Artificial intelligence is profoundly reshaping the underlying logic of the retail industry, and the digital transformation of the sector has officially entered an in-depth AI application phase. At present, the intelligent upgrading of many retail enterprises is trapped in a development dilemma characterized by "overemphasis on concepts while neglecting implementation, possession of technology without incremental benefits". Pain points including scattered AI pilots, disconnection between technology and business, unquantifiable value and barriers to large-scale deployment have become core challenges restricting the long-term growth of brands.
At this critical juncture of industrial transformation, the Burgeon BEYOND User Conference themed "StarConverge, Smart-Drive for the Future" has concluded successfully. Bringing together leading retail brands, seasoned digital transformation practitioners and cutting-edge technology experts, the conference centers on the core themes of commercial AI implementation and business value enhancement. It hosts multi-dimensional, in-depth idea exchanges and technical sharing, delivering systematic, implementable and reusable new solutions for the intelligent transformation of the retail industry.
△ Sun Yihui, Chairman of Burgeon
Sun Yihui, Chairman of Burgeon Technology, put forward the core AI transformation philosophy of "Focus on Business Rather Than Mere Figures" from an overarching industry perspective, targeting the key drawbacks of AI adoption across the sector. He noted that most current AI tools only support basic data reading and fail to fully comprehend enterprises’ real business logic, creating an inherent gap between data inquiry and operational decision-making. Compared with failed AI responses, plausible yet false outputs generated by models constitute the primary hidden risk for corporate digital transformation.
To address this pain point, Burgeon Technology unveiled its new brand "pient" and launched the business analytics AI product "Retail Brain". Rooted in ontology, it abandons the rigid data script generation approach of conventional AI and establishes multi-layered trustworthy governance mechanisms. It achieves end-to-end connectivity with core business systems including ERP, POS and CRM, converting fragmented data into verifiable, traceable and reliable business assets. He stressed that AI transformation is far more than tool iteration; it lies in the intelligent reconstruction of business logic. Enterprises need to evolve from "passively querying data" to "proactively understanding business", setting a new value benchmark for the implementation of trustworthy AI in the industry.
△ Li Hao, Director of Solution Department, Burgeon
Li Hao, Director of Solution Department of Burgeon Technology, delivered an in-depth interpretation of the chaotic landscape of AI implementation in the industry. He pointed out that the AI initiatives of most retail enterprises today fall into the trap of blind trial and error. Although tools such as intelligent Q&A, data reporting and AI content creation have been rolled out one after another, they have failed to deliver the core goals of improved manpower efficiency, operational optimization and business growth.
The Enterprise AI "Self-Driving" White Paper puts forward a five-level L1-L5 AI self-driving capability grading model. It breaks the traditional technology-oriented development mindset and advocates a scientific transformation path for enterprises: "define capability level first, select application scenarios, build technical foundation, and close the value loop". Equipped with standardized grading metrics, implementation criteria, a full business landscape map and an enterprise AI self-assessment toolkit, the white paper provides a full-lifecycle guidance system for retail businesses. It fundamentally addresses industry pain points including disorganized AI development, ambiguous investment returns and untraceable value, and propels industrial AI development from extensive trial-and-error into a new phase of refined value-driven operation.
△ Chen Yulu, CTO of Burgeon
Chen Yulu, CTO of Burgeon Technology, officially launched the UnionStar enterprise-grade agent platform on site, which precisely solves four core challenges in retail AI implementation: difficulties in adapting to business systems, weak comprehension of industry business semantics, fractured cross-department end-to-end execution, and the failure to accumulate corporate business expertise. He proposed five core acceptance criteria for AI deployment — "comprehend requirements, connect systems, execute tasks, retain knowledge, and enforce governance", redefining the benchmarks for enterprise AI rollout.
Built on a lightweight pluggable architecture, UnionStar can rapidly activate existing digital assets without overhauling enterprises’ current IT infrastructure. Powered by a multi-agent collaboration engine and visual scenario canvas, it supports one-click initiation of business commands via natural language and automatic orchestration across multiple systems including ERP and WMS, covering key retail scenarios such as replenishment, inventory management and store operations. Meanwhile, the platform accumulates standardized business knowledge assets to form an iterable business growth flywheel. Coupled with a security framework featuring private deployment and full audit trails, it helps retail AI evolve from isolated scenario pilots into full-link, large-scale delivery of business value.
△ Sky, Business Partner of X-Sigma
Sky, Business Partner of X-Sigma, focused on real-world retail AI implementation scenarios and corrected prevalent misconceptions in the industry. He stated that AI is an enabling tool for transformation rather than an end goal. The core of intelligent development lies in boosting operational efficiency and driving business value growth, and AI capabilities should not be blindly added to every business scenario. He categorized retail AI implementation into three tiers: process automation, AI-assisted efficiency improvement, and AI-native innovation, advocating a lightweight rollout strategy of "automation first, iteration on demand".
Drawing on hands-on experience with Codex technology, Sky illustrated how intelligent coding agents reshape enterprise software development, substantially cutting the development costs of niche business systems and revitalizing scenarios with low return on investment. He also broke down the four-stage evolution path of retail businesses: digitalization, automation, intelligence, and Agent-native applications. He suggested that enterprises should center on business pain points, leverage AI to enhance organizational agility, and steadily deploy AI-native capabilities such as personalized user operations and intelligent scenario marketing to achieve sustainable long-term value growth.
The roundtable session brought together representatives from retail brands, digitalization experts and Burgeon technical consultants. Centered on the theme "In the AI Self-Driving Era, How Can Enterprises Enter the Fast Lane of Growth", the participants held in-depth discussions and explored practical pain points of enterprise AI implementation based on frontline retail cases.
The guests exchanged views on topics including AI application deployment in retail scenarios, organizational capability building, business value realization and risk management, and shared transformation experience from isolated AI pilots to full-link intelligent operations. The white paper also delivers a methodology for AI implementation for retail enterprises, helping brands avoid transformation pitfalls. With systematic AI capabilities, brands can improve quality and efficiency of business and embark on the fast track of high-quality growth.
With 27 years of deep cultivation in retail digitalization, Burgeon Technology has always stood at the forefront of industrial transformation. Centered on technological innovation and guided by business value, it continuously empowers retail brands to achieve full-link digital upgrading.
Going forward, Burgeon Technology will keep advancing AI R&D and scenario-based implementation, iterating its product portfolio and solutions to tackle persistent transformation challenges in the industry. It will help more retail enterprises make progress in intelligence and digitalization, consolidate growth momentum and seize opportunities amid industrial shifts.
2026/06/08 周一 17:16
