Holiday shopping is just around the corner, and both OpenAI and Perplexity have jumped into the fray with new AI-powered shopping assistants integrated into their chatbots. These tools are designed to make the shopping research process smoother and more personalized for users, but the landscape is more complicated than it seems at first glance. Here’s the catch: while these new features from tech giants look promising, specialized startups in AI shopping see things quite differently—and it raises some interesting questions about who will dominate this evolving market.
To break it down, OpenAI’s ChatGPT can now assist users by answering detailed purchase queries like finding a gaming laptop under $1000 with a large screen, or even by analyzing a photo of expensive clothing to suggest similar items at a lower cost. Perplexity’s chatbot, on the other hand, boasts a memory feature that remembers details about users—such as location or occupation—and uses that information to give tailored shopping recommendations. This makes the shopping experience feel more personal and relevant to individual preferences.
Industry forecasts add fuel to this AI-shopping hype. Adobe predicts a staggering 520% increase in AI-driven online shopping during the 2025 holiday season, hinting at a lucrative opportunity not only for the big players but also for startups like Phia, Cherry, and Deft. These startups develop more specialized AI tools focused on niche shopping experiences, such as fashion or e-commerce search. But with OpenAI and Perplexity moving aggressively into this space, the question arises: can smaller startups keep up or will they be squeezed out?
Zach Hudson, CEO of Onton, a startup specializing in interior design shopping, argues that niche-focused AI will continue to outperform broader, general-purpose models like ChatGPT. The reason? Data quality. OpenAI and Perplexity rely heavily on existing web search indices from Bing or Google, which can limit the depth and specificity of results they deliver. In contrast, startups like Onton invest in creating clean, high-quality data pipelines specialized for their market. Hudson warns that startups without this kind of focused data strategy may struggle to compete.
Julie Bornstein, CEO of Daydream, echoes this viewpoint. She highlights that shopping for items like fashion is deeply nuanced and emotional—much more so than buying electronics or generic products. Understanding fabrics, silhouettes, and how outfits come together over time requires domain-specific knowledge and data, which general AI models lack. Startups that build and train their tools on these specialized datasets can offer a more authentic and satisfying shopping experience.
Meanwhile, OpenAI and Perplexity are leveraging the advantage of their massive user bases and high-profile partnerships. For instance, OpenAI partners with Shopify and Perplexity with PayPal, enabling users to make purchases directly within their chat interfaces. This seamless checkout experience could be a game-changer compared to startups who currently redirect users to retailer websites and rely on affiliate revenue.
However, the big players face their own challenges, notably the high costs of running these AI services at scale and the ongoing quest for profitability. Drawing inspiration from giants like Google and Amazon, turning e-commerce into a revenue source through product ads seems logical—but it might also amplify existing frustrations consumers have with search results cluttered by advertising.
Ultimately, the debate boils down to this: broad, all-encompassing AI tools have the advantage of scale and reach, but specialty AI shopping assistants armed with precise, curated data and in-depth expertise will cater better to real consumer needs. This tug-of-war raises intriguing questions about the future of AI in retail. Will consumers prefer a one-stop-shop for everything, or lean toward expert assistants that truly understand their unique tastes? Which model will win out? And most importantly, where do you stand on this retail AI revolution? Share your thoughts—do specialized AI assistants hold the key, or will the tech giants dominate by default?
Amanda Silberling, a TechCrunch senior writer with a background spanning technology and culture, reports on these developments with deep insight. She highlights how the intersection of AI, data quality, and consumer behavior creates both challenges and opportunities in the e-commerce world. Silberling’s experience ranges from grassroots organizing to co-hosting a podcast about internet culture, emphasizing her layered understanding of digital transformation.
