Tips and Tricks/Common Issues with AI Generation

Common Issues with AI Generation

The most frequent problems users run into with AI generation — why they happen and what you can do about them.

6 min read

This page explains the most common issues you may run into when generating AI videos in AutoReach, why they happen, and what you can do about them. If you are new to AI video generation, start here to set the right expectations before you begin creating.

How AutoReach Works Under the Hood

AutoReach is built on top of AI models and engines developed by major tech companies like Google, OpenAI, and ByteDance. These companies invest billions into building and maintaining these AI engines. AutoReach does not have its own AI models.

What AutoReach does is sit on top of these models and make them usable for marketers. We simplify the process, add features on top, and help you get the best possible results for your ads without needing to be a technical expert.

Note

AI video generation is at the bleeding edge of AI innovation. This technology has only been publicly available for a few months, not years. It is experimental by nature. Keep that in mind when you are working with it. The results can be impressive, but they are not as predictable or reliable as tools you may be used to.

Total Failures

A total failure is when you request a generation and it comes back as "failed" with no video file at all.

When this happens, AutoReach automatically refunds the credits to your account before you even notice the failure.
The most common cause is capacity overload. These AI engines are extremely popular right now and have limited processing power. When too many people are generating at the same time, some requests get dropped.
The fix is simple: click Retry in AutoReach. This resubmits your generation request. Most succeed on the second try. Some may take a few attempts during peak traffic.

Note

There is nothing AutoReach or you can do to prevent capacity-related failures. They are caused by the underlying AI providers running at full load. Retrying is the only solution.

Models most affected by total failures

Veo 2 and NanoBanana Pro are currently the most widely used AI video models in the world. Because of their popularity, they hit capacity limits more often than other models. Google's Veo 2 in particular runs at or near full capacity almost constantly.

If you are experiencing repeated failures with these models, try again after a few minutes or switch to a different model temporarily.

Technical Issues

A technical issue is when the generation succeeds and you receive a video file, but something is clearly wrong with the output. Common examples include:

Speech is completely muted or nearly silent
Heavy background noise drowning out the speaker
Strange visual artifacts in the footage, like holes or glitches in the video

Why this happens

Two things can cause technical issues. First, your prompt may unintentionally trigger the problem. Words like "quiet room," "ambient," or anything that could be interpreted as low volume can cause the AI to reduce speech audio.

Second, AI generation introduces a degree of randomness into every output by nature. Even with a perfect prompt, there is always a small chance of a technical defect. For example, you could run the same prompt 20 times and get 15 perfect videos, but 3 of them might have no audio. That is just how the technology works right now.

How to reduce technical issues

Add clarity keywords and negative prompts to the end of your prompt to steer the AI away from common defects:

"Clear speech, loud audio, no background noise"
"Clear talking, no ambient sound"
"Clear footage, full HD quality"

These keywords help a lot, but they cannot eliminate the randomness entirely. If you get a result with a technical defect, you can either try to fix it in editing or simply regenerate.

Pro tip

Adding negative prompts like "no background noise" and quality keywords like "clear speech, full HD quality" at the end of your prompt significantly reduces the chance of audio and visual defects.

Model most affected by technical issues

Sora 2 is currently the best model for authentic selfie-style videos, but it is also the most common model to produce technical issues. Low audio volume is the most frequent problem with Sora 2 outputs.

Quality Issues

Quality issues are when the video generates successfully and plays fine, but the content looks unrealistic. Common examples include:

Morphing or distorted hands
Six fingers instead of five
Objects floating in the air instead of falling
Blurry or soft footage
Lips not matching the spoken audio (lip sync issues)

Why this happens

Quality issues usually come from one of two causes.

Your prompt is not specific enough. The AI fills in the gaps on its own, and the results can look off. Being detailed and explicit about what you want helps the AI stay on track.

You are asking the AI to do too much in one generation. This is the most common mistake. If you try to pack complex physical movements, multiple actions, or delicate motions into a single generation, the AI is far more likely to produce morphing, merging, or unrealistic results.

Examples of requests that often cause quality issues:

Complex physical actions like backflips or gymnastics
Delicate hand gestures like making a heart shape or showing specific finger counts
Multiple characters performing different actions at the same time
Long sequences with many scene changes in one generation

Warning

The more complexity you add into a single generation request (movement, lip sync, multiple characters, product interaction), the higher the chance of quality issues. Keep each generation focused on one simple action or shot.

How to reduce quality issues

Be specific in your prompt about exactly what you want to see
Use negative prompts to call out things you do not want (e.g., "no distorted hands, no blurry footage")
Keep each generation focused on one simple action or scene
Avoid relying on complex physical movements for the success of your video
Think creatively about how to achieve your vision with simpler shots

Pro tip

Do not design your ad around a moment that requires precise physical movement from the AI. Instead, plan shots that are simple and natural, like a person holding a product, looking into the camera, or walking slowly. Save the complexity for editing.

Models most affected by quality issues

Kling and Seedance tend to have fewer technical issues (speech quality is usually great), but they are more prone to quality and realism problems. The most common issues with these models are out-of-sync lip movements, morphing hands, and extra fingers.

Quick Summary

Issue Type	What It Looks Like	Most Affected Models	What to Do
Total Failure	No file returned, generation marked as failed	Veo 2, NanoBanana Pro	Click Retry. Credits are auto-refunded.
Technical Issue	Muted audio, background noise, visual glitches	Sora 2	Add clarity keywords and negative prompts. Regenerate if needed.
Quality Issue	Morphing hands, bad lip sync, unrealistic physics	Kling, Seedance	Simplify your prompt. Break complex scenes into separate shots.

Want to Improve Your Results?

Most of these issues can be reduced significantly with the right approach. Read our How to Get the Best Results with AI Generation guide for detailed tips on prompting, shot planning, and using AutoReach tools like the Prompt Optimizer and Presets.

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