FEATURE
Automation & AI
Nathan Hanson, Head of Sales – SAP, Percipere, says AI will play supply chains for the future
THE TIME IS NOW FOR IMPLEMENTING AI A
s the global economy evolves, supply chain management faces unique challenges. 2025 is no exception with various factors - such as geopolitical tensions, labour and raw material shortages, climate change and technological advancements - shaping the future of supply chains. In a crisis, these disruptions can quickly cascade through today’s interconnected global supply chains, leading to soaring operational costs and longer supplier lead times. Quickly responding to these challenges is therefore essential if businesses are to remain competitive, and most importantly, mitigate the impact of future disruptions. Many mid-market supply chain companies around the world lack the resources required to thrive and adapt in today’s fast-paced digital world. Despite this, 97% of supply chain professionals recognise the urgent need to modernise their IT infrastructure, acknowledging that the current systems are inadequate for meeting the needs of modern supply chains. With many companies still relying on legacy technology, some of which are over 20 years old, integration issues are profoundly prominent for both suppliers and customers – this needs to change. Without the bespoke advancements that modern technology brings, current legacy methods are creating disparate systems brought on by tools reliant on manual processes. These can present several challenges including operational increased vulnerability to cyber attacks, limited visibility, and scalability issues. So, how can organisations within the
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supply chain address these challenges and meet evolving consumer demands? Ultimately, building smart, resilient supply chains requires predict demand and supply needs while also
The future of supply chains powered by AI
a buzzword in the supply chain; it’s a transformative force. According to The State of the Supply Chain report, 82% of supply chain professionals indicate technology technologies such as automated bots and operational assisting mechanisms is that it reduces errors, improves scalability, and enhances operational speed due to a reduction in manual intervention. These tools can help intervention, helping companies improve productivity without the requirement of huge upfront costs. For example, Amazon development of chatbots, voice recognition, fraud detection and product recommendations. Amazon also uses AI to power forecasting, supply chain, and capacity planning, enabling hundreds of millions of products.
Data: The cornerstone of AI To ensure AI adoption translates into meaningful business success, organisations
relies on the quality, accessibility, and alignment of the data it consumes. Without a solid foundation, even the most advanced AI will fail to deliver meaningful outcomes poor data quality. To unlock the full potential of AI,
organisations need to ensure that they address governance, align data initiatives with business goals, ensure accessibility, and adapt to latest technological advancements. Also, a critical yet often overlooked factor is the importance of learning from past IT initiatives. Whether it’s cloud migrations, implementations, analysing the successes invaluable lessons for shaping AI strategies. in optimising supply chains, improving performance.
As leaders move beyond experimentation to implementation of proven AI-driven tools, the opportunity to create a supply resilience and alignment has never been more tangible. However, it’s important to note that achieving AI success requires more than implementation of the technology itself - it demands leadership commitment, and alignment between strategy, people, and processes.
Percipere
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Automation | March 2025 23
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