第14届全国消费品CIO年会圆满闭幕！CIO组织2026年底、2027年活动计划重磅公布！

You can focus on key takeaways from the conference, actionable best practices, and upcoming industry events to quickly catch up on the latest developments in digital and intelligent transformation across the consumer goods sector.

1. Core conference details: The 14th National Consumer Goods CIO Annual Conference, held on September 18, 2026 in Guangzhou, is the highest-level, largest and most influential CIO gathering in China’s consumer goods industry. It drew over 600 IT executives from consumer goods enterprises across the country, covering sub-sectors including food and beverage, beauty and personal care, home goods, apparel and footwear. Attendees exchanged insights on AI-powered digital transformation under the theme "Intelligent Agents, Restructuring, Leapfrog Growth".

2. Actionable best practices for reference: Dozens of leading companies such as Jianlibao, Liby, Xtep and Hengan shared their real-world AI implementation paths, while a range of service providers presented replicable efficiency improvement solutions. Examples include unified network management to reduce multi-store operating costs, AI-powered document review that boosts auditing efficiency by 80%, and intelligent middle platforms to support scalable AI business deployment.

3. Upcoming events: A pharmaceutical and healthcare industry CIO annual conference will be held in Shanghai between November and December 2026. In 2027, a series of digital and intelligent transformation conferences covering consumer goods, advanced manufacturing and other tracks will be held in Shanghai and Guangzhou, which you can follow based on your interests.

This conference gathered extensive cutting-edge practices in digital and intelligent transformation across the consumer goods industry, providing high-value references for your brand marketing, operation optimization and strategic transformation planning.

1. New approaches to brand marketing and user operation: Marketingforce’s AI Agent solution helps brands break through bottlenecks in marketing execution. Sensors Data has built a closed-loop growth framework covering business insight, strategy generation and execution optimization, with proven results including higher attach rates for fresh produce and improved user operation efficiency. TOYUN Tech proposed building a unified, trusted data foundation centered on product QR codes to enable smoother rollout of intelligent marketing and more accurate decision-making.

2. Full-value-chain transformation references: CIOs from dozens of leading consumer brands including Procter & Gamble, COFCO Coca-Cola, Linshi Home and Vinda shared their AI strategies, implementation cases and management experience, covering organizational change, supply chain management, store operations and expense control. These cases can serve as benchmarks for your brand’s transformation roadmap.

3. Industry networking opportunities: In 2027, consumer goods industry digital and AI conferences will be held in Shanghai and Guangzhou, where you can connect with qualified service providers and learn proven practices from industry peers.

The AI implementation practices, risk reminders and event arrangements shared at the conference can help you identify efficiency improvement opportunities through digitalization, connect with cooperation resources, and avoid common transformation pitfalls.

1. Directly replicable efficiency solutions: For multi-store operations, Ansheng Internet’s unified, standardized network service portal can reduce network operation costs. For finance processes, adopting AI document review tools can increase auditing efficiency by 80% and cut manual workload by 60%. For chain stores, an AI + HR workbench enables smart scheduling, dynamic incentives and fast payroll calculation to reduce costs and lift efficiency. For supply chain operations, intelligent agent tools can cover scenarios including storage capacity management, container loading scheduling and receipt verification, closing the loop on execution.

2. Risk and opportunity notes: Companies including Cosmo Lady shared seven common pitfalls in AI implementation, noting that businesses should avoid blindly piling on AI tools and instead anchor transformation around actual business needs. The conference gathered over 600 senior decision-makers from leading consumer companies and dozens of high-quality digital service providers. The CIO organizing body will also host multiple cross-industry digital events going forward, where you can source products and service resources, and learn growth practices from top sellers.

The supply chain digitalization solutions, manufacturing enterprise transformation experience and upcoming event arrangements shared at the conference can provide references for you to optimize production and supply chain management, advance digital transformation, and access new business opportunities.

1. Digital implementation directions for production and supply chain: Dongyin Technology’s supply chain intelligent agent can be applied to storage capacity operation, receipt verification and container loading scheduling, forming a full closed loop from business perception and decision-making to execution and inspection, to help factories improve supply chain operational efficiency. Midea Group shared its experience building a multi-cloud unified Agent platform, which provides a practical reference for factories constructing their own AI technology foundations.

2. Proven pathways for digital transformation: Yunstoo noted that AI transformation should not simply layer tools on top of existing processes; instead, businesses should restructure workflows and reshape role capabilities around human-machine collaboration, to build a scalable, self-reinforcing AI operation system. Baison Software proposed the approach of "middle platform first, AI follow-up": first build an intelligent middle platform to accumulate reusable capabilities, then integrate AI into business closed loops.

3. Business matching opportunities: In 2027, advanced manufacturing digital and AI conferences will be held in Shanghai and Guangzhou, where you can connect with solution providers, learn transformation experience from peers, and access supply chain cooperation demand from downstream consumer brands.

This conference gathered industry-wide demand, pain points and outstanding practice cases in digital and intelligent transformation, helping you identify industry trends, pinpoint customer pain points and optimize your solution offerings.

1. Industry development trends: Multiple sectors including consumer goods, advanced manufacturing and pharmaceutical healthcare are comprehensively advancing AI-driven digital and intelligent transformation. The market has moved past the early phase of scattered, experimental AI tool adoption, and is now entering a stage centered on AI intelligent agents that deeply restructure business processes and organizational forms. Enterprises have strong demand for AI solutions that deliver measurable, implementable results.

2. Core customer pain points: Attendee enterprises widely face challenges including multiple bottlenecks in AI deployment, high costs from fragmented multi-store network management, low supply chain collaboration efficiency, hard-to-close marketing growth loops, low efficiency in back-office operations, and a lack of unified standards for AI applications. Many enterprises also noted that AI implementation is prone to cognitive pitfalls, leading to high trial-and-error costs.

3. Proven reference solutions: The conference awarded annual outstanding digital solutions across categories including unified network management services, data-driven growth closed loops, code-based marketing data foundations, intelligent middle platforms, AI document review tools and supply chain intelligent agents. These industry-validated solutions can serve as references for you to optimize your own service offerings.

The cross-enterprise digital transformation demand and cross-industry event arrangements disclosed at the conference can provide references for you to optimize platform services, conduct merchant acquisition and cooperation, and avoid operational missteps.

1. Core enterprise demands for platforms: As enterprises across consumer, manufacturing, pharmaceutical and other sectors advance AI transformation, they widely need integrated platform services that connect data, rules, processes and systems, covering scenarios including marketing growth, supply chain collaboration, human resource management, financial auditing and network operation and maintenance. The goal is to solve the pain point of fragmented AI tools that fail to form closed business loops.

2. Merchant acquisition and operation opportunities: The conference organizer has reach to 800,000 consumer goods industry IT executives and over 600,000 digital industry professionals across sectors. The upcoming Shanghai pharmaceutical and healthcare CIO conference in November-December 2026, and the 2027 digital transformation conferences in Shanghai and Guangzhou covering six tracks including consumer goods, advanced manufacturing, new energy and semiconductors, are high-quality venues for you to connect with enterprise clients across industries and carry out merchant acquisition and cooperation.

3. Risk avoidance notes: Enterprise demand for AI services has shifted from concept-driven to result-driven. When launching relevant services, you should avoid vague, concept-heavy AI marketing, and instead build solutions tied to real business scenarios that deliver quantifiable efficiency gains, to match enterprises’ core needs of process restructuring and organizational capability adjustment.

This conference gathered cutting-edge practices and core issues in digital and intelligent transformation across industries, providing rich first-hand samples for you to study new industry trends, summarize new models and identify emerging problems.

1. New industry trends: AI-driven digital and intelligent transformation has become a consensus across sectors including consumer goods, advanced manufacturing, pharmaceutical healthcare and new energy. The transformation is moving beyond early-stage superficial tool embedding, toward business restructuring and organizational leapfrog growth centered on "intelligent agents". Enterprises are widely exploring the development of self-controlled AI agents, unified data foundations and intelligent middle platforms, to turn AI from an efficiency tool into a core component of operational closed loops. AI Agents, multi-agent simulation, and human-machine collaborative organizational forms are current hotspots in transformation.

2. Emerging industry problems: Multiple participating enterprises noted common challenges in current AI implementation, including numerous deployment bottlenecks, prevalent cognitive pitfalls, lack of unified application standards, and difficulty achieving scalable replication. Many enterprises initially only layered AI tools on top of existing organizational structures without supporting process and organizational adjustments, leading to underwhelming transformation outcomes.

3. Business model innovation: A cohort of digital service providers have explored vertical-scenario AI service models, focusing on segmented scenarios including marketing, supply chain, finance and human resources. These providers have won customer recognition through quantifiable efficiency improvements, forming a new business paradigm for enterprise services.