What Is AI Video Generation?

AI video tools are now part of many marketing teams' production, but the label covers very different software. This guide explains the category plainly, then shows which form fits which job, what to prepare and how to judge a first pilot.

This applies to marketing, training and sales video where a synthetic or generated shot is acceptable to the audience. It is not a fit for footage that must show real events, real customers or exact product behaviour.

What Is AI Video Generation?

AI video generation is the use of machine-learning models to produce new video from a text prompt, an image, a script or existing footage, and 63% of video marketers in Wyzowl's 2026 survey of 266 respondents had used AI video tools to help create or edit marketing videos.

That figure was 51% in Wyzowl's 2025 edition, so use is spreading quickly among teams that already make video. The practical point is that "AI video" is no longer one product type. Under the umbrella of AI video generation sit tools that do quite different jobs.

This post uses three forms throughout:

• Generative scenes. The model invents a shot from a prompt or a reference image.
• Avatar presentations. A synthetic presenter, stock or cloned from a real person, delivers your script.
• Editing assistance. The model changes footage you already own from a written instruction.

Each form takes different inputs, carries different risks and suits different marketing jobs. Choosing well starts with knowing which of the three a task needs, before comparing any tools.

How Does AI Video Generation Work?

Most AI video generators are diffusion models that refine random noise into frames matching a prompt, and OpenAI describes Sora as a diffusion transformer that turns compressed video into spacetime patches it processes as tokens, much as a language model handles words. Working across frames at once helps the model keep motion coherent.

Diffusion In Plain Terms

A diffusion model learns to remove noise. At generation time it starts from static and refines it step by step until the frames match the prompt. The prompt steers each step, which is why wording, reference images and style instructions change the result so much.

Spacetime Patches

Video adds time to the problem. OpenAI's Sora report describes compressing a video and cutting it into spacetime patches, small pieces that each span part of the frame and a stretch of time. The transformer treats those patches as a sequence, so it reasons about how an object moves, not only how it looks in one frame.

The Three Input Routes

Most tools accept one of three starting points:

• Text-to-video. A written prompt describes the shot, and the model invents everything in it.
• Image-to-video. A still image fixes the look, such as a product shot or a brand character, and the model animates it.
• Footage-to-footage. An existing clip goes in with an instruction, and the model changes part of it while keeping the rest.

How Avatar Systems Differ

Avatar tools do not invent a whole scene. They animate a face and a voice to a script, using a stock presenter, a cloned person or a still photo. The scene stays simple and the variable is the words, which is why avatar tools handle scripts, slides and translation rather than open-ended prompts.

What Are The Types Of AI Video Generation?

AI video generation comes in three working forms for marketing teams. Generative scenes invent footage from a prompt, avatar presentations put a synthetic presenter in front of a script, and editing assistance changes footage you already have from a written instruction. Each form suits a different marketing job.

The table maps each form to what you give it and what comes back:

Generative scenes fit ad shots, social cutaways, b-roll and concept visuals, where no one needs the footage to show a real place or person.

Avatar presentations fit training, onboarding, product explainers, internal comms and localisation, where the message is the script and the same video is needed in several languages.

Editing assistance fits footage you already own. It removes an object, restyles a scene or produces colour variants of a product shot without a reshoot.

Script-to-video assemblers such as InVideo blend the types. They storyboard a script shot by shot and fill each scene with generated media from several models, then let you edit the result on a timeline.

The next three sections take each form in turn, with tools as worked examples. Each example covers what the tool does for that form, the input it takes, the rule or limit that shapes use and where it fits best.

What Are Generative Scenes?

A generative scene is a shot an AI model invents from a text prompt or reference image, and tools such as Pika cap a single generation at a 30-second multi-shot video, so longer pieces are built shot by shot. The team's work becomes keeping characters, light and style consistent across those shots.

Generative scenes suit short ad shots, social clips, b-roll and concept visuals. Readers ready to compare the options can see our guide to AI video generators for marketing teams.

Runway

What it does: Runway runs a cloud workspace to generate and edit video, images and audio, with Gen-4.5 as its current video model.

Input: Gen-4.5 takes text prompts. Runway says it is bringing other control modes, such as image-to-video, to the model, so treat those as announced.

Rule or limit: Runway's own Gen-4.5 announcement lists causal reasoning, object permanence and success bias as known weaknesses, so shots with cause-and-effect action need review.

Best fit: Teams that want generation and later editing of the same shots in one workspace, for concept visuals and b-roll.

Pika

What it does: Pika Video Studio generates anything from a short clip to a 30-second multi-shot video, and offers third-party models such as Seedance 2.5 alongside Pika 2.5.

Input: Text prompts and images, plus a reusable character from Character Studio, clip extension and Pika Soundtrack for music, ambience and foley.

Rule or limit: Pika's terms limit outputs to personal, noncommercial use unless the subscription plan expressly permits commercial use, and they bar deepfakes of any person without prior consent.

Best fit: Social clips that reuse one character and need sound, on a plan whose terms cover commercial use.

InVideo

What it does: InVideo turns a script or idea into a shot-by-shot storyboard and gives access to third-party video models, including Google Veo 3.1, Sora 2 and Kling AI.

Input: A script or a rough idea, with an AI co-writer to draft one, plus voice cloning and text-to-speech.

Rule or limit: Each generation draws credits by the model used, and InVideo's Lite, Pro and Ultra modes cost progressively more per generation.

Best fit: Teams that want one storyboard while trying several third-party models on the same brief.

What Are Avatar Presentations?

An avatar presentation is a video in which an AI-generated presenter reads your script on screen, and Synthesia will only build a custom avatar of a real person after that person records an on-camera consent video. Synthesia also offers hundreds of stock avatars for videos that do not need a real person on screen.

Avatar presentations suit training, onboarding, product explainers, internal comms and localisation. For a side-by-side view, see our comparison of AI avatar video tools.

Synthesia

What it does: Synthesia turns a prompt, a link or a file such as a PowerPoint or document into presenter-led video, with hundreds of stock avatars and voiceovers in 140+ languages. Its dubbing keeps the original speaker's voice and accent, with optional lip sync and a glossary for brand terms.

Input: A personal avatar is recorded on a webcam or smartphone, or from 2-3 minutes of uploaded footage, plus a consent video. Personal avatar voices are cloned and translated into 29 languages.

Rule or limit: A personal avatar is ready in about 1 business day, and studio avatars take 1-5 business days with your own footage. Synthesia creates no avatar of anyone without explicit consent, politicians and celebrities included.

Best fit: Training modules and explainers that need the same presenter in many languages.

D-ID

What it does: D-ID Creative Reality Studio turns text, audio or a still image into a talking avatar video. Its Video Translate feature clones the speaker's voice and adapts lip movements into 40+ languages.

Input: A script or audio track, plus a face from pre-made avatars, an uploaded photo (JPEG or PNG, up to 10 MB) or a generated portrait.

Rule or limit: Videos are limited to 5 minutes, so longer training content is split into modules.

Best fit: Quick talking-head clips from a photo, translated short videos, and teams that want Visual AI Agents, D-ID's real-time conversational avatars that can carry out tasks and trigger workflows.

Consent Is The Gating Input

Consent is not a formality in this form. D-ID's ethics pledge commits it to work to ensure customers obtain third-party consent where required and that uses are clearly marked as synthetic. Synthesia says it builds moderation into the point of creation and treats consent as core to preventing deepfakes and impersonation.

How Does AI Editing Assistance Work?

AI editing assistance changes video you already own from a written instruction, and Runway's Aleph 2.0 can add or remove objects, restyle a scene or recolour a product across clips of up to 30 seconds at 1080p. The footage, people and rights are already yours, which makes it the lowest-risk start.

The difference from generation matters. Generating footage and producing presenter video are different jobs, as our Runway vs HeyGen comparison shows, and editing assistance sits closer to traditional post-production than either.

Runway Aleph 2.0

What it does: Aleph 2.0 edits existing video from a plain-language description. It adds or removes objects, restyles footage, changes a product's colour, hairstyle or clothing while keeping background and lighting, and tightens framing.

Input: An existing clip and a written instruction, or one edited frame that Aleph 2.0 carries through the whole video.

Rule or limit: Clips run up to 30 seconds and up to 1080p, so longer edits are cut into segments.

Best fit: Product colour variants, object removal and restyled versions of shots you already filmed.

InVideo For Editing Assistance

What it does: InVideo lets you edit by describing the change in plain words on a multitrack timeline.

Input: A project on the timeline and a written instruction for the change.

Rule or limit: Each agent response can involve several actions that each draw credits, so set a per-project credit limit and switch the agent to ask before it generates video.

Best fit: Marketers who want to revise a full cut by description, without learning a traditional editor.

Which Type Of AI Video Generation Should You Use?

Choose the type of AI video generation by the job, not the tool. Use avatar presentations for scripted explainers that need many languages, generative scenes for short ad and social shots, and editing assistance when you already own the footage. A script-to-video tool suits a fast first draft from a brief.

Apply one rule per situation:

Two checks sit on top of the table. If the footage must show real people, real events or exact product behaviour, film it. If a cloned person appears, the consent recording comes before any script work.

Agencies running client work face extra questions on client separation and output rights, covered in our guide to AI video tools for agencies.

An Illustrative Scenario

The following scenario is illustrative, not a case study. Its assumptions are:

• A B2B SaaS team has a final 3-minute onboarding script in English.
• It needs four language versions of that script, and all four are languages its avatar tool supports.
• The presenter is either a stock avatar or an employee who records a consent video.
• A product launch ad needs a few short b-roll shots, each under 30 seconds, with no real customers on screen.

Under those assumptions, the onboarding video is an avatar job. A 3-minute script fits inside D-ID's 5-minute limit, and a Synthesia personal avatar is ready in about 1 business day after the consent video. Dubbing then produces the other language versions from one source.

The launch ad is a generative scenes job. The team writes one prompt per shot, generates in Runway or Pika, and keeps the brand character consistent with a reference image or a reusable character. If the team already has product footage, editing assistance can produce colour variants instead of generating new shots.

The team should confirm before it starts that its plan permits commercial use of outputs, and it should set a credit limit for the ad shots.

What Inputs Does AI Video Generation Need?

Every AI video project needs four inputs prepared before generation starts. They are a finished script, brand references, written consent from anyone whose face or voice is cloned, and a credit budget, because tools such as InVideo charge credits by model and quality mode.

Gather these before opening any tool:

• A finished script or creative brief, signed off before generation
• Brand assets and reference images for look, colour and characters
• A consent recording from anyone whose avatar or voice is cloned
• Recording conditions for a personal avatar, such as light, framing and a quiet room
• Source footage you own, for any editing assistance
• A per-project credit limit and a rule for who approves video generations
• A check that the plan's terms permit commercial use of outputs

Budget Credits Before You Generate

Credit meters hide the real cost of AI video. InVideo's help centre explains that one agent response can trigger reasoning, image generation, video clips and voice, each drawing credits by the model used. Its Lite, Pro and Ultra modes cost progressively more per generation, with Ultra adding 4K video.

InVideo shows usage per message and per project, lets you set a credit limit per project and can be switched to ask before it generates videos. Turn both controls on for a pilot, so a long chain of retries cannot drain the month's credits.

Watch What You Upload

What you upload may be licensed back to the vendor.

Is AI-Generated Video Legal To Use Commercially?

AI-generated video can usually be used commercially under a plan whose terms permit it, but the US Copyright Office says prompts alone do not make an output copyrightable, so a team may not own generated footage the way it assumes. In the EU, deepfakes must also be disclosed as artificially generated.

Copyright Of The Output

The US Copyright Office's 2025 report on copyrightability says AI output is protected only where a human author has determined enough of its expressive elements. Protection can cover human-authored material visible in the output and creative arrangements or modifications a human makes. Using AI to assist does not bar copyright.

For a marketing team, that means the edit, the sequence and the script are the protectable parts. A single generated shot from a prompt may not be.

The Licence From The Vendor

Commercial use can depend on the plan. Pika's terms limit outputs to personal, noncommercial use unless the subscription plan expressly permits commercial use. Pika also says outputs might not qualify for copyright. Read the output clause of any tool's terms before an ad goes live.

Likeness And Labelling

The EU AI Act's Article 50 requires deployers using AI to create deepfakes to disclose that the content has been artificially generated or manipulated. Providers must mark outputs in a machine-readable format so they are detectable as AI-generated. These obligations apply from 2 August 2026.

A deepfake under the Act is AI-generated or manipulated content that resembles real persons, objects, places or events and would falsely appear authentic. An avatar of a real employee can fall inside that definition.

This section is general information, not legal advice.

How Do You Measure AI Video Success?

Measure an AI video pilot against the video it replaces. Track hours and credits per finished video, language versions shipped and the outcome metric the video already served, because video ROI is not automatic even before AI is added. Set each measure before the pilot starts so results can be compared.

Wyzowl's 2026 survey found 82% of video marketers say video gives them a good ROI, down from 93% in 2025. Adding AI does not fix a video that was not working, so judge the pilot on cost and outcome together.

Any target you set for these measures is an assumption until the pilot runs, so record it as one. InVideo, for example, shows credit usage per project, which makes the cost line easy to fill.

What Are The Limitations Of AI Video Generation?

AI video models still get cause and effect wrong. Runway says its Gen-4.5 model can show a door opening before its handle is pressed or let an object vanish after it passes behind another one, and OpenAI's Sora report says Sora does not accurately model the physics of basic interactions such as glass shattering.

The limits vendors and model developers admit fall into four groups:

• Physics and causality. Runway lists causal reasoning, object permanence and success bias, where actions succeed more often than they would in reality.
• Short single generations. Pika and Runway's Aleph 2.0 work in clips of up to 30 seconds, and D-ID caps avatar videos at 5 minutes.
• Consistency across shots. A longer video is a sequence of generations, so characters, light and style drift unless the team controls them with references.
• Avatar realism and consent. A custom avatar needs the person's consent, and Synthesia refuses avatars of anyone without it.

Frequently Asked Questions

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