Solink, a leader in AI-driven video intelligence, has released its new research report, The State of AI in Retail, highlighting how artificial intelligence is rapidly reshaping retail operations, loss prevention, workforce efficiency, and the customer experience. The findings point to a decisive shift in the industry, as AI moves from experimental pilots to a foundational component of modern retail strategy.
Based on a survey of 150 retail decision-makers across the U.S., Canada, and the U.K., the report shows that AI adoption has reached a tipping point. More than 80% of retailers are already budgeting for AI initiatives, while 86% plan to increase spending over the next 12 months. The research was released as retailers and technology providers convene at NRF 2026 in New York, where AI and automation are central themes.
“The data is clear: AI is no longer experimental in retail, it’s foundational,” said Michael Scott, CMO at Solink. “Retailers are moving quickly to unify video, data, and AI so they can operate more efficiently, reduce loss, and deliver safer, more consistent customer experiences.”
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The report reveals that 65% of surveyed organizations now regularly use generative AI—nearly double the adoption seen year over year. Investment is being prioritized in areas directly tied to the industry’s most pressing challenges, including labor shortages, theft, increasing operational complexity, and the need for real-time visibility across stores.
Across retailers of all sizes, operational efficiency, labor cost reduction, and customer experience ranked as the top three drivers of AI adoption. Mid-size retailers, defined as those operating 200–499 locations, are showing the fastest acceleration. Every retailer in this segment plans to increase investment in labor optimization, and nearly half report strong confidence in scaling AI across their organizations. Larger retailers with more than 500 locations lead in overall budget commitment but face challenges around governance, talent, and internal AI expertise.
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AI adoption is also expanding across multiple retail functions. Asset protection teams are using AI to detect fraud patterns and anomalies in transactions and store activity. Operations teams are applying AI to improve demand forecasting, optimize labor deployment, and enhance store performance. IT departments are leveraging AI for system health monitoring and infrastructure stability, while physical security teams rely on AI-driven insights to improve situational awareness and response times.
At the same time, the report highlights a growing risk of AI fragmentation. Many teams are adopting AI independently, without a shared data model or unified platform, creating inefficiencies and overlapping tools. This fragmentation presents an opportunity for retailers to consolidate technologies and modernize their stacks around integrated AI platforms.
One of the most significant shifts identified in the report is the move from traditional video surveillance to vision intelligence. Retailers are increasingly using AI-powered video as a real-time operational dataset rather than a reactive security tool. Video intelligence is now being applied to staffing optimization, transaction validation, compliance monitoring, faster investigations, and improving both employee and customer experiences—especially for mid-size and enterprise retailers facing shrink, organized retail crime, and rising operational complexity.
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