Retailers are operating in an environment that demands constant adjustment. Imports at major U.S. container ports are expected to remain below last year's levels through the first half of this year as retailers continue to navigate tariff uncertainty and changing sourcing strategies. At the same time, e-commerce sales reached $302.3 billion in the first quarter of this year, up 9.7% from the same period in 2025.
The pressure on inventory, sourcing, fulfillment, and pricing decisions continues to grow, and technology investment has grown with it. Global spending on enterprise transformation initiatives is expected to approach $4 trillion by 2027, while AI adoption accelerates across retail operations, supply chain planning, customer experience, and fulfillment.
Yet many organizations remain frustrated by the results. In fact, 89% of operations and supply chain leaders say their technology investments have not fully delivered the outcomes they expected.
The assumption is often that retailers need better software. In many cases, they already have it. The challenge sits elsewhere.
The hidden obstacles inside retail operations
Retailers have spent much of the past decade solving for scale. They invested in cloud platforms, forecasting tools, inventory systems, e-commerce infrastructure, and data platforms capable of handling enormous transaction volumes. Those investments were necessary. They enabled retailers to support growing online demand, increasingly complex fulfillment networks, and expanding product assortments.
What many organizations did not eliminate, however, were the operational workarounds that accumulated around those systems.
A fulfillment exception gets routed through multiple teams before action can be taken. Inventory decisions rely on spreadsheets maintained outside the system of record. Pricing changes require approvals that slow the organization's ability to respond to market conditions.
Each workaround exists for a reason. Together, they create drag. Retailers struggle to move as quickly as their technology should allow, and the cost is highest when conditions change unexpectedly. Inventory that appears balanced one month can become excess stock the next. A sourcing strategy built around one set of assumptions may need to be revised as tariffs, transportation costs, or consumer demand shift.
For retailers, the cost of those delays is substantial. Overstocks and out-of-stocks are estimated to cost the retail industry more than $1.7 trillion globally each year, a problem that extends far beyond inventory management alone.
Technology alone does not create agility when decisions remain trapped inside slow operational processes.
Why AI is exposing the problem
AI is often presented as the solution to operational complexity. In reality, it is exposing where complexity already exists.
Research has found that 88% of organizations now use AI in at least one business function. Generating insights is easier. Identifying patterns across large datasets is faster. Building software costs less than many organizations anticipated. Yet the gap between information and action remains stubbornly difficult to close.
An inventory planning model can identify a demand shift in minutes. A forecasting system can recommend adjustments before a planner would have spotted the issue manually. A fulfillment optimization engine can surface a more efficient routing decision almost instantly. Those recommendations still need to move through the organization.
Many retailers have spent years building processes designed to minimize risk through review, oversight, and escalation. Those structures made sense when information moved slowly and technology projects required months of planning and implementation. Today, they have become a source of delay.
This is one reason AI initiatives struggle to generate the value leaders expect. The technology can move faster than the organization surrounding it.
The bottleneck is no longer finding information. It is acting on it.
Building for responsiveness
Many transformation efforts still focus primarily on system replacement or platform modernization. Those initiatives have value, but they rarely address how decisions move through the business after the technology has been implemented.
In many cases, the first step is not another technology initiative. It is understanding where decisions slow down once information enters the organization. Retailers often discover that delays stem from approval processes, competing priorities, or operational handoffs rather than a lack of visibility. Identifying those bottlenecks can meaningfully improve responsiveness without a major change to the underlying technology stack.
A retailer may have sophisticated forecasting capabilities and near real-time visibility into inventory levels, yet still rely on multiple approval layers before adjustments can be made. Merchandising teams, supply chain leaders, finance departments, and store operations all have legitimate reasons for maintaining oversight. Over time, however, those layers make it difficult to respond when conditions change quickly.
That challenge becomes more visible as AI capabilities improve. The technology can surface potential actions far earlier than most planning cycles were designed to accommodate. Whether the organization can act on them remains a separate question.
Retailers have spent years investing in systems designed to provide greater visibility into their operations. Visibility remains important, but it is no longer the primary constraint. Most organizations can already see what is happening across their inventory, fulfillment, and supply chain networks. Converting that information into timely decisions is where progress slows, and where the greatest opportunity now sits.
Retailers do not lack data. They do not lack dashboards. Increasingly, they do not lack technology. What many still lack is the ability to turn information into action at the speed the market now demands.
