Winning Through Process: AI Rewires the Efficiency DNA of Retail Enterprises

The recently released industry report "AI-Driven Retail Nirvana: The CIO's Strategic Blueprint for Omnichannel Retail & Intelligent Growth" by the Burgeon Research Institute points out that AI transformation for retail enterprises does not happen overnight. It clearly progresses through three sequential stages: Data Foundation, Process Efficiency, and Model Innovation.

Today, we focus on the second stage—Process Efficiency. Once a company has completed initial data governance and system integration, the next major battle is to use AI as a "scalpel" to meticulously scan and reconstruct complex business processes.

I. Why "Process"?

Over the past decade, all innovation in China's retail industry has essentially been "channel innovation." From offline stores to e-commerce platforms, and then to live streaming and private domains, each channel expansion brought new growth—but also left behind more complex process gaps and data silos.

Which channel did the order come from? Which warehouse should fulfill the inventory? How do membership benefits work across channels? How should settlements be accurately split? These seemingly basic business processes, in today's fragmented channel landscape, have become the biggest black holes devouring efficiency, driving up costs, and harming customer experience.

At the heart of every retail problem lies inventory. And behind inventory problems lie countless fragmented, inefficient processes that rely on manual judgment.

II. Traditional Workflows Are Being Redefined

As a digital service provider with 26 years of deep expertise in the retail industry, Burgeon has served over 5,000 retail brands. We have witnessed the entire evolution of business processes—from paper-based to system-driven, and now to intelligent.

Traditional ERP or middleware platforms defined "how processes should run." But in the AI era, the authority to define processes is shifting from "system presets" to "real-time business drivers." Processes are no longer rigid assembly lines, but intelligent agents capable of sensing, deciding, executing, and self-optimizing.

What does this mean?

From "people finding tasks" to "tasks finding people": The system can automatically alert on inventory anomalies, identify fulfillment bottlenecks, and push tasks to the most suitable person.

From "fixed processes" to "dynamic orchestration": In sudden scenarios like "live-streaming flash sale – urgent store fulfillment," the system can automatically combine order, inventory, and logistics workflows to achieve optimal fulfillment.

From "experience-driven" to "data-driven": Replenishment, transfer, and pricing no longer rely on store managers' intuition, but on AI models that generate recommendations based on multidimensional data such as real-time sales, weather, and competitor activities.

This is the direction Burgeon has been continuously evolving toward in products like its Omnichannel Business Middleware and Intelligent OMS: building omnichannel transaction capabilities that remain robust amid constant change. Whether orders come from Tmall, Douyin, or mini-programs, and whether inventory sits in central warehouses, stores, or cloud warehouses, the system can automatically receive, intelligently assign, and accurately settle them.

III. The Industry Pain: An "Invisible Ceiling" on Efficiency

A set of data from the "AI-Driven Retail Nirvana" report reveals widespread anxiety in the industry: retail executives expect AI's contribution to revenue growth to increase by 135% by 2027. Yet 71% of retailers cite cost as the biggest barrier to integrating generative AI.

The contradiction: Companies know AI is the future, but are stuck in the present—unsure where to invest to generate real efficiency gains.

The report further notes that AI budgets in retail are growing at 19%, with 51% of that growth originating outside IT departments. This sends a strong signal: business units' hunger for efficiency has moved ahead of technology procurement. Merchandising, marketing, and operations teams are no longer satisfied with passively using tools; they are actively seeking solutions that can directly optimize their daily work using AI.

The pain point is clear: companies don't lack systems. What they lack are "intelligent processes" that can connect systems, run through the business, and continuously self-optimize.

IV. Industry Practice: From "Point Solutions" to "Holistic Optimization"

Process efficiency is not empty talk. It happens in every concrete business scenario.

Case 1: The "Process Mining" Revolution in Luxury Retail

For high-end fashion brands, customer service experience is paramount. By introducing Process Mining technology, they gained deep visibility into the entire chain of order fulfillment and complaint handling. Like an X-ray, AI precisely identified redundant steps and abnormal paths causing delays. Through subsequent automated interventions, the brand successfully reduced average resolution time for customer service issues by 90%, and lowered cost-per-resolution by 46%. This confirms our view: Hyperautomation should not be launched blindly—process mining is the essential first step toward precise, high-ROI operational optimization.

Case 2: From "Inaccurate Forecasting" to "Intelligent Replenishment"

Accurate sales forecasting in the apparel industry has been jokingly called "mission impossible," influenced by countless non-linear variables like weather, trends, and social media. During the process efficiency stage, companies began applying AI large models here. AI-based solutions can integrate historical sales data, real-time weather, regional heat maps, and even trending Xiaohongshu posts to generate dynamic replenishment recommendations. While 100% accuracy remains elusive, their ability to react quickly mid-season and reduce risks of stockouts and overstocks already far surpasses traditional manual experience. At its core, this is using AI to reconstruct the decision-making nodes of the core business process chain: "merchandise planning – procurement – replenishment."

Case 3: Turning Every Sales Associate into a "Super Individual"

In stores, complex POS operations and membership systems were once a nightmare for new hire training. Burgeon's "AI Cloud Assistant" transforms system operations into natural language conversations. A sales associate simply says, "Check if this shoe is available in size 36" or "Add points for member Mr. Zhang," and the system automatically performs the query and action. Tens of hours of training are compressed into "just say it." This is not just a tool upgrade—it reshapes the "service process" from rigid click-by-click steps into a more human, efficient interactive experience.

V. Winning Through Process: Succeeding on the Second Curve

The second stage of AI transformation—"Process Efficiency"—is a quiet but profound efficiency revolution. Its goal is not disruption, but optimization; not replacing people, but empowering them.

By deeply embedding AI into every business process node—from demand forecasting and intelligent fulfillment to store operations and customer service—enterprises can:

Cut hidden costs: Reduce manual intervention, lower error rates, and optimize inventory turnover.

Increase operational resilience: Faced with sudden traffic spikes or supply chain disruptions, the system can automatically allocate resources to keep business running smoothly.

Unlock talent value: Free employees from repetitive, tedious tasks so they can focus on creative marketing, service, and customer relationship building.

What accumulates through this process is not just short-term cost reduction and efficiency gains, but the organizational muscle memory and data assets needed for future "model innovation." When processes are intelligent enough and data flows smoothly enough, innovation ceases to be a gamble and becomes a natural outcome.

The era of winning through process has arrived. Is your enterprise ready to rebuild every business process with AI?

This article is based on the core findings of the Burgeon Research Institute report "AI-Driven Retail Nirvana: The CIO's Strategic Blueprint for Omnichannel Retail & Intelligent Growth." The report details a three-stage retail AI transformation model and includes additional industry data, trend analysis, and full customer case studies. Download the full report for free and unlock your intelligent growth blueprint.