In 2023, the global supply chain management market size was valued at $23.58 billion. Now, the market is projected to grow from $26.25 billion in 2024 to $63.77 billion by 2032, exhibiting a CAGR of 11.7 percent during the forecast period.
This growth means only one thing: supply chain complexities are about to increase. With Southeast Asia and the Asia-Pacific region emerging as important hubs for manufacturing, trade, and e-commerce, businesses are under pressure to enhance operational efficiency, meet growing consumer expectations, and minimize environmental impact.
When it comes to AI’s potential, many businesses find themselves at a crossroads, uncertain about when, where and how to weave AI into their complex operations.So what should the supply chain sector do when they think of weaving AI applications in their industries?
It is all about the right parameters
AI’s computational power far surpasses human cognitive capacity, making it tempting for companies to apply technology indiscriminately to every problem. However, to fully realize AI’s potential in the supply chain, building a robust foundation is essential.
When it comes to sustainability, it can’t be achieved through traditional methods of supply chain management alone. The integration of AI is necessary to manage the vast amounts of data, particularly emission data, and to address the persistent challenges in supply chain visibility.
The effectiveness of machine learning algorithms depends on setting the right parameters. This requires a clear understanding of the specific goals and characteristics of the challenges the AI is meant to address.
Rather than attempting to tackle every issue, this targeted approach enables companies in Southeast Asia to prioritize and solve the most critical problems with precision. For instance, if a client has thousands of SKUs and global inventory in the millions, they need to focus on parameters such as cycle days, lot sizes, and number of production plants to help them determine the right mix of regional distribution centers for a particular product line.
Investing time in defining these parameters not only enhances efficiency but also prevents organizations from spreading their efforts too thin. By focusing on what matters most, companies can integrate AI in a practical, impactful way.
Predictive AI in supply chain visibility
From the solutions we work with, explainability is a fundamental pillar of our approach to AI – for example, our advanced demand sensing and forecasting solution, Demand.AI, has been carefully designed to improve user adoption and acceptance of machine learning-generated results with easy-to-interpret visualizations that explain which data features affect demand predictions.
By showing them the “why” behind an AI-generated prediction or recommendation, planners are more likely to trust and embrace the outcomes.
As well as driving more widespread adoption, this allows for increased confidence in decision-making and a healthy balance between human expertise and AI capabilities.
The role of AI in risk management
Due to AI’s predictive capabilities, AI has been used more frequently in coming up with innovative solutions for complex problems.
AI enables companies to identify risks earlier, streamline manufacturing processes and make informed decisions to mitigate product shortage challenges much more quickly than traditional methods.
By identifying the risk of possible shortages before they happen, supply chain shortages can not only be mitigated but even prevented. AI will alert the company of the upcoming risk, allowing them to make an informed decision around what action to take.
Some of our key solutions like Maestro has even allowed life sciences companies to use AI to simplify multi-year supply chain planning, predict and plan for future scenarios with smart modeling, and gain a comprehensive, always-on digital view of your supply chain to ensure maximum agility.
How is AI reshaping the logistics and supply chain industry in Southeast Asia and Asia-Pacific region?
AI is having a significant impact in reshaping the logistics and supply chain industry in Southeast Asia and Asia-Pacific region, especially within manufacturing and healthcare.
The manufacturing sector is using AI to enhance predictive maintenance and optimize supply chains while the healthcare industry is exploring early disease detection and improving patient outcomes. Other industries seeing a significant impact in Southeast Asia and Asia-Pacific include financial services, retail and e-commerce, and urban development.
Businesses embracing AI will need to ensure that they are nurturing talent and fostering a culture that is conducive of learning and talent development – this will allow for more growth and innovation within APAC.
Phillip Teschemacher is President (APAC) of Kinaxis.
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