How Filmmakers Can Reduce AI Video Problems When Making Videos?

AI filmmaking has become a major trend in recent years. Artificial intelligence is now integrated into almost every aspect of our daily lives from kitchen appliances and home technology to cameras, smartphones, and countless other devices. AI video generation tools are being used every day by filmmakers, creators, and businesses around the world, while generating millions of dollars in revenue for the companies developing them. As these technologies continue to advance, AI is rapidly changing how video content is created, produced, and distributed.

AI  has made it possible for filmmakers, artists, and independent creators to produce cinematic scenes that once required expensive cameras, large crews, actors, sets, and visual-effects teams. Yet almost every AI video tool has one frustrating weakness: decoherence and morphing.

A character’s face may suddenly change. Hair can become a different color. Clothing may transform between frames. Hands and fingers can become distorted. Objects may disappear and reappear. A character can even seem to turn into another person. These problems occur across many AI video platforms, and they are not necessarily caused by a bad prompt.

The fundamental reason is that AI video generation is still an approximation of reality rather than a true understanding of a filmed scene.

What Is Decoherence?

Decoherence happens when visual information that should remain consistent begins to drift during a video.

Imagine generating a Viking character with red hair, a particular face, leather clothing, and a scar-free appearance. In the first few seconds, everything looks perfect. Then the face subtly changes. The hairstyle becomes different. The clothing changes shape. Eventually, the character may no longer look like the original person.

This happens because the model is generating visual information across multiple frames. Small differences can accumulate over time.

The AI does not maintain a perfect digital model of the character in the same way a 3D animation program would. Instead, it predicts what the next frames should look like based on the information it has been given.

A tiny change can therefore become a larger change later.

Why Morphing Happens

Several factors increase the likelihood of morphing.

Long shots are difficult because the model has to maintain consistency for many frames.

Complex movement makes the problem harder. If the character is walking, turning, fighting, speaking, gesturing, while the camera is also moving, the AI has to calculate many changes simultaneously.

Complex environments create additional challenges. Snow, smoke, fire, water, crowds, clouds, trees, and moving shadows all introduce constantly changing visual information.

Multiple characters are even more difficult. The model must remember which face belongs to which person while maintaining their positions, clothing, body proportions, and interactions.

Reference images help considerably, but they are not always a perfect identity lock. In many systems, a reference functions more like strong visual guidance than an unbreakable instruction.

How Filmmakers Can Reduce AI Video Problems When Making videos?

The most effective solution is surprisingly simple: make shorter shots.

Instead of asking an AI model to create a thirty-second sequence containing walking, dialogue, fighting, camera movement, weather, and complicated interactions,if it is 10 sec, go lower make it 6 sec shot, divide the scene into several smaller shots.

For example:

• Establishing shot of the village.
• Close-up of the character.
• Character walking toward another character.
• Two-shot of both characters.
• Close-up during dialogue.
• Reaction shot.
• Wide shot showing the environment.

These individual shots can then be assembled in an editing program such as DaVinci Resolve. I love this tool! It has everything in it and keeps getting better and better with each upgrade! I tried all other tools but my money is on Davinci Resolve Studio. 😉

Shorter generations give AI less time to drift, especially when using Google Flow (aka Veo 3). I hate using it, but I trust Google and know that “Google One” support agent is available if I run into payment or certain technical issues. With most other AI video tools, customer support, billing assistance, and technical help can be practically nonexistent. That is the ONLY reason I continue using Veo and I’ve found ways to work around its problems.

Camera movement should also be controlled. A static camera or slow cinematic push-in is generally easier to maintain than a complicated orbit, crane movement, zoom, and character movement happening simultaneously.

Another important technique is character consistency. Creators should establish a fixed description for each important character and reuse it throughout production. The description should specify facial structure, hair, age, clothing, body proportions, and other important characteristics.

For example, if a character must always have red hair and no facial scar, those details should remain consistent in every relevant prompt. For color grading, I either use LUTs or color-grade manually in DaVinci Resolve’s Color page. It depends on the story. If it is dark fantasy, I often grade manually. For some scenes, I use a LUT depending on the mood of the shot and its psychological resonance within that particular scene.

Reference images should also be reused whenever possible. Even better, a successful frame from one generation can sometimes be used as the visual starting point for the next shot. This creates a chain of visual continuity rather than generating every shot independently.

Don’t Ask AI to Make the Entire Movie

The most important lesson is that AI video generators should be treated as shot-generation tools, not complete filmmaking systems.

A professional looking AI film is created by combining many carefully controlled shots rather than expecting one generation to perform everything.

AI creates the individual images and moving shots. The filmmaker creates the story through editing.

Cuts can hide inconsistencies. Close-ups can protect facial continuity. Reaction shots can reduce the need for complicated interactions. Wide establishing shots can provide breathing room between detailed character shots.

Sound, music, editing, and pacing then transform these individual AI-generated moments into a coherent film.

AI video technology is improving rapidly, and future models will undoubtedly become better at maintaining identity, objects, environments, and physical continuity. But for today’s creators, the best strategy is not to fight the technology’s weaknesses.

Instead, design the filmmaking process around them.

Shorter shots, simpler movement, controlled cameras, strong references, consistent character descriptions, and careful editing can dramatically reduce decoherence and morphing.

The AI may generate the footage, but the filmmaker remains responsible for creating the illusion of reality. In the article below I explained the problem from machine learning and computer engineering perspectives. I answered to the questions such as

• Why are AI video tools still inconsistent?
• Don’t AI video tool providers know this is a problem?
• Do they have a real solution for identity drift? If they do, can they afford to implement it at scale?

Click the link below to find out.

Why AI Video Tools Still Struggle

Finally, why do we filmmakers use AI in the first place?

The reality is that most independent filmmakers don’t have a Hollywood budget. We don’t have the financial resources of a Christopher Nolan production, where large crews, professional actors, sets, equipment, insurance, locations, and countless other production costs can be covered.

Actors and crew need to be paid, productions need to be insured, locations need to be secured, and every day of shooting costs money.

For many independent filmmakers, AI provides a way to visualize and create stories that would otherwise remain impossible to produce.

That doesn’t mean we don’t want to work with real actors and professional crews. Quite the opposite. When we have the funding to do it properly, many of us would love to bring real actors and crews onto our productions.

Until then, AI can be a filmmaking tool that allows independent creators to develop their worlds, tell their stories, build an audience, and hopefully save enough resources to eventually produce those stories with real actors and traditional filmmaking techniques.
Here is another way to look at it: consider it a proof of concept!

Aren’t you tired of seeing so many remakes year after year? I mean, come on! There is so much fresh, original content waiting to be discovered. Why not give it a chance? Check out mine!

What we lack is investment.

Oh, and I promise you, we do have the marketing vehicles to promote it, reach an audience, and work toward getting your ROI back  plus hopefully generating a profit.

Look at how major Hollywood films are marketed today. A film like Christopher Nolan’s doesn’t simply appear in front of an audience. Millions were/are spent on AI marketing, and the film is continuously pushed and pushing across Facebook, Instagram, TikTok, LinkedIn, YouTube, press outlets, and film communities. Every minute, there is another piece of content, another interview, another trailer, another post, another discussion keeping the film in front of audiences.

That is the world we live in now.

We are not living in Hollywood in the 1950s or 1970s. We are living in the age of AI, social media, digital marketing, and global online communities. Independent filmmakers can now build awareness and promote their projects in ways that simply weren’t possible decades ago.

If you like the story and you are genuinely interested in it, then invest in it, and we can use a real cast, real crew, and the whole nine yards to make the film properly.

This way, our film community gets money in their pockets, creating opportunities for actors, filmmakers, technicians, and crew while helping address the employment challenges facing the film sector. And our audience gets entertained.

Until then, don’t blame us for using AI in production.

If you hate AI so much, but you genuinely like the story and the premise, why don’t you invest in making it with real actors and a real crew?

AI isn’t necessarily the destination. For many filmmakers, it is a bridge to getting there.