Operational Excellence (OPEX) Insight – Tuesday, January 20, 2026: AI Is Reshaping Global Supply Chain Operations Toward 2026.
Góc Nhìn Vận Hành Xuất Sắc – Thứ Ba, Ngày 20/01/2026: AI Tái Định Hình Chuỗi Cung Ứng Toàn Cầu Hướng Tới Năm 2026.
Welcome To Operational Excellence (OPEX) Insight Article For The Paid Subscriber-Only Edition.
This is the bilingual post in English and Vietnamese. Vietnamese is below.
Đây là bài viết song ngữ Anh-Việt. Tiếng Việt ở bên dưới.
English
PART 1 – OFFICIAL INFORMATION
During the 2024–2026 period, artificial intelligence (AI) is being recognized as one of the fastest-adopted technologies with the most far-reaching impact in global supply chain management. According to official reports from leading research and consulting organizations such as Gartner, McKinsey, BCG, Deloitte, and the World Economic Forum, AI is no longer viewed as a localized support technology, but is gradually becoming a core operational capability in modern supply chains.
Industry reports indicate that AI is being widely deployed across many critical stages of the supply chain, including demand forecasting, supply planning, inventory management, logistics coordination, warehouse operations, and quality monitoring. Rather than serving only descriptive analytics models, AI is increasingly integrated to support predictive analytics and prescriptive decision-making in near real time.
One clearly confirmed trend is that AI is gradually replacing or significantly reducing manual processes that traditionally rely heavily on individual experience and fragmented data handling. Modern AI systems are capable of automating supply chain workflows end-to-end, from multi-source data collection and data cleansing to demand variability analysis and recommendations for order planning or inventory allocation adjustments. This enables enterprises to reduce their dependence on long planning cycles and slow reaction times.
In forecasting and planning, official reports note that AI is improving forecast accuracy by combining historical data with real-time data, market signals, weather factors, geopolitical developments, and customer behavior indicators. Research organizations emphasize that AI does not completely eliminate traditional forecasting, but allows enterprises to shorten planning update cycles and respond more flexibly to volatility.
In warehouse operations, AI is increasingly applied through computer vision, machine learning, and robotics. Reports from Gartner and Deloitte indicate that computer vision is being used to automatically identify goods, monitor inventory, detect handling deviations, and optimize storage space. These applications help accelerate goods processing, reduce manual errors, and increase transparency in warehouse operations.
In logistics and transportation, AI is deployed to optimize routing, predict delivery times, manage fleets, and coordinate resources. Industry reports emphasize that AI enables supply chains to respond more quickly to disruptions such as transportation congestion, fuel cost volatility, or sudden changes in demand. Instead of situational reactions, enterprises can make decisions based on data and machine-learning models.
One point consistently emphasized across official publications is that AI is not being implemented to completely replace humans, but to enhance the operational capacity of the system. AI handles repetitive tasks, processes large volumes of data, and supports decision-making, while humans focus on risk management, exception handling, and strategic coordination.
From an investment perspective, reports show that enterprises are shifting from purchasing standalone AI tools to building end-to-end integrated data and AI platforms for supply chains. This reflects a change in implementation mindset—from technology experimentation to rebuilding data-driven operational capabilities.
Official sources indicate that the outlook for AI in supply chain management through 2026 does not lie in showcase-style breakthroughs, but in AI gradually becoming an inseparable part of operational systems, helping enterprises manage complexity, reduce latency, and enhance adaptability in an increasingly volatile business environment.
