AI in supply chains: should you believe the hype?

From tech brands to mainstream media, boardrooms to factory floors, artificial intelligence (AI) is being hailed as the key to driving operational excellence.  

But is the reality as revolutionary as the rhetoric? The answer is more nuanced than the headlines suggest. 

A reality check 

While AI offers transformative potential, it is not a silver bullet, and businesses risk falling into the trap of hype-driven decisions if they do not approach with caution. 

Before jumping in, businesses must have defined goals, measurable outputs, and a deep understanding of their process flows. Robust cyber security is also critical because as technology evolves and scales, so do the risks, making robust security non-negotiable. 

Without these foundations, AI becomes a costly and disruptive experiment rather than a strategic advantage. 

The first challenge is understanding where AI genuinely adds value. Not next year or in five years, but today. 

AI’s practical applications 

AI is not one-size-fits-all. Its potential impacts depend on the type of AI system businesses adopt: 

• Agentic AI acts as a central decision-making hub, integrating workflows and autonomously managing tasks, such as forecasting and ordering. Agentic AI is unique in its ability to enlist the help of other AI tools or engines to perform the widest range of tasks. 

• Predictive AI powers tools such as predictive maintenance, spotting early signs of equipment stress to reduce downtime. Risk management platforms are utilising predictive AI more to simulate and pre-empt supply chain disruption. 

• Generative AI tools like ChatGPT, Co-pilot and Gemini assist with content creation and insights but are supportive rather than autonomous. 

And these capabilities are already shaping practical applications across supply chains: 

• Supply chain management: automated ordering and promotions optimisation. 

• Logistics: dynamic route planning and network modelling based on live and historical data. 

• Food production: microscopic AI-driven quality checks to prevent contamination, optimise production activities and ensure safety. 

• Risk management: anticipating disruptions and flagging compliance risks across global networks. 

The bottom line  

Strategic, informed adoption of AI can unlock efficiency and resilience in supply chains. But buying into the hype without a plan risks wasted investment and added vulnerabilities.  

Successful outcomes will come to those who ask the right questions before taking the plunge. 

Want to know what’s next for supply chains? 

Download our report, ‘Supply chain trends 2026’, to learn more about AI adoption and the four key trends that will disrupt and evolve supply chains in the near future. 

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