Artificial intelligence is moving from experimental retail add-on to operational necessity, but the gap between ambition and impact remains wide. A recent industry picture, echoed by SAP Cloud One and The Commerce Team Global, suggests that roughly 89% of retailers are using AI in some form, yet only a small fraction have managed to scale it across the business in a way that delivers clear profit. That divide is less about access to tools than about whether retailers have the data fou...
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ndations, processes and governance to make the technology useful at enterprise level.
The issue is increasingly urgent because consumer discovery is changing fast. Euromonitor reported in March 2026 that AI-driven referrals to retail websites rose by 304% in 2025, far outpacing growth from other referral sources. Adobe Analytics, as cited in another 2026 report, went further, saying AI-driven visits to U.S. retail sites climbed 393% year on year in the first quarter of 2026, with those shoppers converting at higher rates and producing more revenue per visit. The message for retailers is clear: generative platforms are becoming part of the path to purchase, not just a curiosity at the margins.
That shift has implications well beyond marketing. McKinsey has warned that AI is changing the structure of retail itself, from how stores are designed to how shopping centres are managed, while stressing that physical locations still matter for certain customer interactions. The most successful operators, the consultancy argues, will be those that combine digital intelligence with in-person retail rather than treating them as competing models.
In practice, the most effective uses of AI in ecommerce are increasingly operational. Brands are using machine learning to improve pricing, inventory forecasting, fraud detection and customer support, while more advanced systems are beginning to automate campaign management and product catalogues. These tools can reduce false payment declines, cut the cost of overstocking and help teams react faster to changes in demand. The promise is not simply faster content production or smarter recommendations, but a more connected commercial operation.
Yet many retailers still struggle to move beyond pilot projects. The common failure point, according to several industry analyses, is fragmented data: AI is bolted on top of systems that do not share a single view of the customer, stock or margin. Without that integration, even sophisticated tools can create more complexity rather than less. Vendors and consultants increasingly argue that AI needs to be treated as part of the core operating model, not as a series of disconnected applications.
The commercial stakes are high enough that investment continues to rise. Nvidia said in its 2026 State of AI in Retail report that 91% of organisations are using or evaluating AI, and 90% plan to increase budgets this year. That spending, though, will matter only if it translates into measurable gains in revenue, productivity and service quality.
For retailers, the question is no longer whether AI belongs in ecommerce. It is whether they can build the infrastructure and discipline to turn adoption into advantage before customer behaviour moves on again.
Source: Noah Wire Services
