With the increasing volume of video being produced, it is becoming more difficult for content creators to keep up with the demand for their videos. In an era where users expect real-time access to relevant video, marketers need to find ways to surface timely and engaging video that resonates with consumers. AI-generated video can accomplish this while delivering a better user experience. Let’s explore advanced AI-generated video, its potential use cases, and its limitations.

What is AI-Generated Video?

Let’s start by defining what we’re really talking about when we refer to AI-generated video. AI-generated video is a type of video production where an algorithm is used to generate content based on the media and public attention it is likely to receive. Unlike other forms of video production, where a human creates the video, AI-generated video is produced by algorithms.

These algorithms are trained to generate videos that are relevant to the audience, timely, and with good quality. AI-generated video can be used in a few different ways when compared to other video types. It can be used as an alternative to human-generated video in ads, or it can be used as the basis for a video news article.

Advancements in AI-Generated Video

The field of AI has been around for a long time, and over the years it has seen significant advancements that have paved the way for more impactful AI-generated video. We’re going to take a look at the main advancements that have taken place in AI-generated video and how they can be applied to improve the video publishing process.

Training the algorithm to produce better results – The first and most significant advancement in AI-generated video was the development of meta-programming, which enabled the creation of better results-driven videos. Before meta-programming, content creators had to hope their algorithm was programmed to produce video that would be of good quality, timely, and relevant to the audience. Now, with meta-programming, the AI can be programmed to produce better results with less effort from the content creator.

Deciding what to include in the video – The second advancement in AI-generated video was the ability to include assets based on topic or sentiment. In the past, content creators would have to assume their algorithm would always produce video with perfect grammar and no apparent errors. Now, content can specify what to include in the video and the AI can decide what parts of the video to include.

Potential Use Cases of AI-Generated Video

When it comes to potential use cases for AI-generated video, we have a few different categories to choose from. The first is advertising. For brands looking to create more engaging videos, AI can help by training ad-specific modules to produce better results. Similar to the advertising examples, AI can also be used in video news articles to help deliver timely and relevant content to viewers.

Advantages of AI-Generated Video

More impactful video – When it comes to advantages of AI-generated video, there are a few different categories that come to mind. The first is impactful video. AI-generated video is much more impactful than human-generated video, as it can create videos that have a much greater effect on consumers.

This can be done through several different means, such as the ability to include higher resolution photos and videos or offer additional information or insights that might be relevant to the viewers’ situation or life.

More personal – Another advantage of AI-generated video is that it allows brands to create more human-like videos with ease.

Humans are much better at creating videos that are appealing to the eyes and don’t attempt to appeal to the brain, but AI-generated videos are different in that regard.

Better user experience – According to research, a large percentage of consumers (46%) are likely to watch a video ad three or more times, and when they do, they are likely to be affected by the brand’s tactics.

AI-generated video can deliver personalized, relevant content to consumers based on their previous ad views.

Disadvantages of AI-Generated Video

More work for the creators – The main disadvantage of AI-generated video is that it requires a lot of work from the content creator. Since the algorithm has to be programmed to produce good quality videos, it can’t simply be thrown into theMod bin and left to generate content.

It has to be trained to produce high-quality results and then tested to see if it actually works on the target audience. Fragmented view of the creative process – The creative process for AI-generated video is likely going to be more fragmented than in-house-generated video.

The algorithm is going to have to generate multiple videos with various attributes and produce them in real-time. While it might sound like a dream job for AI-specialists, the truth is that it is a challenging task that needs high-quality, relevant content.


In an era where video is king, brands and marketers need to find ways to surface timely and engaging video that resonates with consumers. Ad-based video is the future, and AI-generated video can help brands surface timely and engaging video that resonates with consumers. Let’s explore advanced AI-generated video, its potential use cases, and its limitations.