The emergence of generative AI saw a rise in AI-generated content online, particularly AI-generated videos and images.
One consequence of this is growing mistrust among the public about any and all content they encounter online. When we see a suspicious piece of content, the first thing we think of is: is this AI?
But in a continuously modernizing world, it’s becoming more and more impossible not to follow suit in the popular usage of AI, especially if you’re a company or institution looking to scale content creation.
With all that being said, here’s the piercing question: can you build trust and authenticity with AI Video?
The short answer: yes and no.
Let’s begin with the obvious: no, you can’t build trust and authenticity using AI video alone.
There are certain qualities to AI video that makes it almost instantly distinguishable that it is made by AI, and is therefore untrustworthy.
But, contrary to popular belief, there is actually a way to build trust and authenticity with AI.
How? By adding a human touch.
This means that, as content creators, we shouldn’t fully rely on AI to generate the content we put out.
We must also be involved in the process—by writing the content ourselves before feeding it into an AI generator or editing the end product before putting it out, among others.
To understand this completely, we must first look at how AI video works, its use cases, and how the general public perceives it.
What is AI Video?
The 2025 Artificial Intelligence Index Report defines AI Video, also known as text-to-video model, as a machine-learning model that uses text input description to create a video output relevant to the inputted text.
Simply put: these models generate videos based on the text you provide describing the content you’d like to see.
For example, if you’d like to see goblins working in a gold mine, you’d put that exact description into the AI generator and, within a matter of minutes, you’d have your video of these silly creatures digging gold from the earth.
But how do these video models do this in as short as a couple of minutes?
To further understand AI Video, we also have to take a closer look at how it works.
How it works
The selling point of AI Video—and generative AI, in general—is that it can make content creation quicker than the speed of light.
Well, not literally, but it does generate content at a superhuman speed.
Taking the previous example, an animator would simply not be able to animate a detailed, fully rendered video of goblins in a gold mine in a couple of minutes.
AI can do this because there is already a massive amount of content on the internet that it can train itself with. This is the so-called “training data” that you may have heard of.
In other words, anything posted online can be used by AI to generate content. Those goblins? They’re derived from already existing content on the internet that AI “trained” itself with.
This is why generative AI can be perceived in a bad light—derivative content, after all, can mean stolen content.
The result of this is a number of heated debates and controversies on the ethics and the “correct” use of AI, which begs the question: can we ever trust AI if it’s just stolen content?
When is AI content considered stolen content?
Now that we know that generative AI is derived from already existing content on the internet, we must also look at how it can be perceived as stolen.
In an article titled Theft is not fair use, David Carson delves deep into how AI gathers data and basically defies the laws of intellectual property and copyright.
He writes, “They need the data, so they take it and claim it’s transformative fair use. It’s not; it’s theft.”
So, is there a way to use generative AI without unintentionally stealing content from individual artists?
Using AI responsibly
Because the AI boom is fairly recent, it’s still heavily unregulated. So, as individuals, we should consider it our personal obligation to use it responsibly.
The best way to use AI ethically and responsibly is to make sure you have the consent of the artist/creator of the content you’re feeding into it.
Regardless if it’s for research or simply for curiosity’s sake, consent is key!
We must also note that however you use generative AI, the content it generates can’t be considered original—this means you can’t sell it or even share it and claim it as your own.
These are all individual considerations we should make when we’re using generative AI. But how can companies and institutions use AI in a way that still fosters trust and authenticity?
Let’s look at the use cases of generative AI, particularly AI video, in two different bodies: corporations and universities.
Use cases
There are many use cases to generative AI, particularly AI Video Models. Many institutions, from large corporations to universities, use generative AI to improve efficiency and streamline workflows.
Below, we’re going to look at how these two different institutions use AI Video Models.
How corporations use it
If you work in a corporate setting, you’re probably familiar with the fast-paced environment it operates under.
This is why AI is notoriously used by corporations to automate previously manual work. By doing this, they’re able to make work more efficient and reduce costs.
AI Video models, in particular, are used in large corporations for training, onboarding, and presenting data.
1. Training
Different people have different learning styles. Some of us learn by reading, some by hearing, and some from a combination of both.
To provide more engaging training materials, corporations use AI Video. AI Video models help them produce this type of content.
For example, they might use AI Avatars to create a video of a person teaching existing training materials.
They can even use custom AI avatars to generate a video of a real person from the company presenting these materials.
The same can also be applied to employee onboarding.
2. Employee Onboarding
The onboarding process can be particularly time consuming and tedious. For this, corporations can save time and money with the help of AI videos.
Custom AI avatars are also typically used to make the onboarding process less tedious and more engaging.
Using existing onboarding material, a video of a real person from the corporation can be generated presenting this material.
And because onboarding materials are constantly being updated, AI Video can be particularly useful as it skips the process of filming (which involves setting up and getting together a whole crew), which can be time consuming and costly.
3. Presenting data
If you’ve ever presented data in a meeting, you’re probably familiar with how difficult it is to keep your audience engaged.
AI Video can be used to make data presentations more engaging, whether that’s through a dynamic presentation or an AI avatar.
This is how AI Video can be particularly helpful when presenting data, especially large amounts of it.
4. Creating ads and promotional videos
Creating advertisements can also be time consuming and costly.
This is where AI Video models come in: they help corporations skip the process of setting up a crew and filming, making content creation efficient and cost effective.
AI Video tools help you create advertisements and promotional videos within the blink of an eye.
Using just a simple description, you’ll have your video in no time—saving you time and costs from preparation, filming, and editing.
How universities use it
1. From written text to engaging videos
Reading is not everybody’s learning style. However, our educational system is set up in a way that requires heavy reading.
Indiana University hacked this problem by using AI video to turn their static case studies into video learning modules.
Using AI Video, they were able to turn static content into multimedia assets, translate it into different languages, and keep it up-to-date without having to reshoot.
2. Onboarding and training materials
In another case, Bolton College used AI Video to efficiently create onboarding and training materials for its staff.
Within the span of a year, they were able to create 400 training and onboarding videos and effectively reduced their production time by 80%.
What made this work is how simple the process was. Staff didn’t need expertise; they simply put the description in their AI video tool, selected an avatar, and let it do the rest.
As we can see, there are many different ways to use AI responsibly. However, public opinion often still sees AI in a negative light, and understandably so.
So, to build trust and authenticity with AI video, it’s imperative for us to understand how the public generally perceives it.
Public opinion and the concept of ‘AI slop’
One consequence of the ‘AI boom’ is the emergence of the so-called ‘AI slop’. These are pieces of low-quality media made with an ‘inherent lack of effort’ and ‘generated at an overwhelming volume.’
‘AI Slop’ ranges from cats swimming in a slime pool to a statue of Jesus underwater with shrimps for arms and legs.
Its random and bizarre nature can be quite jarring when you stumble upon it on your feed. In a way, it’s similar to spam; it’s low-quality content that basically pollutes the internet.
AI slop is one of the biggest reasons why it’s difficult to build trust with AI videos. If it can be used to generate these types of content, how could you possibly use it and still stay credible?
Remaining credible
With the proliferation of generative AI tools, it’s virtually impossible to not use AI in today’s day and age.
However, you can still remain credible while using AI video—but only if it’s used responsibly and with ethical considerations.
Whether you’re an individual, a corporation, or an institution, stay off of AI slop and add a human touchto your content.
When building training materials, for example, make sure these materials are original content, and that the knowledge and skills you’re teaching are based on facts, not on misinformation.
The same goes for writing scripts for AI videos—maybe you can let AI help you write a draft, but the end product should always undergo human editing.
So, if you want to stand out from the rest, make sure to use AI responsibly and ethically!
