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Companies are using AI in marketing to generate and adapt creative, personalize advertising, produce product imagery, and speed up campaign workflows. An AI Weekly roundup updated September 28, 2026, counts 24 named deployments, but that is the roundup’s classification—not a representative survey or an independently audited measure of adoption. The cases below show what some organizations have done and what results their sources report.
What the 24 deployments reveal
The examples span different jobs rather than one all-purpose marketing system: creating many versions of an asset, tailoring messages to places or audiences, generating product imagery, and compressing campaign production time. They also differ in maturity. Some are described as customer deployments or campaigns; IBM’s Adobe Firefly work is explicitly an early pilot. A pilot can demonstrate a possible workflow without establishing that the same result will recur at scale.
Survey findings offer a broader—but still qualified—view. In its 2025 CMO Playbook #3, Capgemini Research Institute reports that 72% of surveyed organizations used generative AI in marketing either extensively or to a limited extent, compared with 37% in its 2023 comparison. The latest survey wave involved 1,500 organizations, with fieldwork in June and July 2025. Capgemini also reports that 77% used generative AI for content creation in 2025, up from 58% in its 2023 comparison. These are survey results for the report’s respondent population, not a universal rate for every company.
How companies are using AI in marketing and content
Producing and adapting creative
For a 2024 campaign with agency Tombras, PODS used live data to adapt truck advertisements for New York City neighborhoods. Google’s customer story says the campaign covered all 299 neighborhoods in 29 hours and generated more than 6,000 headlines. Those figures describe that campaign’s reported throughput; they are not a general benchmark for how quickly AI can produce advertising.
#1 Best Overall
Capgemini Research Institute describes Cadbury’s “Just a Cadbury Ad” as a generative-AI campaign featuring a Bollywood star in localized video ads promoting local stores across India. Capgemini attributes 140 million-plus reach, more than 2,500 unique ads, and a 32% engagement spike to the campaign. These are figures from Capgemini’s case summary.
IBM used Adobe Firefly to create 200 images and more than 1,000 variations in an early marketing pilot. Axios reported that the AI-generated campaign’s engagement was 26 times higher than the benchmark for those efforts. That is a result reported for this pilot and its benchmark, not evidence that AI-generated campaigns generally achieve that lift.
Personalizing advertising and product imagery
Google reports that PUMA used Imagen to customize product photography for its website. PUMA India reported a 10% increase in click-through rate. Localization and time savings were described as aims of the work; Google’s account does not quantify those outcomes.
Radisson Hotel Group worked with Accenture and Google Cloud, using Vertex AI and Gemini models with datasets in BigQuery to personalize advertising at scale. Google’s 2024 customer story reports 50% higher ad-team productivity and more than 20% revenue growth from AI-powered campaigns. These are customer-story figures; the account’s measures should not be treated as directly comparable to the other companies’ results.
Rank #3
Capgemini describes Ulta Beauty producing personalized content at scale in collaboration with Adobe. Its report quotes Mike Maresca, Ulta Beauty’s CTIO, saying generative AI was improving productivity “by around 30%,” owing to tools such as Microsoft Copilot. This is an executive’s attributed estimate, not a separately specified productivity study in the report.
Changing campaign and content workflows
Kraft Heinz introduced TasteMaker, a custom retrieval-augmented generation engine for content creation and personalization, according to Capgemini. The report says the product-content design timeline fell from weeks to hours—an eightfold reduction as summarized there.
Standard Chartered used ChatGPT for marketing concept development and Adobe Firefly for design execution. Capgemini reports that from 2023 to 2024, the bank increased total campaigns by 150% and total assets by 133%, while reducing average working days per campaign by 21%. The report separately describes a target of reducing campaign time from 21 days to five; that is a target, not an achieved result.
Other examples involve transforming existing media rather than creating a campaign from scratch. Google describes Formula E using Google Cloud generative AI to condense two-hour race commentary into a two-minute podcast in any language, and Globo using Google Cloud AI to personalize streaming content. The cited Google account does not provide quantified outcomes for these two cases.
Best Value
How to compare the reported results
The figures measure different things—throughput, engagement, click-through rate, revenue, or working time—and come from company stories or research-publisher summaries. They are not a head-to-head test. The table keeps the task and reported outcome together so the numbers are not mistaken for equivalent measures.
| Organization and task | Reported outcome | Source and qualification |
|---|---|---|
| PODS: neighborhood-specific outdoor creative | More than 6,000 headlines; all 299 New York City neighborhoods covered in 29 hours | Google customer story, 2024; campaign-specific figures |
| Cadbury: localized video ads for local stores in India | 140 million-plus reach, 2,500-plus unique ads, 32% engagement spike | Capgemini Research Institute case summary, 2025 |
| IBM: image creation and variation in an early Firefly pilot | 200 images, more than 1,000 variations; engagement 26 times the benchmark for those efforts | Axios report, March 6, 2024; pilot result and stated benchmark |
| PUMA India: localized product photography | 10% increase in click-through rate | Google customer story, 2024; reported by PUMA India |
| Radisson: personalized advertising | 50% higher ad-team productivity; more than 20% revenue growth from AI-powered campaigns | Google customer story, 2024; customer-story outcomes |
| Kraft Heinz: product-content design workflow | Timeline reduced from weeks to hours, or eightfold | Capgemini Research Institute case summary, 2025 |
| Standard Chartered: campaign production | From 2023 to 2024: 150% growth in campaigns, 133% growth in assets, and 21% fewer average working days per campaign | Capgemini Research Institute case summary, 2025; the 21-to-5-day reduction is a target |
What these cases do—and do not—establish
Together, the cases show AI being applied to bounded tasks inside marketing workflows: adapting copy to live or local context, generating asset variations, personalizing content, and helping teams develop or execute campaigns. They do not establish that AI has replaced marketing departments, that every deployment is autonomous, or that the reported gains will transfer to another organization. The examples are selected case accounts, and their metrics may rely on company-specific definitions and benchmarks.
In some cases, the reports identify the data or systems involved: PODS used live data; Radisson used datasets in BigQuery; Kraft Heinz’s TasteMaker is described as retrieval-augmented; and Cook Medical’s internal-data chatbot supports content creation, predictive analytics, and decision-making. Capgemini quotes Cook Medical Global Marketing Director Terrence Wiggins describing that chatbot as a way to access company information and make better business decisions. These descriptions indicate that integration and data access are part of the work, but they do not provide a common measure of data quality, review requirements, or human oversight across deployments.
The strongest reading of the evidence is practical rather than predictive: companies have deployed or piloted AI in specific marketing activities, and some have reported substantial case-level results. Those reports are useful illustrations of possible workflows, not guarantees or comparable independent benchmarks.
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