With holiday shopping approaching, OpenAI and Perplexity (and Google too) have unveiled AI shopping features integrated into their existing chatbots. The tools allow users to research products with natural language queries, such as finding a gaming laptop under $1,000 or requesting fashion recommendations based on uploaded photos.
OpenAI’s ChatGPT suggests products that match user criteria, while Perplexity emphasizes how its chatbot memory can tailor recommendations based on previous interactions, including location and occupation. Both companies aim to simplify product discovery and enhance user experience through AI.
Specialized Startups Maintain an Edge
Despite these new features, experts suggest niche AI shopping startups may still provide superior experiences. Zach Hudson, CEO of interior design shopping tool Onton, that just recently raised $7.5M to make AI shopping smarter, emphasized that specialized datasets give vertical startups an advantage. Onton, for example, catalogs hundreds of thousands of interior design products to train AI models with higher-quality data.
Julie Bornstein, CEO of Daydream, highlighted fashion as a sector requiring nuanced understanding. “Finding a dress you love is not the same as finding a television,” she said. Vertical models, tuned to real consumer behavior, are likely to outperform general-purpose AI tools in domains like fashion, home goods, and travel.
E-Commerce Partnerships and Monetization
OpenAI and Perplexity also benefit from existing user bases and partnerships with major platforms. OpenAI integrates with Shopify, while Perplexity has deals with PayPal, enabling users to complete purchases directly in the chatbot interface. This approach mirrors strategies from tech giants like Google and Amazon, where monetization can come from product advertising and e-commerce facilitation.
However, reliance on general search indexes may limit effectiveness. Hudson noted that AI models dependent on external search results can only perform as well as the data those indexes provide, underscoring the value of proprietary, domain-specific datasets.
Looking Ahead
As AI shopping grows – Adobe projects a 520% increase in AI-assisted online shopping this holiday season – competition is likely to intensify. Startups focusing on vertical markets, investing in high-quality datasets, and leveraging domain expertise are positioned to maintain relevance even as large AI platforms expand their capabilities.
The race to merge conversational AI with e-commerce reflects a broader trend of AI adoption across consumer applications, but experts agree that specialization and data quality will remain decisive factors for success.
