As the supply chain ecosystem continues to navigate the unpredictable waters of macroeconomic turbulence, Gartner has unveiled its list of the top 10 technology trends that Chief Supply Chain Officers (CSCOs) in Asia should focus on to enhance operational efficiency in 2025. This comes as companies face challenges from geopolitical uncertainties, ongoing transformation initiatives, and relentless cyber threats.
According to Gartner, these trends emphasize the transformative potential of connectivity and intelligence within supply chains, enabling leaders to enhance operational efficiency and adaptability. Christian Titze, VP analyst and chief of Research in Gartner’s Supply Chain practice, stated, “This year’s trends highlight the transformative potential of connectivity and intelligence in supply chains, enabling leaders to enhance operational efficiency and adaptability.”
One of the standout trends is the rise of Agentic AI, which offers a virtual workforce of intelligent agents capable of making autonomous decisions. This innovation allows CSCOs to optimize inventory management and enhance responsiveness to real-time demand fluctuations. By leveraging Agentic AI, organizations can gain a competitive edge through improved adaptability and efficiency.
Another key trend is Ambient Invisible Intelligence, which utilizes ultra-low-cost smart tags and sensors. This technology provides real-time visibility into end-to-end supply chains, allowing for large-scale tracking of goods, particularly perishables. Enhanced traceability not only ensures compliance with environmental regulations but also strengthens overall supply chain integrity.
The Augmented Connected Workforce (ACWF) is also gaining traction among supply chain executives. By digitizing standard operating procedures and employing digital tools, organizations can improve decision-making accuracy while addressing the skills gap prevalent in today’s workforce. ACWF initiatives streamline employee onboarding and boost productivity across manufacturing and logistics operations.
Furthermore, the introduction of a Multimodal User Interface (UI) transforms how users interact with supply chain systems. This technology enhances user experience by allowing communication through various modes, such as voice commands and gesture-based controls, which not only improve driver safety but also enhance overall operational efficiency.
Polyfunctional Robots represent another exciting development within the supply chain. These versatile machines can perform multiple tasks, from sorting to packaging, thereby reducing reliance on human labor. Their adaptability makes them invaluable in warehouses, where efficiency is paramount.
Moreover, Autonomous Data Collection technologies, including drones and mobile robots, are revolutionizing data capture in supply chains. By automating inventory checks and other data-gathering processes, these tools significantly enhance productivity while minimizing manual errors and risks.
Decision Intelligence (DI) and Intelligent Simulation are set to change the decision-making landscape. DI combines various analytical tools to support and automate decisions, while intelligent simulation integrates AI and machine learning into traditional models, providing enhanced predictive capabilities. These technologies empower CSCOs to optimize logistics routes and improve overall cost efficiency.
As the supply chain landscape evolves in 2025, these emerging technologies will play a crucial role in enabling CSCOs in Asia to navigate complexities and drive innovation. By prioritizing these trends, leaders can position their organizations for success in an increasingly competitive environment.
In late 2022, the introduction of ChatGPT marked the beginning of a global acceleration in AI development. By the end of 2024, the number of large-scale AI models worldwide had surpassed 1,300, with China and the United States collectively holding 80% of the market share. The U.S., leveraging its technological strength and innovative capacity, remains at the forefront of large AI model development, while China has quickly emerged as a formidable competitor, bolstered by its vast market and proactive government support.
As of 2025, China has over 300 domestically developed large AI models. However, the country faces significant challenges in developing truly original AI large models. According to a senior analyst at ANBOUND, “large AI” refers to general-purpose large models, while “small AI” refers to smaller models designed for specific application scenarios. The development of “large AI” in China is hindered by high costs related to computing power, energy, and finances, as well as security concerns such as data leaks.
In contrast, China holds local advantages in developing “small AI” models, which are expected to continue emerging as new competitors. The use of AI is set to become a trend, particularly in the training industry and some low-risk sectors. AI offers distinct advantages in training, including vast knowledge reserves and the ability to create personalized learning plans.
However, the healthcare sector presents high risks for AI applications. The complexity and low tolerance for error in medical scenarios pose significant challenges, particularly due to the limited quality of medical data used to train AI systems. Inaccurate patient descriptions can lead to compromised AI responses, potentially endangering lives.
As AI becomes more widespread, traditional search apps like Baidu are facing a survival crisis and may eventually have to rely on AI. This shift marks a transition from keyword-based searches to natural language communication with AI, which could diminish the competitive edge of traditional search engines.
The rise of AI computers is also expected to lead to the decline of traditional “dumb computers” by 2026 to 2028. AI computers will break down language barriers and improve work efficiency, but progress in China has been slow due to technological restrictions.
In the e-commerce sector, AI-driven shopping optimization is intensifying competition as platforms like JD.com and Pinduoduo integrate AI to enhance user experiences and operational efficiency. The future success of these platforms will heavily depend on their AI capabilities.
Ultimately, as AI continues to develop, it will gradually transform society, influencing production and lifestyles. This transformation is not sudden but a gradual process, reshaping the trajectory of human civilization. The trends reflected in the AI landscape indicate both immense potential and challenges that will shape the future of AI in China.
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