Physical retail is failing to meet customers’ demands for real-time responsiveness as their expectations for more reactive retail experiences are accelerated by ecommerce and AI, the latest data from SAI, the leading active intelligence solution for stores, reveals.
Original research of over 1,000 shoppers by SAI showed that over a third (35%) believe stores are falling behind because they can’t keep pace with the speed of AI or respond to data with the same agility as ecommerce channels. This view is even more acutely felt among younger cohorts of customers, rising to 51% of Millennials and 48% of Gen Z.
As the Answer Economy gathers pace and AI adoption grows, consumers increasingly expect the immediate responses they have become used to receiving in digital buying journeys.
And this immediacy is bleeding into their in-store expectations, with three quarters (75%) saying stores should adapt in real-time, whether through queue management, optimising stock allocation or matching labour to pressure points in the store. A further two thirds (65%) say they now expect in-store frictions to be resolved as quickly as ecommerce can react to any issues they experience online.
However, even as stores become more digitalised and connected, shoppers aren’t seeing the benefits of physical retailers using the insights generated from their estates to improve shopping experiences, with many suggesting stores remain digital black holes.
Despite greater visibility being available to retailers through computer vision, AI and store monitoring systems, six in ten (60%) of customers say retailers still suffer from “blind spots” and are unaware of what’s happening on the shop floor. A further 56% feel retailers currently aren’t effectively – or actively – managing store operations and a similar proportion (55%) believe physical retail is too slow to respond when issues occur.
“With stores becoming more connected, retailers have never had more opportunities to gain visibility across their estates. Yet too often those opportunities aren’t being translated into meaningful operational insight,” said Som Sinha, Co-Founder & CEO of SAI. “By shining a light on what’s happening across every location, retailers can elevate all stores to the standard of their best-performing stores, reducing operational drag and delivering the responsive experiences customers increasingly expect.”
Over half (53%) of shoppers in SAI’s poll said their bricks-and-mortar experiences would be improved if retailers tapped into data to inform store-wide operations, rising to 64% of Millennials, while 74% agreed proactive problem-solving in-store was key to creating positive shopping encounters.
Using its patented Visual Language Model (VLM), the SAI One platform blends computer vision with GenAI to turn traditionally ‘passive’ store surveillance systems into an active, operational platform for real-time store intelligence.
Proprietary AI innovation within the platform analyses live data from video feeds using advanced VLM to build a comprehensive, contextual picture of how stores actually operate, surfacing meaningful operational signals, insight cues and timely staff alerts that drive estate-wide performance.
