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Jul 03, 2024

As summer sales approach, do you really need an AI shopping assistant?

Amazon’s new AI assistant, Rufus, offers a “conversational shopping experience.” Will you let it decide what’s best for you?


A shopping buddy should be entertaining, while a shopping assistant should be helpful. Now, a new hybrid is emerging that promises to be both: meet Rufus, an AI-powered helper designed to enhance your Amazon shopping experience.

We are already familiar with virtual assistants like Alexa and Siri, but we will soon find personified algorithms becoming a regular part of our online shopping journeys. 

AI shopping assistants are not entirely new, nor are they yet mainstream. Still, their seamless integration into our shopping habits seems imminent, especially with major players like Amazon launching their own versions. The primary goal of these new assistants is to help us discover items we love through engaging, conversational interactions.


How AI-Powered Chatbots are Revolutionising Your Online Shopping Experience

It all starts with a shopping list or a wishlist of items you know you like. Based on your preferences, the AI assistant can predict what else you might enjoy using criteria such as similarity, price range, designer, or material. This recommendation system is already embedded in major online shopping apps and websites. But how does it work? Essentially, it’s a sophisticated equation.

 AI introduces an element of prediction and interpretation, evaluating a range of factors to offer suggestions. For example, you might start a conversation with your AI shopping assistant, engaging in a human-like interaction.

In a physical store, you would ask a shop assistant to help you find a specific pair of sneakers in your size from the display and expect them to return with that exact item. Online shopping is different; you can browse countless sneakers, filter by size or brand, and easily become overwhelmed by the sheer number of choices. This is where AI shopping assistants come in – they can bridge the gap between the curated (yet limited) selection of physical stores and the endless (yet impersonal) array of options available online.

An AI shopping assitant can predict products you might like based on previous wishlists and shopping habits. Graphics by Alumna and visual Designer Constanza Coscia

An AI-enhanced chatbot offers numerous advantages. You can be vague about what you’re looking for and still be surprised by the variety of options it presents. You can ask the AI to filter through choices to find exactly what you want, then compare prices across different online retailers or find the most reliable seller on pre-loved fashion sites.

AI-powered chatbots are set to excel at handling open-ended questions and vague requests. Modern AI can manage a wider range of queries than their predecessors, which only worked effectively with neatly tagged and categorised databases of items.

Graphics by Alumna and visual Designer Constanza Coscia

An AI chatbot can be extremely useful while online shopping, helping you filter through options and giving you exactly what you need. Graphics by Alumna and visual Designer Constanza Coscia

We are entering a new era of casual discovery where you can ask AI for recommendations such as: “Find me a stylish outfit suitable for a dinner party with my in-laws,” “Show me a perfect, stylish, and affordable raincoat in one size that fits all,” or “Discover a statement designer handbag in a bold colour.” It’s up to you to provide specific feedback and guide the AI in finding the perfect garment or accessory.

The Filter Bubble Dilemma: How AI Shopping Assistants Might Limit Your Choices

The primary concern with allowing algorithms to take over your shopping wishlists is their extreme accuracy, which may not always be in your best interest. By providing AI with detailed clues about your preferences, you essentially train the machine on your specific tastes, leading it to inundate you with similar products and potentially trapping you in a filter bubble.

Disadvantage? The AI assitant might trap you in a filter bubble. Graphics by Alumna and visual Designer Constanza Coscia

In 2011, activist Eli Pariser shed light on this phenomenon in his bestselling book, “The Filter Bubble: What the Internet Is Hiding from You.” Pariser revealed to a broad audience that social media platforms manipulate our feeds to show us content that aligns with our existing biases and interests. This issue is even more evident with AI, as personalised recommendations can backfire, distorting our shopping experiences and limiting our exposure to only those items that need to be sold or are conveniently located in nearby warehouses.

This is already happening, and in the future, we might have independent, cross-platform AI shopping assistants that truly serve our interests. These assistants could introduce us to niche options, emerging designers, and small indie brands from across the globe, encouraging us to invest in unique and special items, even if it means paying extra for shipping and waiting a few weeks for delivery. This is a vision we should cherish and work towards.


Gaia Giordani
Generative AI Explorer and New Media Communication Expert