AI & Machine Learning in Supply Chains: Building Competencies for a Resilient Future
What are key supply chain competencies, why they are essential, how these competencies can be used to optimise supply chain performance and how these key technologies can help.
Technology has been revolutionising supply chains globally over the past few decades. This rapid adoption has given rise to more advanced technologies such as Artificial Intelligence (AI) and Machine Learning (ML). These technologies, while improving efficiency, also creates resilience and adaptability in supply chains.
While companies are now working on adopting AI and ML on a larger scale, the need for strong supply chain competencies is becoming increasingly apparent.
In this article we will explore what are key supply chain competencies, why they are essential, how these competencies can be used to optimise supply chain performance and how these key technologies can help.
How AI and Machine Learning works in supply chain
AI and ML are essentially the brains behind many automated processes in supply chains. AI refers to the simulation of human intelligence in machines that can perform tasks such as decision-making, speech recognition, and visual perception. ML, a subset of AI, allows computers to learn from data without being explicitly programmed.
In demand forecasting: AI and ML can process a vast amount of data like historical sales, social media trends, and economic indicators to predict future demand. This helps businesses avoid having too much or too little stock and ensure smoother operations.
In inventory management: ML can check stock levels and product movement to better manage warehouses while AI tools can trigger automatic replenishment orders when stock is low.
In supply chain visibility: AI-powered platforms provide real-time insights into the movement of goods, allowing companies to monitor each stage of the supply chain. This visibility helps in identifying bottlenecks and proactively managing risks.
In logistics and transportation: AI can analyse traffic, fuel prices, weather conditions and route efficiencies to suggest the best delivery routes, making shipping faster and cheaper especially in the last mile which is one of the most expensive stages.
Why supply chain competencies are important
While AI and ML are powerful tools, their effectiveness largely depends on the competencies within the supply chain workforce.
These technologies cannot function in isolation—they need to be implemented, managed, and continuously improved by professionals who understand both the technical and operational aspects of supply chains.
Supply chain professionals need to know and understand how AI and ML work, what data is needed, and how to make decisions based on the results.
AI and ML depends on data and data literacy, both of which have become an essential component for supply chain professionals to know and manage in order to be able to analyse data correctly and isolate bad data which can lead to bad decisions.
AI and ML systems often require input and collaboration from all areas of business such as marketing, operations, and finance to ensure that these technologies are implemented in a way that it aligns with the company’s business and digital transformation strategy.
When used correctly, one of the key uses of technologies like AI and ML is that it can help provide insights into possible risks, but supply chain managers need the capability to understand these insights and make informed decisions to safeguard their operations.
Introducing AI and ML, however, may require substantial changes in how things are done, and supply chain professionals need to manage these changes smoothly to ensure smooth transition, staff buy-in and maximise the effectiveness of these modern technologies.
Core competencies required for an AI-Powered Supply Chain
To succeed in a world where AI and ML are key, supply chain professionals need to:
- Understand how AI and ML work and how they can solve supply chain problems
- Be good at gathering, cleaning, and understanding data
- Know how to use automation to make supply chains more efficient
- Work well with different departments to get the most out of AI
- Be strategic and solve problems that come up when using AI and ML
- Prepare for potential risks and keep the supply chain running smoothly
- Commit to continuous learning to stay abreast of the latest advancements
How businesses can prepare their workforce for AI and ML
In order to fully harness the power of these technologies, businesses need to invest in training their staff to develop key competencies in AI and ML.
These can be done in numerous ways
- Through specialised training and development programs focussing on AI, ML, and data analytics. By upskilling staff in these areas, it empowers them to take on new challenges while also reducing dependencies on external consultants.
- Creating cross disciplinary teams can help to identify common problems within the various departments and provide an opportunity for supply chain professionals to work closely with IT, AI specialists and data scientists and get a deeper understanding of how AI and ML can be applied to solve complex problems.
- Encouraging a company wide data-driven culture so it inculcates a culture of decision making based on data insights. This of course would require a shift in mindset of the staff and require them to be comfortable with the usage of data in order to drive improvements in performance.
- Enhancing soft skills such as effective communication and problem solving as it is equally important for staff to have these skills along with technical skills in order to manage AI driven supply chain projects effectively.
Conclusion
AI and ML are no longer futuristic technologies, they are already here and transforming the way in which supply chains are working.
However, the full power of these technologies can only be unlocked if the team has the right competencies, and the future of supply chains will depend on how well companies develop these competencies so that it helps them stay competitive and flexible.
Those that succeed will be the ones that continue learning and working well together while using both technical and strategic knowledge.
As we move further into the age of Artificial Intelligence (AI) and Machine Learning (ML), supply chain competencies will become the linchpin that determines whether companies can navigate the challenges and seize the opportunities of the digital era.
About the Author
Hariesh Manaadiar
Founder at Shipping and Freight Resource and Features Editor – OceanFreight at CargoNOW
Hariesh Manaadiar is a subject matter expert in the field of shipping, freight, logistics and trade active in the industry for over 35 years. Hariesh shares his knowledge and experience through his Shipping and Freight Resource which he founded in 2008. He has a Masters in Shipping and Logistics, is a Fellow of the Institute of Chartered Shipbrokers, qualified in Digital Trade Strategy and Digital Supply Chain Management and holds a Diploma from the London School of Journalism.
