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What scaling advertising content with AI video means
Scaling is not simply generating more clips. It can mean turning a campaign idea into a visual preview before committing to a full shoot, converting existing product imagery into video, or producing tailored variants for different formats and audience contexts. Those options can make a wider set of creative tests practical when conventional production would take too long or cost too much.
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Industry adoption figures suggest that advertisers are exploring these workflows, but they are not proof of performance. The IAB reported in July 2025 that 50% of advertisers were already using generative AI to build video ads, while 86% were using or planning to use it. The same announcement said buyers projected that 40% of ads would use GenAI creative by 2026; that was a forecast, not a measured 2026 result. IAB also reported uses including versions for different audiences (42%), visual-style changes (38%), and contextual relevance (36%). IAB’s 2025 video-ad and GenAI survey announcement notes faster adoption among small and mid-tier brands than among the largest advertisers.
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Pre-visualize a campaign before full production
AI-generated previews can help teams explore visual directions and discuss an idea before investing in finished production. Microsoft’s June 2025 customer story describes WPP’s T&Pm using Sora through Azure OpenAI for campaign pre-visualization and tailored variants. In its rice-brand example, the agency described generating videos for different recipes, audiences, languages, or platforms from brand guidance. This is an agency workflow example, not an independent performance assessment. Microsoft’s WPP customer story also describes using a pet owner’s photo and story to create a customized animated dog-food video.
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Adapt a core idea into audience- or format-specific versions
A single approved concept may need different lengths, aspect ratios, language, context, or imagery to suit placements and audiences. AI can reduce the manual effort of producing those variations, while a human team decides which differences are relevant and on-brand. T&Pm Chief Strategy Officer Oli Egan said, “If we can establish real personal relevance to consumers in the content we create, it’s more effective.” That is the agency’s view of personalization, not a guarantee that any tailored asset will perform better.
Make video from existing product assets
When a brand already has product photography or other approved imagery, AI workflows can help turn those materials into video creative without starting from a new live-action shoot. Amazon Ads’ WD-40 case describes a French launch using AI-powered video generation based on existing product visuals. The campaign combined Sponsored Brands video and Online Video through Amazon DSP, making it an example of both creative production and broader media planning.
What campaign examples show—and what they do not
The published cases below report positive outcomes, but each is specific to its brand, campaign design, geography, and measurement. They do not establish that AI-generated video generally outperforms conventional production.
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| Campaign | Reported result | What was compared or measured |
|---|---|---|
| Cuisinart, United States, 2026 | AI-generated asset had an 18-point higher detail-page view rate, 14% lower cost per detail-page view, and a 10-point higher branded search rate. | Amazon Ads describes an approximately 30-day comparison of a 15-second AI-generated ad with a traditionally produced asset, holding audience segments, bidding, and optimization consistent. Amazon Ads’ Cuisinart case study. |
| WD-40 Company, France, 2026 | Amazon Ads reports more than 50% higher average daily sales, three times daily unit sales, 88% new-to-brand purchases, and CTR 45% above category benchmarks. | The launch combined AI-powered video with a full-funnel media strategy and used before-and-after measurement. The results cannot be attributed to video generation alone. Amazon Ads’ WD-40 case study. |
| Traditional Medicinals, 2026 | Partner-provided figures report a 1.24x higher new-to-brand purchase rate and 1.14x more efficient cost per new customer. | Amazon Ads says the streaming TV campaign was compared with a comparable traditionally produced campaign running in the same period; the figures are identified as partner-provided data. Amazon Ads Partner Perspectives. |
The Cuisinart example also describes a four-week production timeline for the tested video, compared with one to three months for motion design or six to eight months for original filming. Those are timings reported for that case’s workflow, not standard production benchmarks.
How to decide whether AI video belongs in your campaign
Start with the production problem
Identify what is difficult to make with the current process. AI may be useful when a team needs to preview several concepts, create multiple format variants, localize a campaign, or test a placement that would otherwise be uneconomical to produce for. If the goal is a defining brand identity or a high-stakes tentpole launch, practitioner Claire Magruder recommends involving the full creative team and making the appropriate production investment; she identifies format variation and placement testing as clearer AI-video fits. This is practitioner guidance, not a universal rule.
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Give the system direction, not just a prompt
Effective variation depends on inputs: audience, placement, product truth, approved assets, brand voice, and the action the ad should encourage. WPP Creative Innovation Designer Stuart Foy said that access to Sora through an API let him make many quick “mistakes” to reach a desired result. That describes a creative exploration process; it does not mean outputs are ready to publish without selection and review.
Keep brand and human approval checkpoints
Define who checks accuracy, visual quality, rights and usage of source materials, brand guidelines, and final claims before an asset runs. In the Cuisinart case, Amazon Ads describes a brand-guideline review and storyboard approval checkpoint before production, alongside a controlled campaign comparison. Those controls are especially important when AI changes product appearance, language, or audience context.
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Measure the campaign objective
Choose metrics that match the job of the ad rather than treating output volume as success. Cuisinart tracked detail-page view rate, cost per detail-page view, and branded search rate. A different campaign might prioritize video completion, purchases, customer acquisition cost, or another downstream action. Compare AI-assisted and conventional assets under comparable audience, bid, and optimization conditions where possible, and distinguish creative effects from changes in media strategy.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.AI-assisted production versus conventional production
| Decision factor | AI-assisted production | Conventional production |
|---|---|---|
| Best-supported role | Pre-visualization, variant creation, localization, and testing formats or placements. | Full creative-team production remains a practitioner-recommended choice for defining brand identity and tentpole launches. |
| Production time | Cuisinart’s case reports four weeks for its tested video; this is a case-specific timeline. | In the same Cuisinart case description, motion design took one to three months and original filming six to eight months; these are not universal timelines. |
| Brand control | Requires a specific brief, approved inputs, and human review and approval. | Production teams still need brand direction and review; the available sources do not establish that either method inherently ensures quality. |
| Performance evidence | Reported campaign outcomes are promising examples, not a general benchmark or causal guarantee. | Traditional creative can serve as a control or comparison asset, as in the Cuisinart and Traditional Medicinals examples. |
| Workflow integration | May involve standalone creative tools or API-based integration; WPP’s cited example used Sora through Azure OpenAI. | Production arrangements vary; the cited sources do not establish a standard process or cost. |
What brands should take away
AI video is most useful as a way to widen creative exploration and lower friction around adaptation and versioning—not as a substitute for strategy or a shortcut to guaranteed results. Amazon Ads practitioner guidance recommends choosing use cases deliberately, supplying specific audience context, keeping people in a directing role, and judging AI creative by the same performance standards as other assets. As Amazon Ads’ Cuisinart case shows, a disciplined comparison can reveal whether an AI-assisted asset helps a particular campaign; the answer must come from that campaign’s evidence.
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