Retailers are turning to computer vision to boost productivity, using automated shelf tracking to defend their thinning profit margins.
This technology rollout tackles the costly in-store execution errors that are draining billions from the industry. A report by Coresight Research—developed with technology partners Simbe and RELEX Solutions—puts a precise figure on these operational gaps.
These inefficiencies eat up 6.4% of total sales sector-wide. In 2026, the hardware, mass merchandise, and grocery segments will lose $196.4 billion to these failures. That loss figure is climbing 21% year-over-year, dwarfing the sector’s overall projected sales growth of just 3%.
Nearly all retailers—90%—are struggling with shop floor management. Empty shelves and wrong prices are squeezing operating margins. More than five percent of margins are being eroded for 89% of businesses.
Store intelligence platforms are now fully operational in 60% of enterprise locations, marking an 18-percentage-point increase from last year.
Pilot programs make up only 18% of current activity, with adoption heavily concentrated among large enterprises. Fully scaled deployments are in place at 73% of retailers with over $5 billion in annual revenue.
Mid-market retailers are falling behind—only 42% of companies under $1 billion have reached the same level of maturity. Treating physical stores as separate from digital channels hurts customer lifetime value. Investment is focused on out-of-stock detection, automated pricing, planogram compliance, and assortment optimization.
Production deployments in hardware and grocery
BJ’s Wholesale Club offers a clear example of shelf digitization in action. The company rolled out Simbe’s robotic systems to track inventory and pricing accuracy across its stores.
Leadership leveraged this hardware to create digital twins of its warehouse clubs, establishing real-time visibility that was previously missing from physical operations.
BJ’s used these digital models to optimize routing for online and curbside orders. The engineering team saw a 40% year-over-year jump in picking efficiency thanks to this data. CEO Bob Eddy noted the tech helped the company raise quality standards in fresh categories.
Albertsons is applying AI to streamline complex retail operations, targeting $1.5 billion in productivity gains over three fiscal years. CEO Susan Morris stated: “We’re equipping our merchants with AI-driven insights and automated execution to refine pricing, promotions, and assortment decisions—transforming category management and boosting margins.
“Our vision is a future where intelligent automation guides these decisions, freeing our teams to focus on strategy and innovation.”
Flaws in deployment sequencing
Many companies are jumping straight to pricing software without first investing in the underlying sensor infrastructure. Pricing optimization tools are the top priority for 43% of tech leaders surveyed.
Supplier collaboration platforms come second, drawing investment from 36% of retailers. Yet only 33% are investing in the shelf digitization hardware needed to feed accurate data into those pricing systems.
This hardware includes the sensors and cameras that verify actual stock on shelves. Store intelligence deployments must follow a strict sequence to work: first digitize the shelf, then layer on analytics, inventory tracking, and finally pricing automation.
Reversing this order leads to downstream data errors. Markdown algorithms rely on outdated inventory counts when physical tracking sensors aren’t in place. Mispricing rates hit 13% in 2026—a four-point rise since 2024.
Pricing and promo execution remains the biggest challenge, cited by 92% of operators. Kim Anderson, VP of Store Operations at Schnucks Markets, emphasizes that shelf data must come first—without accurate physical inventory tracking, downstream tools can’t deliver results.
Out-of-stock issues are still highly disruptive, with 52% of operators ranking inventory availability as a top concern. Many are trying to fix too much at once—40% are investing in three or more operational fixes simultaneously.
Labour reallocation and efficiency metrics
Lowe’s showcases the financial upside of automating associate workflows through its ‘Perpetual Productivity Improvement’ program. Executive VP of Stores Joseph McFarland led the rollout of workforce management and inventory tools to cut redundant tasks.
The initiative saved 80 non-productive labor hours per store each week. Lowe’s then advanced further with AI-powered shelf replenishment tech that tracks stock depletion in real time.
The company rewarded staff with financial bonuses tied to proven productivity gains—$5,000 for store managers and variable payouts for hourly associates.
Industry-wide data backs up Lowe’s results. Intelligence tools are driving a 14% average drop in time spent on manual store tasks, with 86% of companies reporting measurable reductions.
Performance varies by company size: 56% of retailers with over $5 billion in revenue report significant time savings, versus just 36% of mid-market firms.
Operational efficiency is the top investment goal, followed closely by unifying store data. Retailers also expect these tools to unlock new revenue—40% are eyeing opportunities like retail media networks.
Securing market competitiveness
Store intelligence tech works as a connected ecosystem—not a patchwork of isolated fixes. Deploying it without a clear sequence means building on shaky ground.
Real-time, shelf-level visibility is essential before scaling any downstream software. Pricing automation, supplier collaboration, and inventory forecasting all depend on verified physical data to work accurately.
Customers notice when operations improve. Proper deployments lift customer lifetime value by 11% across the sector, and half of retailers using physical automation see higher conversion rates.
Loyalty program sign-ups rise for 48% of companies after integration, and 47% report better online reviews thanks to accurate pricing and consistent stock.
Retailers that combine properly sequenced hardware and software gain a clear edge over competitors stacking disconnected tools.
See also: HSBC expands AI banking partnership with Google Cloud
Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London. The comprehensive event is part of TechEx and is co-located with other leading technology events including the Cyber Security & Cloud Expo. Click here for more information.
AI News is powered by TechForge Media. Explore other upcoming enterprise technology events and webinars here.
