Pinterest has a new way for users to find exactly what they’re looking for — and it doesn’t involve typing keywords into a search bar. The platform launched an experimental conversational shopping app called Ask Pinterest, a standalone AI-powered experience that lets people discover products and get personalized inspiration through natural language, much like chatting with a knowledgeable friend who happens to know your taste perfectly.
Summary
Key takeaways
- Pinterest launched Ask Pinterest, a standalone experimental AI chatbot app for conversational product discovery and personalized shopping recommendations.
- The app draws on Pinterest’s proprietary Taste Graph and users’ saved Pins and Boards to tailor its answers.
- Pinterest introduced the Pinterest Model Context Protocol (MCP) to let advertisers manage campaigns with third-party AI tools.
- A new global AI model called Performance+ creative helps advertisers automatically identify which ad creatives are likely to perform best.
- An AI assistant for Ads Manager is currently in beta in the U.S., part of a broader push into AI-powered advertising infrastructure.
Pinterest unveils ‘Ask Pinterest’ experimental AI shopping app
Ask Pinterest is designed to go somewhere the main Pinterest app hasn’t fully gone before: complex, multi-step conversations about what you need. Instead of entering a search term and scrolling through results, users can ask things like how to furnish a room over time or how to plan a dinner party — and the app will keep their context across sessions, building on previous answers rather than starting fresh each time.
That kind of query has always been awkward in traditional search. You can type “boho living room decor” and get images, but you can’t easily follow up, refine, and plan across multiple visits. Ask Pinterest is built specifically for that gap.
The app will initially roll out in limited access, with no detailed public timeline announced yet for a wider release. Pinterest has described it as an experimental environment — a sandbox where the company can test AI-driven discovery without altering the experience of its main platform.
Why a standalone app makes strategic sense
Keeping Ask Pinterest separate is a deliberate move. By running it outside the main app, Pinterest can iterate quickly, observe how users actually interact with conversational shopping, and eventually bring the most successful elements back into the flagship experience. It’s a lower-risk path to a major product evolution.
This also matters in a broader competitive context. Google has embedded AI directly into shopping search. ChatGPT has experimented with agentic shopping. Meta and Shopify have made similar moves. Pinterest is entering a crowded space, but it’s doing so with something the others can’t easily replicate: years of accumulated visual taste data tied to real users.
Personalization through Pinterest’s Taste Graph and user data
The Taste Graph is what makes Pinterest’s AI ambitions particularly interesting. It’s the company’s internal system for mapping people to their aesthetic preferences, interests, and style sensibilities — built from billions of saved Pins and Boards over years of user behavior. Ask Pinterest taps directly into that data to make its answers feel less generic and more tuned to who you actually are.
On top of the Taste Graph, Ask Pinterest can pull from a user’s own saved Pins and Boards to further personalize its responses. If you’ve been saving minimalist kitchen inspiration for months, the app won’t recommend maximalist decor. That’s a meaningful distinction from general-purpose AI chatbots that start with no knowledge of your preferences.
Critically, Pinterest is not licensing this data to other AI services. The company has made a clear strategic choice to use its proprietary information exclusively to train and power its own AI products. That keeps the competitive advantage in-house — and signals that Pinterest sees its data as a long-term asset, not a short-term revenue stream.
New AI advertising innovations for marketers
The Ask Pinterest announcement arrived alongside a significant set of tools aimed squarely at advertisers, timed just ahead of Cannes Lions — the adtech industry’s flagship annual event, which this year is centered on how AI can serve marketers more effectively.
Pinterest Model Context Protocol (MCP) for third-party AI campaign management
The Pinterest Model Context Protocol is a new infrastructure layer that lets advertisers manage and monitor their Pinterest campaigns using third-party agentic AI tools — in a standardized way. In practical terms, this means brands and agencies using external AI platforms for campaign management won’t have to work around Pinterest’s system; they’ll be able to work within a defined, open protocol. That’s a meaningful shift for larger advertisers who already run multi-platform AI workflows.
Performance+ creative AI model and Ads Manager beta
A new AI model called Performance+ creative has been introduced globally to help advertisers choose between different ad creatives. Rather than manually A/B testing which version of an ad performs better, the model picks the highest-performing creative each time an ad is served. It’s the kind of automation that could meaningfully reduce wasted ad spend at scale.
Separately, Pinterest’s AI assistant inside Ads Manager is currently live in beta in the U.S. Together, these tools represent Pinterest’s clearest pitch yet to advertisers: the platform is not just a place to reach an audience, but an AI-powered system for optimizing how you reach them.
Pinterest’s AI strategy and the future of discovery
There’s a philosophical argument embedded in everything Pinterest announced. Chief Business Officer Lee Brown put it directly: “the future of discovery won’t be driven by keywords alone. It will be shaped by context, taste, and trusted recommendations.” Pinterest believes it has a unique advantage in that future — one built on a user base that actively curates their interests, not just passively scrolls.
That framing matters when you consider how the company is positioning itself against much larger AI players. Pinterest isn’t trying to build a general-purpose chatbot. It’s building something narrower and potentially more valuable for shopping: a system that already knows what you like before you ask. The questions Pinterest users bring to the platform — what to wear, how to decorate, what to cook — are exactly the kind of high-intent, taste-driven queries that reward personalization over raw information retrieval.
Whether Ask Pinterest evolves from experiment to mainstream product depends on whether that personalization edge holds up at scale. But the architecture is in place, and the proprietary data is already there.
FAQ
What is ‘Ask Pinterest’ and how does it differ from the main Pinterest app?
Ask Pinterest is an experimental standalone AI-powered app designed for conversational shopping and personalized product discovery using natural language. Unlike the main Pinterest app, which is built around visual search and browsing, Ask Pinterest uses a chatbot-like interface where users can pose complex, multi-step questions and receive tailored recommendations informed by their personal taste history.
How does Ask Pinterest personalize its recommendations?
Ask Pinterest draws on Pinterest’s internal Taste Graph — a data system that maps users to their aesthetic interests — as well as each user’s own saved Pins and Boards. This means responses are shaped by years of individual behavior on the platform, not just the content of a single query.
What new AI tools has Pinterest introduced for advertisers?
Pinterest introduced three new advertiser-focused tools: the Pinterest Model Context Protocol (MCP), which allows campaign management through third-party agentic AI tools; the Performance+ creative AI model, launched globally to automatically select the best-performing ad creative; and an AI assistant for Ads Manager, currently in beta in the U.S.
What is Pinterest’s vision for the future of discovery?
According to Chief Business Officer Lee Brown, Pinterest believes the future of discovery will be driven by context, taste, and trusted recommendations — not keywords alone. The company sees its proprietary data and personalization capabilities as a distinct advantage as AI reshapes how people find products and inspiration online.
Article produced with the assistance of artificial intelligence and reviewed by the editorial team.
