AI Video Generation Trends 2026: What the Data Shows

AI video generation trends 2026 at a glance

• Kling is the model people are searching for now: 'kling ai image to video' (1,900 searches a month, US) hit its 12-month peak in the most recent month of the index, and 'kling vs veo 3' did the same (Semrush, retrieved 2026-09-05).
• Sora interest spiked once and fell: 'sora 2 prompts' (880 a month) peaked in month five of the window and sat at 0.19 of that peak in the latest month; OpenAI has scheduled the Sora 2 models and Videos API for shutdown on 2026-09-24 (OpenAI deprecations page).
• Veo prompt searches are in decline: 'veo 3 prompts' (720 a month) peaked in the first month of the window and read 0.01 in the last; comparison searches ('sora 2 vs veo 3') followed the Sora curve.
• Formats out-search models: the top template keywords in LazyKiwi's demand file are camera moves and photo looks, led by 'dolly zoom' at 5,400 a month and 'mirror selfie' at 4,400, well above any single model query in our basket.
• The market context is disruption, not maturity: HubSpot's 2026 report has 61% of marketers saying marketing faces its biggest disruption in 20 years because of AI, and Stanford's 2026 AI Index frames a widening gap between what AI can do and how prepared institutions are to manage it.

A sixth finding comes from our own logs rather than search: across LazyKiwi's workbench data for August 2026, image tools were the most used feature (57 external users ran image template or tool generations against 17 for video templates), raw text-to-video had no external use in the window, and GPT Image 2 sat behind 127 of 181 external generations. People arrive for a finished format, not a prompt box.

Two caveats before the tables. Search interest measures curiosity, not usage, so a model can lose search share while gaining paying users. And our basket is US-only and skewed to English keywords, which undercounts the Chinese-language interest around Kling, Seedance and Hailuo. Read the rows as directional.

Three inputs, each dated. First, a fixed basket of model-name keywords pulled from the US database of Semrush (2026) on 2026-09-05, with monthly volume, keyword difficulty and the Trends column. Second, LazyKiwi's template-demand file, a list of the primary keyword, US monthly volume and keyword difficulty behind each template page, pulled on 2026-09-04 and used to order the templates hub. Third, external reports and vendor pages opened on 2026-09-06, cited inline where a figure is used.

What does the Semrush trend index mean?

Semrush's Trends field holds up to twelve monthly values for the year before retrieval, scaled so the busiest month equals 1.00 and every other month is a fraction of it. A keyword that reads 0.00 for four months and then 1.00 did not exist in search before month five; a keyword that reads 1.00 first and 0.01 last has lost almost all of its interest. Newer keywords carry fewer than twelve values, which is why our head term shows five: 0.07, 0.15, 1.00, 0.80, 0.65.

• Window: the twelve months preceding retrieval on 2026-09-05; the last value is the most recent month.
• Scale: peak month = 1.00; values are relative, so two keywords cannot be compared by index alone, only by volume.
• Basket: every Kling, Veo, Sora and comparison keyword that appeared in our Semrush pulls for the video cluster; no Wan or Hailuo keyword met the volume floor, so they are absent rather than flat.
• Template demand: 104 template pages with a keyword, volume and difficulty; ordering score is volume multiplied by one minus difficulty over one hundred.
• Limits: US only, English only, search not usage, and two market-size reports (Grand View Research, McKinsey) were behind bot walls on the check date, so no market-size figure is quoted.

The table lists the basket with US monthly volume, keyword difficulty and the last three values of the twelve-month index, all from Semrush on 2026-09-05. 'Latest' is the most recent month; a 1.00 there means the keyword is at its twelve-month high right now.

The shape is clearer than any single row. Sora keywords share one profile (zero, a spike, a long tail), Veo prompt keywords share another (high early, near zero now), and Kling keywords are the only group whose latest values are at or near their highs. The 'sora 2 alternative' bump in the last quarter of the window is consistent with the deprecation notice OpenAI sent developers on 2026-03-24, which set a shutdown date for the Sora 2 models and the Videos API of 2026-09-24, per OpenAI (2026).

Which of these AI video generation models can you run today?

The models hub listed 23 models on the day of capture, 15 of them video. The search leader is in the lineup: Kling v3 Omni runs text, image and start-and-end-frame generation at 720p or 1080p for 3 to 60 seconds. Veo is present as Veo 3.1 Lite, 16:9 or 9:16 at up to 1080p and up to 60 seconds, without audio in this tier. Sora 2 is not in the workbench; the model page for it is an alternatives page, which matches what the search data says people now want.

We quote only what we could open. The market trends in AI video creation 2026 that survive that filter are about adoption pressure and model churn rather than dollar sizes.

On the demand side, HubSpot's 2026 State of Marketing (2026) reports that 61% of marketers believe marketing is experiencing its biggest disruption in 20 years because of AI. On the capability side, the Stanford AI Index (2026) describes its 2026 edition as showing a widening gap between what AI can do and how prepared we are to manage it. Public attitudes are tracked in Pew's June 2026 report on Americans and AI, per Pew Research Center (2026), which is the reference to use when a client asks whether audiences mind.

Why does model churn count as a market trend?

Because it changes what a creator can buy. OpenAI's deprecation page sets 2026-09-24 as the shutdown date for sora-2, sora-2-pro and the Videos API. Google's Veo page frames Veo 3.1 as its leading video model and notes that its own preference evaluation could not compare image-to-video against Sora 2 Pro because that model did not support realistic human images, per Google DeepMind (2026). Independent rankings exist for anyone who wants a third opinion: Artificial Analysis (2026) runs text-to-video, image-to-video and video-editing leaderboards, and Arena (2026) crowdsources head-to-head votes. AI video generation market trends 2026 are, in practice, the story of which of those names are still available next quarter.

LazyKiwi's template-demand file attaches one primary keyword to each template page, with US monthly volume and keyword difficulty from Semrush, pulled 2026-09-04. It exists to order the templates hub, which showed 225 templates on the day of capture. The top rows are camera language and photo looks, not model names.

Seven of the twelve are camera moves, which is the practical finding for anyone choosing what to build: people search for the shot they want, not the engine that renders it. Current trends in AI video creation on the effect side are face and style filters with low difficulty ('fat filter' at KD 12), where a single template page can rank quickly.

AI video trends move faster than content calendars, so the useful response is procedural: decide what to test now, what to stop, and how to check the numbers yourself before the next planning cycle.

1. 1

   Test Kling first for image-to-video

   It is the keyword group at its twelve-month high and it is in the LazyKiwi AI video generator. Run the same photo through Kling v3 Omni and Veo 3.1 Lite and keep whichever holds the face.

2. 2

   Stop building Sora-specific content

   The API shuts down on 2026-09-24 per OpenAI's page, and the 'sora 2 alternative' keyword is already rising. A comparison post written as 'X vs Sora 2' has a shelf life measured in weeks.

3. 3

   Name the shot, not the model

   Title landing pages and videos with the camera move or effect ('dolly zoom', 'bullet time', 'mirror selfie'); those keywords carry five to ten times the volume of any model query in the basket. The referral side agrees: in the 90 days to 2026-09-04, chatgpt.com was the second-largest source of sessions to lazykiwi.ai after direct (300 sessions, 279 users), landing mostly on the AI clothes changer and logo animation tool pages, which are named for the job, not the model.

4. 4

   Finish at 1080p

   Search interest in enhancement follows resolution expectations; when a 720p render is the only take that worked, pass it through the AI video enhancer rather than re-rendering.

5. 5

   Re-check the index quarterly

   Paste the basket into Google Trends for a free cross-check; its interest-over-time chart uses the same peak-equals-100 scaling idea, per Google Trends (2026).

Cite the underlying sources, not this post, for any single figure: Semrush (US database, retrieved 2026-09-05) for the keyword rows, LazyKiwi template-demand file (pulled 2026-09-04) for the template rows, and the linked vendor or report page for everything else. If you cite the synthesis, use 'AI Video Generation Trends 2026, LazyKiwi blog, data as of 2026-09-05' and link this page.

• Update cadence: the keyword basket is re-pulled when the video cluster is refreshed, roughly quarterly; the template-demand file changes when new template pages ship.
• Reuse: the tables may be reproduced with attribution; the index values are Semrush's and subject to its terms.
• Corrections: if a row disagrees with what Semrush shows you today, the index has moved; the retrieval date in the caption is the reference.

The earlier version of this page presented a four-observation series without naming its source. The series was the Semrush trend for our head keyword; it now has five values (0.07, 0.15, 1.00, 0.80, 0.65) and is reported above with its origin, which is the only change to the finding.