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How to create an AI video (2026): the full workflow from idea to published

How to create an AI video in 2026, start to finish: pick a format, write the prompt, generate footage, add voice and captions, then publish — the step-by-step.

Last verified · 2026-09-15 · by Moe Ameen

"Create an AI video" sounds like one action — type a prompt, get a video — but a video people actually watch is the output of a short workflow, not a single click. A text-to-video model hands you a raw clip, usually eight to thirty seconds, often without the exact captions, voice, aspect ratio, or branding a real post needs. That clip is the middle of the process; the work on either side of it is what turns it into content that ships.

This guide walks the whole thing in order: deciding which kind of AI video to make, writing the script and prompt, generating the footage, adding voice and captions, checking it before it goes out, and publishing it in the right format on each platform. It applies whether you're making a talking-head explainer, a cinematic generated clip, or a short cut from a long recording — the three main routes differ mainly at the generation step, and the rest of the workflow is shared. Do it once deliberately and you'll have a repeatable process instead of a one-off novelty.

The steps

  1. Decide which kind of AI video you are making. There are three main routes and they use different tools. (1) A generated clip — a text-to-video or image-to-video model (Veo, Kling, Seedance, Runway) makes net-new footage from a prompt; best for cinematic or product shots, but clips are short and you can't control exact wording. (2) An avatar/talking-head video — a tool like HeyGen renders a presenter delivering your script with a synthetic or cloned voice; best for explainers, updates, and ads where a consistent on-screen identity matters. (3) A clipped short — you start from footage you already have (a webinar, podcast, or long video) and cut a vertical short from it. Pick the route before you write anything, because it decides your script length and your tool.
  2. Write a tight script and a specific prompt. Decide the video in words before you spend a generation credit on pixels. Write a one-idea script with a real hook in the first line — an LLM is a good drafting partner here, but keep the point of view yours. Then turn the visual into a specific prompt: not "a cat running" but "a ginger tabby sprinting down a neon-lit alley at night, shallow depth of field, motion blur, handheld." For avatar video, the script is the voiceover verbatim, so tighten it to the exact words you want spoken. Fix the length and beats now so voice, captions, and footage line up later.
  3. Generate the footage. Run your chosen tool. For a generated clip, submit the prompt (and a reference image if the model supports image-to-video for more control), pick aspect ratio and duration, and generate — expect to iterate a few times, since first outputs rarely nail motion and framing. For avatar video, pick the presenter and voice and render from the script. For a clipped short, upload the long video and let the tool find and cut the strong moments. Generate a little more footage than you need; trimming down beats regenerating.
  4. Add voice, music, and lip-sync. If your generation step produced native audio, this shrinks to a review. If it didn't — common with clipping and some avatar workflows — assemble a voice (synthetic or cloned), add music that matches the pacing, and confirm lip-sync is tight. Keep the voice consistent from video to video: a narrator who sounds different every week reads as a content farm. Desynced or robotic audio breaks the illusion faster than an imperfect frame, so treat audio as a real stage, not an afterthought.
  5. Burn in captions and reframe to vertical. Most short-form is watched muted, so burned-in captions are non-negotiable — generate them from the audio and fix any wrong names or timing. Reframe to vertical 9:16 for Reels, Shorts, and TikTok, checking that the reframe keeps your subject centered rather than cropping them out. Add your branding — colors, logo, a lower-third or template — and cut the first three seconds tight for retention. This finishing pass is what separates a video that performs from a raw clip that gets buried.
  6. Review it before you publish. Run a quick quality check: watch it muted (do the captions carry it?), watch it with sound (is the audio synced and on-voice?), confirm the aspect ratio and safe zones for the target platform, verify any on-screen text and claims are correct, and decide whether it needs an AI-generated label. AI video is exactly where a small error — a garbled word, a wrong figure, an artifact — slips through, and it's far cheaper to catch it here than after it's live.
  7. Reformat, schedule, and publish per platform. A finished video still has to meet each platform's rules: aspect ratios, caption and description limits, hashtag conventions, and native-upload quirks differ across Instagram, TikTok, YouTube, LinkedIn, X, and the rest. Reformat the video and its copy per destination, then schedule it into your calendar so posting is a habit, not a scramble. One video is a demo; a channel is dozens of on-brand videos published consistently across every surface your audience uses.

Common gotchas

  • Publishing the raw model output. Unedited text-to-video looks like everyone else's unedited text-to-video, and platforms spent 2026 demoting exactly that homogeneous AI video. The differentiation is in the script, the captions, the voice, and the brand styling — not the model.
  • Skipping captions. Most short-form is watched with the sound off; a video without burned-in captions loses the majority of its audience in the first second.
  • Wrong aspect ratio. Generating in 16:9 and posting to a 9:16 feed either letterboxes the video or crops your subject out. Decide the aspect ratio before you generate.
  • Treating audio as an afterthought. Desynced or robotic voice breaks the illusion faster than a slightly imperfect frame — and a narrator whose voice drifts between videos reads as a content farm.
  • Expecting one clip to be a whole video. Frontier models still output short clips (commonly eight seconds, with the leading edge pushing toward fifteen to thirty in one pass by late 2026). Longer pieces mean stitching or an avatar/clip route.
  • Making one video and stopping. Generating is the fun, easy part; publishing on-brand video everywhere, every week, is the actual work. Build the workflow to repeat, or it stays a novelty.
Legal note

Several jurisdictions and platforms now require AI-generated or significantly AI-altered video to be labeled — the EU AI Act's transparency rules and platform policies on Instagram, TikTok, YouTube, and others among them — so check the disclosure requirements for where you publish. Separately, using a real person's face or voice (including a cloned voice) requires their consent, and generated footage can still infringe third-party trademarks or likenesses; don't publish an avatar or voice you don't have the rights to use.

Where Kompozy fits

The tutorial above is a stack of separate tools — a model to generate, something for voice, a captioner, a scheduler — and the friction is in the handoffs between them. Kompozy runs the whole thing as one click-path, because it's a full content generation and multi-platform publishing engine, not a single-stage video tool. In practice, you don't pick a generator and then wire up the rest: you pick a video format and Kompozy produces the finished, captioned, on-brand video end to end.

That format menu maps directly onto step 1's three routes. For an avatar/talking-head video, choose [Persona Shorts](/glossary/persona-shorts) — a HeyGen presenter plus auto-captions and optional B-roll — or Persona HeyGen for longer multi-scene pieces. For a branded on-screen look, choose [Persona Frames](/glossary/persona-frames), which composites the avatar as a movable layer inside a pixel-exact [HyperFrames](/glossary/hyperframes) template. For the clipping route, Kompozy cuts vertical shorts from your existing long-form footage. For lightweight formats there are Listicle Videos and Marketing Shorts. You give it one prompt; steps 2 through 5 — script, generation, voice, captions, reframing, and branding — happen inside a single render, governed by your [Persona Brief](/glossary/persona-brief) so the voice and angle stay consistently yours across every video instead of resetting each session.

Then step 7, the one that turns AI video from a novelty into a habit, is [Autopilot](/glossary/autopilot): it reformats each finished video per platform and fans it across eight social platforms plus blog and email from one queue, behind a per-post review gate (step 6) where you approve or rewrite before anything ships. Pricing is credit-based: Starter ($99/mo for 5,500 credits) covers a solo creator or small brand's video cadence; Pro ($299/mo for 18,000 credits) suits an agency running video for several clients across platforms; Enterprise is custom. The point isn't that Kompozy beats a dedicated frontier model on a single cinematic shot — it's that for the real job, publishing on-brand video everywhere every week, it removes the seams that make the multi-tool version collapse.

Frequently asked questions

How long does it take to create an AI video?

A short social video can go from idea to published in well under an hour once you have a workflow — a few minutes to script, a few generation passes, a finishing pass for captions and branding, and a schedule step. The first one takes longer because you're learning the tools; the value is in making the process repeatable so the tenth video takes a fraction of the time of the first.

Do I need one tool or several to make an AI video?

You can assemble a best-of-breed stack — a text-to-video model for shots, a separate voice tool, a separate captioner, and a scheduler — which gives maximum control but leaves you managing the handoffs between them. Or you can use one engine that collapses script, generation, captions, and multi-platform publishing into a single workflow. Solo creators and small teams usually want the second, because their bottleneck is the seams and the volume, not model quality.

How do I make an AI video that doesn't look generic?

Don't stop at generation. A distinctive script and angle, a consistent persona or voice across videos, real burned-in captions and tight pacing, and a recognizable brand style are what separate your video from the flood of raw model output. The workflow around the model — not the model itself — is where a video stops looking like everyone else's AI video.

Do I have to label an AI-generated video?

Increasingly, yes. Platform policies and laws like the EU AI Act now require disclosure when video is AI-generated or materially AI-altered, and the exact rule depends on where you publish. When in doubt, label it — a clear disclosure costs you nothing and protects against demonetization or removal, whereas an undisclosed AI video that gets flagged can cost you the account's standing.

Can I create an AI video for free?

Many generators have free tiers, but they typically cap resolution, length, and monthly generations and add watermarks, and they only cover the generation stage — you'd still assemble voice, captions, and publishing separately. Free is fine for testing whether AI video fits your workflow; a sustained, on-brand publishing habit across platforms usually needs a paid plan that covers the whole pipeline, not just the clip.

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