Retailers are focused on getting their products recommended by AI this Christmas. But what happens when AI becomes better at creating demand than retailers are at fulfilling it? Mark Ruston, Global Retail Lead at Capgemini, explores the link between AI-powered demand and the less visible machinery required to fulfil it.
This holiday season, retailers face a new challenge: becoming victims of their own success.
As shoppers look for the perfect gift, they are turning to increasingly sophisticated AI shopping assistants to discover products and compare options, giving retailers opportunities to reach customers who might otherwise never have considered their products.
But what happens if AI becomes better at generating demand than retailers are at fulfilling it?
When recommendations create problems
With shoppers asking questions like, ‘Where can I find the best Boxing Day deals?’, AI shopping assistants can recommend products based on price, features, reviews and individual preferences.
This could change purchasing patterns across the retail sector, directing more customers towards certain products or brands than retailers had anticipated. Smaller, less familiar brands could be particularly affected, as AI recommendations give them new opportunities to compete with established names.
For example, imagine a relatively unknown brand whose products suddenly begin appearing in AI-generated gift recommendations. Shoppers who might never have discovered the brand are now being directed towards its products.
For the brand, this should be a success story. But if its inventory, warehouse operations and delivery capacity cannot keep pace, the additional demand could become a problem.
The same challenge could affect larger retailers if AI recommendations generate unexpected demand for particular products or in locations where they have limited stock or delivery capacity.
This risk is particularly relevant during the holiday shopping period, when retailers are already managing seasonal peaks in demand and pressure on their delivery networks.
The pace of AI adoption makes this challenge all the more pressing, as consumers are arguably embracing the technology faster than retailers are able to prepare for it. And retailers need to be ready for more than a new way to search.
AI’s role in shopping is expanding; from inspiring shoppers to discover products, to narrowing their choices through conversation, completing purchases on their behalf and helping resolve issues or arrange returns afterwards. As AI takes on more of the purchasing process, it could create demand faster and concentrate it more sharply than traditional search and advertising.
Your AI reputation may hinge on delivery
Poor fulfilment has always disappointed customers; in future, it could also influence how AI shopping assistants assess and recommend retailers.
Consumers weigh price against factors such as convenience, quality and reliability. Knowing that a gift will arrive before December 25 can be just as important as finding the right product at the right price. As AI shopping assistants become more capable, these considerations could increasingly influence which retailers they recommend.
For example, an AI assistant could make recommendations based on a retailer’s track record on stock availability and delivery. This means a retailer offering the most suitable product or lowest price might lose out to a competitor with a stronger record of fulfilling orders reliably.
How this pans out for retailers depends on the access to and quality of data that shopping assistants have. But it raises the possibility that retailers which repeatedly miss delivery commitments or substitute unavailable products could find it harder to win future AI recommendations.
Anticipating demand is now essential, and AI can help
The good news is that AI can also help retailers manage the additional demand it generates. For shoppers, the most valuable AI may be the AI they never notice: the intelligence working behind the scenes to ensure the right product is available, in the right place, with a delivery promise the retailer can keep.
Rather than waiting for orders to arrive, retailers can use AI to anticipate what consumers are likely to buy, where they are likely to buy it, and when they are likely to buy it.
If AI identifies growing interest in a particular product, that information should influence decisions about where inventory is positioned, which stores or warehouses should fulfil orders and the delivery capacity required. Without this connection, retailers risk generating valuable insights into customer demand without being able to act on them quickly enough.
AI can help retailers make data-backed decisions about fulfilment by bringing together information on stock availability, warehouse operations, transport networks and last-mile delivery.
AI can also support retailers when unexpected problems arise, helping identify alternatives when products become unavailable or deliveries are disrupted.
Getting the basics right this festive season
While technologies such as warehouse automation, robotics and new delivery models will continue to advance, retailers should not overlook the fundamentals this holiday shopping season.
Accurate inventory information, realistic delivery commitments and the ability to respond quickly when something goes wrong will remain essential.
And fulfilment does not end when a parcel reaches the customer’s doorstep. Holiday purchases inevitably generate returns, and AI can also help retailers manage these processes, from handling customer enquiries to supporting the inspection and restocking of returned products.
Ultimately, retailers need to efficiently connect the entire shopping journey, from anticipating customer demand to delivering products reliably, all while protecting margins. For many retailers, the 2026 holiday season will be their first at this level of AI-assisted shopping, leaving them with little precedent for how demand could shift and limited time to adapt.
For global retailers, connecting customer intent, inventory, fulfilment and delivery across markets is complex. But they do not need to transform everything at once. The priority is to connect trusted demand signals to the operational decisions that matter most: what inventory to hold, where to position it, which location should fulfil the order and what promise can realistically be kept. The winners of this AI-driven Christmas will not simply be the retailers that appear in the recommendation. They will be the ones capable of delivering it, profitably and reliably.
