Most retailers aren't losing to competitors with better technology — they're losing to the friction between the technology they already have. Fifty-four percent of retail executives cite integration challenges as their primary barrier to AI adoption, more than budget constraints, talent gaps, or lack of ROI clarity. The data they need exists. The systems generating it don't talk to each other.
A recent survey conducted in collaboration with ServiceNow and Retail Dive's Studio by Informa TechTarget confirms the scale of the problem: previous technological upgrades have too often been built on top of one another, leaving systems siloed and unable to communicate — stalling progress on challenges that affect associates, brands, and customers alike.
“Retailers who stop adding point solutions and start connecting the ones they have will have a real advantage as AI capabilities continue to evolve,” says Ellie Quartel, head of global retail and hospitality at ServiceNow, an enterprise workflow and AI platform.
Back-to-front improvements
The path toward better serving customers starts with store operations. Inefficient processes result in associates manually addressing back-end concerns rather than attending to consumers. The combination of low inventory, increased wait times, and even higher frustration levels erodes confidence and loyalty among shoppers, who will take their business elsewhere if their in-store experience doesn’t match their expectations.
89% of retail executives report that their companies are at least somewhat reliant on manual processes and 72% believe that manual processes have moderately or significantly hindered their companies’ ability to achieve their operational goals.
Meanwhile, retailers who have already adopted AI-driven platforms are seeing positive results:
- 44% of retailers who've deployed AI report faster service and reduced wait times.
- 38% report more accurate inventory availability.
That connection isn't automatic. An inventory system may flag a replenishment gap, but without a workflow layer routing that signal to the right associate and closing the loop, the insight stalls. That's where platform thinking changes the equation.
Quartel sees a mindset shift underway among retailers who are making progress. "Retailers are starting to connect their back-end operational improvements to front-end customer outcomes in ways they weren't doing before," she says.
Where to start on your tech upgrade
Today’s retail success is built upon data. Employees, executives, and managers all require access to up-to-the-minute information to maintain proper stock levels, regulate staff schedules, and minimize reporting errors. While all of this information is already collected, it is often not stored in the same place. The fragmentation is the core cause of most pain points, according to Quartel.
“Most large retailers are running over 300-point solutions across their operations, and those systems rarely talk to each other in a clean, consistent way,” Quartel says. “When you try to build an AI model on top of that — or even just run a report — you're working with data that's incomplete, inconsistent, or siloed in ways that make it hard to act on.”
Quartel points to workforce planning as one concrete example of where connected data changes outcomes for store teams. When sales and scheduling data live in the same workflow, managers can match staffing to demand in real time — without manually pulling from multiple systems.
Another example Quartel cites is connecting sales records with maintenance workflows so operational disruptions get flagged and resolved without manual escalation. In that case, a low-stock alert can automatically trigger a replenishment task, notify the right associate, and update the customer-facing availability display without a manager having to manually coordinate the process.
“If your inventory data doesn't sync reliably with your store operations system, your AI-generated demand forecast will fail because it is only as good as the data feeding it,” says Quartel.
To that point, the ServiceNow study found that 40% of retailers cite data quality as a top barrier to AI adoption and 41% say investing in better data integration across systems is the single most impactful thing they could do to improve the ROI on AI. “Those numbers tell you this isn't a secondary concern. It's foundational,” Quartel says.
Set specific goals to prove ROI
The goal isn't a tech stack overhaul — it's connectivity. ServiceNow sits across existing systems, connecting workflows so information moves and work gets completed, without requiring retailers to rip out what's already running.
The most practical path forward usually starts with identifying where retailers' pilots are generating insights that can't be acted on because they're stuck in one system, says Quartel.
“If your inventory AI is flagging replenishment needs but that signal isn't connected to your task management workflow, you've built a dashboard, not a solution,” she notes.
Rather than waiting for an all-in-one solution that may never arrive, a best practice is to start with a workflow that already crosses two systems — something where a handoff between teams or tools is causing visible delay or error. Once that connection is fixed and the store is running noticeably smoother, retailers have their proof that the new platform delivers on its promise.
The measure of success isn't how well the technology performs — it's what changes in the business as a result.
“Your executives don't care about model accuracy,” says Quartel. “They care about fulfillment time, labor cost per transaction, task completion rates, and customer wait times.”
The retailers making real progress right now aren't waiting for the perfect integration architecture. They're identifying one workflow where a handoff between systems is causing visible delays, fixing it, and building from there. That's how pilots become platforms — and how operational efficiency becomes a competitive advantage.
See how ServiceNow helps retailers connect their existing systems, complete work automatically, and get associates back on the floor.
