Global supply chain fragility costs organizations US$184 million annually, prompting manufacturers to adopt generative AI for improved predictive capabilities, resilience, and efficiency, as reported by cognizant.
Recent advancements in generative AI offer significant transformative potential by democratizing data and analytics across all organizational levels. To maximize these benefits, manufacturers must pinpoint where generative AI can most effectively impact their supply chains and implement it strategically.
A recent post by cognizant highlighted that industries constantly strive to predict market shifts accurately. Successful predictions can boost revenue significantly, while errors can lead to excess stock or critical shortages, causing substantial financial losses. Traditional AI assists manufacturers by analyzing historical data to anticipate and address such issues. Generative AI enhances this process by integrating structured and unstructured data from various sources in real time, providing a comprehensive view of operations and demand trends.
For example, generative AI can forecast demand fluctuations by analyzing customer orders, transactional data, social media trends, economic indicators, and weather patterns. These insights enable manufacturers to plan more effectively for future demand shifts. Additionally, generative AI can evaluate past supplier performance, contracts, and financial statements to create dynamic supplier risk profiles, facilitating swift and informed decision-making.
Supply chain disruptions invariably incur costs. Identifying alternative suppliers and ensuring timely material delivery during crises is essential to maintain production and revenue. The UK's car production drop in early 2022 due to parts shortages underscores the need for a resilient supply chain.
Generative AI optimizes decision-making during unplanned disruptions by providing greater visibility into the supply chain through data analysis from distributors, suppliers, and factories. This helps manufacturers proactively identify and address bottlenecks, mitigating potential disruptions.
Generative AI also enables scenario modelling, allowing companies to prepare for various disruption scenarios and formulate effective responses. Manufacturers can build a more resilient and adaptive supply chain ecosystem by enhancing supply chain understanding.
Generative AI contributes to smarter factories by reducing downtime and enhancing resource efficiency. For instance, US Steel uses Google Cloud’s generative AI to minimize machine downtime and expedite repairs. Combining IoT devices with generative AI allows manufacturers to monitor machine performance and predict maintenance needs.
Adopting generative AI requires understanding its capabilities and collaborating with trusted AI providers. Developing a comprehensive AI adoption roadmap is crucial. Early adoption of generative AI foundations will enable manufacturers to make faster, more informed decisions, enhancing business resilience and productivity.