026, professionals have very different perceptions:

• 30% believe costs are decreasing;
• 32% see no change;
• 38% believe they are increasing.

These results show that AI is not causing a uniform decrease in video production costs.
It can reduce the cost of a specific task. But it can also lead to more versions, formats, personalisation and post-production.
The unit cost may decrease while the overall scope of the project increases.

Generating an Image Is Not Always Cheaper Than Shooting It

AI-generated imagery is often presented as an almost free solution. In practice, this is not always the case.
Generative AI tools are becoming increasingly powerful, but also increasingly expensive. Subscriptions, generation credits and the use of multiple solutions can quickly represent a significant budget.
The number of iterations required also needs to be taken into account.

A first generation rarely produces the final image straight away. Different prompts need to be tested, compositions adjusted, details corrected, consistency improved and, in some cases, several tools used.
Every new version requires time and resources.
To obtain a shot lasting only a few seconds, it may be necessary to generate dozens of options before retouching, animating, editing and integrating the result into the film.
In some situations, we find that it would ultimately be simpler and less expensive to shoot the scene.

The right question is therefore not always “can we generate it?”. We also need to ask whether generation is actually the most efficient approach.

What Was Once Out of Budget Is Now Possible

Let’s take a concrete example.

On one of our current projects, we are using AI to translate a film and adapt the actors’ lip movements to the new language.
Not long ago, this type of operation would have required a much heavier production process. Depending on the project, certain scenes might have needed to be reshot, the brand might have had to accept dubbing without precise lip-sync, or a highly complex post-production process would have been required.

This additional version would probably have been abandoned because it would have been out of budget.

With AI, it becomes accessible. But the film does not necessarily cost less than before, because this international version simply would not have existed.
The budget is now financing an additional possibility.
This is one of AI’s main effects: it does not simply replace existing tasks. It makes new ambitions possible.

A Lower Unit Cost, but More Deliverables

Brands are increasingly asking for more content:

• a main film;
• short formats;
• vertical versions;
• square versions;
• adaptations in several languages;
• variations for different markets;
• social media content;
• versions for stores or events.

AI can accelerate the creation of these variations. But each version still needs to be prepared, checked, corrected, approved and delivered.
For an identical result, some operations have indeed become less expensive.

But reality is rarely that simple. The time saved often makes it possible to produce more content or reach a level of finish that was previously inaccessible.
The budget is therefore shifted towards a richer production ecosystem.

High-Volume Content and Brand Films Serve Different Purposes

A social media variation designed to be used for a few days does not have the same requirements as a premium brand film created for an international launch.

For high-volume content, AI can quickly produce:

• variations;
• social adaptations;
• short formats;
• translations;
• short-lived content.

A premium brand film has different requirements.
It must precisely respect the visual identity, present the product correctly, maintain consistency between shots and achieve a sufficient level of quality across every platform.
AI can contribute to this process. It does not eliminate the need for direction, control and validation.

Generating an Image Does Not Mean Directing It

A tool can produce ten, fifty or a hundred options. Someone still needs to decide which one works.

What should the film communicate? What level of realism is appropriate? Which references should be avoided? How can consistency be maintained across several shots? Does the image genuinely reflect the brand’s visual language?
These decisions are part of creative direction.

AI accelerates exploration. It makes it possible to test several approaches before building a set, launching a production or approving an aesthetic.
At L’Imagerie, for example, we can use it to visualise a set design, test a lighting atmosphere or compare several creative directions.
These images do not necessarily become part of the final result. They help with decision-making and make it possible to better prepare the next stages of the project.
An Adobe study published in 2026 indicates that 76% of surveyed organisations are already seeing improvements in content volume and production speed through generative AI.
The easier it becomes to produce images, the more important the ability to select the right ones becomes.

Shots and Retouching That Were Previously Out of Reach

AI also allows us to produce certain images that we could not previously have achieved with the same resources.

It can be used to:

• extend a set;
• transform a background;
• remove or modify an element;
• enhance a material;
• adapt facial movements;
• create a transition;
• perform advanced retouching;
• generate an additional shot.

Some of these operations would previously have required a new shoot, a significant 3D team or several days of compositing and post-production.
AI makes them more accessible. But once again, the savings are not always removed from the budget. They can instead be used to enrich the film, create more shots or improve the level of finish.

Increasingly Hybrid Productions

The most interesting scenario is probably not choosing between a live-action shoot and a fully AI-generated video.
It is combining the two.

A project can bring together:

• live-action footage;
• physical sets;
• generated imagery;
• 3D animation;
• VFX;
• AI-assisted retouching;
• translation and lip-sync adaptation.

Live-action shooting remains relevant for products, actors and elements that require precise control.
AI can then extend those images, accelerate certain retouching tasks or produce elements that would otherwise have been too complex to create.
It integrates naturally into our post-production workflow, which already includes editing, colour grading, sound, motion design and visual effects.

So, Does AI Ultimately Reduce the Budget?

For an identical result, AI does reduce costs.
It can speed up preparation, produce variations more quickly and simplify certain post-production operations.
But projects rarely remain identical.
AI opens up new possibilities. It can add an international version, create a shot that was previously impossible, multiply formats or increase the level of finish.

It can also require many iterations and several different tools before producing a usable image. In some cases, shooting remains the simplest and least expensive solution.
It is therefore more accurate to talk about a shift in budgets than an overall reduction.
Films do not necessarily become cheaper. They can simply become more complete, more international and more ambitious.

The question is no longer:
Can we replace this production with AI?

It becomes:
How can we use AI to improve the film and create images that would not otherwise have been possible?

Used in this way, artificial intelligence becomes another tool within audiovisual production.
It allows us to move faster on certain tasks, explore more creative directions and push certain technical boundaries. But knowing why an image should be created, which one to choose and how to integrate it into a coherent film remains a matter of creative direction and production.