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Generative AI Produces Near-Identical Ads for Locals

Generative AI tools like ChatGPT are producing near-identical ads for local businesses and school fairs in New Zealand, sharing similar fonts, layouts, and generic imagery, according to RNZ. ChatGPT processes about 2.5 billion requests daily globally, with an estimated 15 million from New Zealand. Creative director Vaughn Davis warned that agencies risk delivering "the machine-built average of every other ad.

read3 min publishedJun 13, 2026

Generative AI is producing visually similar adverts used by a wide range of organisations, from local restaurants to school fairs, RNZ reports. The ads often share the same fonts, layouts, dense text and generic imagery, and are easy to create by prompting tools such as ChatGPT, the article says. RNZ cites ChatGPT handling about 2.5 billion requests per day globally and estimates 15 million of those come from New Zealand. An unnamed New Zealand business owner told RNZ, "I didn't really know what I was doing but I got there," while Vaughn Davis, creative director at The Goat Farm, cautioned that agencies should avoid delivering "the machine-built average of every other ad," per RNZ.

What happened

Generative AI tools are being used to create social and print adverts for a broad set of local organisers, including new businesses and school fairs, according to RNZ. The article reports these ads frequently share the same visual hallmarks: similar fonts, comparable layouts, lots of text and generic images. RNZ cites ChatGPT usage statistics, saying the service processes about 2.5 billion requests daily worldwide and that roughly 15 million of those originate in New Zealand. RNZ includes a direct quote from an unnamed New Zealand business owner: "I didn't really know what I was doing but I got there," and quotes Vaughn Davis, creative director of The Goat Farm, warning that agencies that rely on the same tools risk producing ads that look "like everyone else's," as reported by RNZ.

Editorial analysis - technical context

Generative-image and text tools produce outputs by recombining learned visual and linguistic patterns; that makes template-like sameness a predictable outcome when prompts are generic or when users lean on default styles. For practitioners, the repeatability reflects two technical drivers: model training on large, overlapping corpora of commercial imagery and text, and the prevalence of short, underspecified prompts that prioritize speed over bespoke prompt engineering. Industry-pattern observations: teams that invest in stronger prompt design, prompt chains, or lightweight post-processing typically extract more distinctive creative results from the same base models.

Context and significance

Industry observers have noted rapid diffusion of generative creative tools into nontraditional advertising users, lowering the barrier to entry for basic asset production. This increases the volume of cheaply produced marketing materials, which can compress attention for professional creative shops and raise the importance of differentiation. For data and ML teams, the practical implication is an increased demand for toolchains that combine model outputs with constrained templates, brand overlays, or retrieval-augmented asset libraries to maintain distinct visual identity.

What to watch

Observers should track:

  • •whether local businesses continue to rely on default prompts or adopt curated prompt libraries
  • •emergence of tooling that automates brand-safe overlays and asset hygiene
  • •responses from creative agencies in packaging higher-value services around customization, testing and distribution. RNZ did not include a statement from platform vendors about these specific uses in the article

Scoring Rationale #

Widespread adoption of generative creative tools matters to practitioners because it changes production volume and creative workflows, but the story is about diffusion and practice rather than a new technical advance.

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