AI video terms every business owner should know, grouped by the decision they affect

By Ranjit Bhinge, founder of Blur Studio · Updated November 4, 2026 · 10 min read

Short answer: Text to video means a tool makes a short clip from a written description. Image to video means it animates a picture you supply, which is usually the safer way to work with a product. The other terms that matter most to an owner are credits (what you spend), artifacts (visible mistakes), lip sync (matching mouths to speech) and synthetic media labels (what you may have to disclose). Below, each term sits under the decision it affects.

Every AI video tool talks in its own shorthand, and the words decide what you pay, what you get and what you must tell your audience.

I'm Ranjit, and I run Blur Studio: 15+ years building software, 120 apps taken live, and clients who have gone on to raise $10M+. I build AI systems and processes that help businesses do a lot more with a lot less time. I also work differently from most of what else is out there, more on that further down this page. Say hello.

Most AI video glossaries are alphabetical lists written by tool sellers. They are hard to use when you are trying to decide something. This one is grouped by decision: what you feed the tool, what you get and what can go wrong, how it handles sound, what it costs, and what you must disclose. Each term has a plain definition and a business example.

Sellers define some terms generously, such as "perfect" lip sync, "unlimited" use or "same seed, same result". The real rule is in the licence and the plan page, not in a glossary. It is information, not legal advice.

Group 1: What you feed the tool

These terms decide what goes in. Better input is the cheapest way to get better output.

Prompt: The written instruction you give a tool. Example: "A slow push-in on a ceramic coffee mug on a wooden table, morning light." Be specific about subject, setting, camera and light. Vague prompts get generic clips.
Negative prompt: A list of things you want left out, such as "text, extra fingers, blur". Not every tool offers one, and models differ in how well they obey it.
Text to video: The tool makes a clip from words alone. Good for ideas, backgrounds and mood. Weak when you need your exact product, logo or room, because the tool invents the details.
Image to video: The tool animates a still image you provide, with a motion prompt. For a business this is usually safer, because you control the starting picture, such as your own product photo. Watch out: the tool can still change a label, shape or colour a few seconds in. Check the last frame, not just the first. See turning product photos into short videos without warping labels.
Video to video: The tool changes an existing clip, for example restyling it or swapping a character, while keeping the motion. Useful when you have real footage and want a different look. You still need the rights to the source footage.
Reference image: A picture you give the tool as a guide for a face, style or product, in addition to the prompt. If it shows a real person, you need that person's consent.
Start frame and end frame: Two images that mark where a clip begins and ends, and the tool fills in the motion between them. Example: a shop door closed, then open. Handy for controlling a short sequence. Not every tool offers it.

Group 2: What you get, and what goes wrong

These terms describe quality and the mistakes to look for. They map to the symptoms you will see. For a longer review routine, see my quality check for AI video. For how the technology produces them, see how AI video generation works.

Diffusion model: The common type of AI that makes images and video by starting from random noise and refining it step by step toward your prompt. You do not need this term to use a tool. It helps to know why every run gives a different result.
Latent space: A compressed, behind-the-scenes version of the picture that many of these models work in, instead of working on full-size pixels. Think of it as the model's rough sketch pad: it does the hard work there, then turns the result back into a normal image or video. You never see it or set it. It is why some tools are quicker than you would expect, and it is a term you will meet in vendor explanations, not in a settings menu.
Temporal consistency: Whether things stay the same from one moment to the next in a clip. When it fails, a face changes shape, a logo wobbles or a hand grows a finger. Test any tool by playing the clip at full length, not as a thumbnail.
Artifact: A visible mistake left by the generator: warped hands, melting objects, garbled text, flicker. Small text and logos are especially prone, so do not rely on generated signs, prices or packaging text.
Hallucination: The tool invents something you did not ask for, such as a feature on a product or a detail on a building. For property and product work, this is a misleading-advertising risk. Always compare with the real thing.
Visual drift: A look that slowly changes over a clip or across several clips, such as a character's hair colour shifting. This is why long videos are usually stitched from several short clips.
Character consistency: Keeping the same person, mascot or product looking the same across many clips. Tools handle it by different methods, and none is perfect. Plan to check every shot.
Uncanny valley: The uneasy feeling when a person looks nearly real but slightly wrong. For brand video, a stylised character often feels better than a nearly-real one.
Upscaling: Making a clip or image sharper or bigger, for example from 720p to 4K. It adds detail by estimate and cannot recover true detail, and it can add its own errors. See upscaling AI video.

Group 3: Control words and under-the-hood terms

Seed: A number that starts the random process. Reusing the same seed and settings often gives a similar result, which helps when you want small tweaks. Vendor glossaries sometimes say it gives an identical clip every time. That is overstated: results can differ after a model update or a changed setting, so save the clips you approve and do not count on regenerating them.
CFG (guidance scale): Short for classifier-free guidance. A setting in some tools that decides how strictly the model follows your prompt. A higher value sticks closer to your words but can make the result stiff or over-processed. A lower value gives the model more freedom. Many consumer tools hide it, and sensible values differ from model to model, so I give no number here. If a tool shows it, change it a little at a time.
LoRA and fine-tuning: Fine-tuning means giving an existing model extra training so it handles one thing better. A LoRA (short for low-rank adaptation) is a small add-on file made that way, often from a handful of example images, to teach a model a particular style, product or character without retraining the whole model. Useful if you need the same look every time. Check who owns the training images, and if they show a real person, you need that person's written consent. How many examples you need depends on the tool, so treat any fixed number from a seller as a guide only.
Aspect ratio: The shape of the frame: 16:9 for YouTube and websites, 9:16 for Reels, Shorts and TikTok, 1:1 or 4:5 for feeds. Choose it before you generate. Cropping later can cut off the part you care about.
Resolution: How many pixels the video has, such as 720p, 1080p or 4K. Higher usually costs more and can take longer. Match it to where the video will play.
Duration: How long one generated clip is. Clips are usually seconds, not minutes, and the limit varies by tool and model. An ad is normally stitched from several clips.
Camera control and motion control: Settings or prompts that steer how the camera moves (push in, pan) or how a subject moves, sometimes by copying motion from a reference video. Useful for repeatable looks. The quality varies by model.

Group 4: Sound and speech

Native audio: Sound generated together with the picture, such as ambience, effects or speech. Some current models offer it. Google says its Veo model (Google's AI video model) can generate dialogue and sound effects, and also says natural speech and sync remain an area of active development. Always listen with headphones before publishing.
Text to speech: Software reading a script aloud in a synthetic voice. Check the voice licence for commercial use.
Voice cloning: Making a synthetic copy of a real person's voice from recordings. Use only with the speaker's clear written consent, and read the tool's terms. A cloned voice of a real person may also need a disclosure on some platforms. See my consent checklist.
Lip sync: Matching a face's mouth movements to speech. It is used for dubbing and talking avatars. Sellers sometimes call it perfect or real time. Treat that as marketing: check teeth, side angles, fast speech and non-English words yourself. See best AI lip sync and talking photo tools.
Dubbing: Replacing the spoken language of a video with another, sometimes in the original speaker's voice. Good for first versions. Have a native speaker check anything customers will rely on.
AI avatar: A synthetic presenter that reads your script on screen. It may be a stock character or a consented copy of a real person.

Group 5: What it costs

Credit: The points a platform sells and spends each time you generate. The number spent depends on the model, the length, the resolution and the feature. Higgsfield (a web platform offering many AI image and video models) is one example: its credit costs for some features show on the Generate button and not in a table. Read the plan page, and see how to spend credits wisely.
Allowance: The credits or generations included in a plan each period. Some plans let unused credits expire at the end of the billing period, and others carry them over. Ask which.
Retry rate: How many attempts you need for one usable clip. This is not a standard industry term, but it is the one that decides your real cost. If you need four tries per good clip, your cost per clip is four times the price per attempt.
Cost per approved result: Total spend divided by the clips you actually used. Track this for a month before comparing tools.
Watermark: A visible mark on output, common on free plans. A visible watermark is not the same as an invisible marker. Check if a free plan's output may be used in ads. See what free AI video generators really give you.
Commercial licence: Permission to use outputs in business, such as in ads. Words like "unlimited commercial licence" in marketing can hide limits on plan, on use or on third-party rights (a face, a brand, a song). Read the terms, not the glossary. See AI video in paid ads: a rights checklist.

Group 6: What you must disclose

Synthetic media: Any image, audio or video that was made or changed by AI. Some platforms and laws require a label when it looks realistic. The rules differ by platform and place. See the platform labelling rules.
Deepfake: Synthetic media that makes a real person appear to say or do something they did not, usually without their consent. An AI avatar made with consent is not the same thing in intent, but a real person's face or voice still needs written consent whatever the tool calls it.
Watermark (invisible): A hidden signal in the file that says it was AI-made. SynthID is Google DeepMind's invisible watermark, which Google says it adds to content made with its own AI tools, including Veo video. Google describes it as designed to survive cropping, filters, frame-rate changes and compression, and offers a SynthID Detector to check files. That is a design goal, not a guarantee, and it only covers content from participating tools, so a file with no SynthID may still be AI-made. It is a signal for detection tools, not a promise that every viewer will see a label. For what viewers can spot by eye, read how to tell if a video is AI-generated.
Content Credentials and C2PA: C2PA (the Coalition for Content Provenance and Authenticity) is the industry group behind an open standard called Content Credentials. C2PA describes them as working like a nutrition label for a file: where it came from and how it was edited. The label travels as data attached to the file, which can be lost when a file is re-saved, exported or uploaded to some platforms, so do not assume it survives. Some platforms, such as TikTok and YouTube, say they may add an AI label automatically when a file carries this data. See why you should not strip provenance marks.

Which terms to ask a vendor about before you pay

When you compare tools, these are the questions that matter, in the order I would ask them:

What exactly does one credit buy, and how many credits does a clip like mine cost, at my resolution and length?
Do unused credits expire, and when?
Is output on this plan cleared for commercial use, and is there a watermark?
Does the tool store or train on what I upload? (Ask in writing for client work.)
What happens to a real person's face or voice that I upload? Who holds the consent?
Does the output carry any hidden marker, and does the platform I publish on need a label?
What is the maximum clip length, and do I need to stitch clips together?

How I'd approach this

You do not need to memorise 30 terms. I would learn the first group, because it decides what you feed the tool, then keep the money and disclosure groups open as a checklist when you pick a plan and when you publish. Start with image to video from your own photo, save every clip you approve, and track the cost per approved result for one month. If you want a repeatable setup for a team, such as a shared prompt library, an approval step and a place to keep approved clips, Blur Studio builds that kind of workflow; see what I offer businesses.

Questions people ask

What does text to video mean?

It means the tool makes a short video clip from a written description alone. It is good for mood and ideas, and weak when you need your exact product or location, since the tool invents the details.

What does image to video mean?

The tool animates a picture you supply, guided by a short motion prompt. It gives you more control than text alone, but check the whole clip because labels and shapes can change as it plays. See turning product photos into videos.

What is lip sync?

Lip sync matches a face's mouth movements to spoken audio. It is used for dubbing and talking avatars. Quality varies by tool, so check close-ups and side angles before you publish.

What is a seed?

A seed is a number that starts the random part of generation. Using the same seed and settings often gives a similar result, but not always an identical one, especially after a model update. Save approved clips rather than relying on regeneration.

What are credits in AI video?

Credits are the points a platform spends each time you generate. Cost depends on the model, length, resolution and feature. Read the plan page and track your cost per approved clip. See how to spend credits wisely.

What is the uncanny valley?

It is the uneasy feeling when a person looks almost real but slightly off. For a brand, a stylised character often works better than a nearly-real human.

What is a deepfake?

A deepfake is synthetic media that shows a real person saying or doing something they did not, usually without consent. Using a real person's face or voice always needs their written consent, whatever the tool calls the feature.

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