For years, we've thought that a creative asset had one main goal: to capture a person's attention. The product had to look appealing. The copy had to persuade. The user had to click.
But in 2026, there's a second audience we also need to convince: artificial intelligence.
More and more platforms are using AI models capable of interpreting images, text, context and intent to decide which content to show each user. Pinterest is one of the most interesting examples thanks to the development of PinCLIP, an internal AI model designed to better understand every Pin and improve search, recommendations and content distribution.
Although PinCLIP isn't a feature available to advertisers, it reflects a shift that affects every brand investing in content or advertising: creative assets no longer communicate only with people; they also communicate with algorithms.
The result? The way brands design images, write titles and structure product catalogues is beginning to have a much greater impact on how platforms understand and distribute content.
How does Pinterest use artificial intelligence?
When we think about artificial intelligence on Pinterest, it's easy to assume the platform simply recommends Pins similar to those we've already saved.
The reality is far more sophisticated.
Pinterest uses a range of AI models to understand both content and user behaviour.
On the one hand, it analyses traditional signals such as:
- search queries;
- saved Pins;
- clicks;
- boards;
- engagement time.
But it also interprets the content itself.
It doesn't simply recognise that an image contains a sofa.
It tries to understand whether it represents a minimalist living room, a home renovation project, a small apartment, Mediterranean interior design or inspiration for decorating a rental property.
This leap is possible thanks to multimodal models such as PinCLIP, which combine visual and textual information into a single semantic representation.
In other words, Pinterest no longer relies solely on keywords. It is increasingly able to understand the meaning behind images, bringing the platform much closer to an intelligent visual search engine than a traditional social network.
What is PinCLIP and why is it changing the way Pinterest understands images?
When we talk about artificial intelligence, we tend to think of tools capable of generating images or writing text.
But there are other AI models whose job is not to create content, but to understand it.
That is precisely the purpose of PinCLIP, the multimodal model developed by Pinterest to better understand every Pin and improve the way the platform organises, recommends and distributes content.
Although it is not a visible feature for users or a tool that advertisers can activate through Pinterest Ads, PinCLIP represents an important shift: Pinterest no longer needs to rely solely on keywords or previous interactions to decide what to show.
It can now interpret the content of an image in a way that is much closer to how a person would understand it.
How does PinCLIP work?
To understand how it works, imagine Pinterest receives two new Pins.
The first shows a pair of trainers against a white background.
The second features the same trainers in a photograph taken during a trip, alongside a backpack, a camera and a mountain landscape.
Although both Pins promote exactly the same product, PinCLIP understands that they tell different stories.
The first Pin is simply about a pair of trainers.
The second conveys concepts such as:
- travel;
- adventure;
- hiking;
- holidays;
- nature;
- outdoor equipment.
This information allows Pinterest to connect the Pin with users looking for travel inspiration or planning a getaway, even if the Pin description does not mention any of those words.
How users interact with content
Pinterest also learns by observing which Pins are frequently saved together or appear on similar boards.
If thousands of users save a lamp to boards related to Mediterranean interior design, that relationship helps the system better understand the context of the content.
The result is a platform capable of recommending inspiration long before a piece of content has accumulated thousands of interactions.
What does this mean for brands advertising on Pinterest?
Although brands can't use PinCLIP directly, they can adapt their creative assets to make it easier for AI models to understand and distribute their content.
This is where the creative brief starts to change.
A few years ago, simply showcasing the product was enough.
Today, context matters almost as much as the product itself.
Example 1
A furniture brand wants to promote a dining table.
Creative A:
A table against a white background.
Copy:
"New collection."
Creative B:
A table set for dinner with friends.
Copy:
"Ideas for making the most of a small dining room."
Both creatives promote the same table. But the second communicates much more. It speaks about space. It reflects a real need. It presents a usage scenario. All of this gives the algorithm more context to understand when that content is relevant.
Example 2
A fashion brand sells a pair of trainers.
Instead of producing a single creative, it develops multiple versions.
- For travelling.
- For work.
- For festivals.
- For city walks.
- For weekend getaways.
The product is exactly the same.
The intent is different.
And that difference enables Pinterest to connect each creative with different searches, interests and moments of inspiration. At Adsmurai, we've been working around this idea for years.
Creative at scale isn't simply about producing more assets. It's about creating content tailored to different moments, needs and contexts, so that both people and algorithms can better understand when each message should be shown.
Creativity is now part of the algorithm
Pinterest is probably one of the most visible examples of this development.
But it is not the only one. Google interprets images to enrich its search results. Meta uses AI to better understand advertising creatives and optimise their distribution. TikTok automatically analyses videos, scenes and visual elements to improve recommendations.
The trend is common across all platforms. Creativity is no longer merely a visual resource. It has become a source of information for artificial intelligence.
That is why at Adsmurai we advocate a different approach to marketing. It is not enough simply to create better adverts. We need to build a system where creativity, data, AI, product catalogue and media work together seamlessly. Because the new challenge is no longer just about capturing the user’s attention; it is also about helping platforms understand exactly what your content represents, what need it fulfils and when it should appear.
Conclusion
The arrival of models such as PinCLIP makes one thing clear: visual marketing is entering a new phase.
Platforms no longer simply distribute content; they interpret it. And the better they understand a piece of creative content, the greater the chances are that it will reach the right audience.
For brands, this presents an opportunity. Not to design with an algorithm in mind alone, but to create content that is richer, more useful and more closely aligned with the user’s actual intent. Because, ultimately, the creativity that artificial intelligence understands best is usually also the kind that people understand best.
