Mindmap AI in supply chains
The recent developments in Artificial Intelligence (AI) since the launch of ChatGPT in late 2022 are astonishing and changing the business dramatically. AI is also revolutionizing supply chains by addressing some of the most pressing challenges faced by businesses today. Supply Chain Movement has created a mindmap of AI in supply chains, together with Carlos Cordon, Professor of Digital and Supply Chain at IMD Business School in Lausanne, and the executive advisory firm Supply Chain Companions. This mindmap describes the megatrends in global business, the impact of these trends on companies, the challenges in supply chains, and the different practical and applied solutions.
The world is in turmoil since Covid-19, the war in Ukraine and the Gaza conflict. And these ‘black swans’ come on top of other ongoing megatrends like demographic changes, economic pressures, technological advancements, sustainability requirements and political tensions. Demographic shifts such as aging populations and urbanization are reshaping labour markets and consumer behaviour, leading to staff shortages and increasing the need for automation and upskilling. From an economic perspective, high inflation, job displacement due to automation, and industry disruptions demand adaptive strategies.
Technological trends like advanced machine learning, edge computing and the Internet of Things (IoT) are reshaping supply chain management, while sustainability pressures require companies to focus on carbon accounting, circular economy practices, and environmental monitoring. Meanwhile, political pressures like geopolitical conflicts and trade wars are impacting global supply chains, necessitating agile risk management and compliance strategies.
Impact on company
These megatrends impact various business functions differently. In finance, these trends drive the need for enhanced risk management, fraud detection and real-time monitoring of transactions to manage economic uncertainties and achieve financial stability. Sales functions increasingly rely on predictive analytics to understand buying behaviour, personalize sales strategies and optimize demand forecasting. Marketing is affected by the push for personalized content and products, the rise of contextual advertising, and changes like the deletion of third-party cookies.
In IT, there is a growing need for better security, automation, and alignment with business goals, especially in adapting to new software development methodologies and open-source platforms. HR departments face challenges in talent acquisition, employee engagement and personalized training programmes due to demographic and technological shifts. Legal teams must navigate complex contract analysis and compliance issues, while R&D focuses on rapid prototyping, predictive modelling, and reducing time-to-market.
More complex
Supply chains are becoming more complex, requiring robust data governance, end-to-end visibility, and a shift from being execution-focused to enabling business growth in response to sustainability pressures and geopolitical uncertainties.Current supply chain challenges are numerous and complex. In planning, demand volatility and forecasting accuracy are major issues, exacerbating difficulties in stock allocation. Sourcing faces supply risks, especially beyond Tier-2 suppliers, necessitating dual sourcing strategies and sustainable material choices. Manufacturing is challenged by the need to balance ESG goals with cost reduction and product variety, while distribution complexities arise from omnichannel order management, high returns, and complex logistics execution.
Additionally, international shipments are hindered by exploding freight costs and transport disruptions. Managing these complexities requires a shift from traditional execution to orchestration, with a significant focus on green delivery options, inventory allocation, and home delivery solutions.
AI solutions
AI provides a suite of solutions to these supply chain challenges. Digital Supply Chain Twins offer simulation and optimization capabilities that enhance planning by creating demand scenarios, optimizing inventory policies, and improving supplier performance analysis. In manufacturing, AI-driven solutions enable better production scheduling, predictive maintenance, and product quality management, while logistics operations benefit from dynamic route planning and warehouse optimization. AI-powered predictive analytics can sense demand, predict supplier risks, optimize production yields, and forecast freight costs, thereby providing a more resilient supply chain framework.
Supply chain efficiency
Robotics Process Automation (RPA) further enhances supply chain efficiency by streamlining demand planning, supplier onboarding, purchase order processing, and real-time quality monitoring. Moreover, AI contributes significantly to sustainability efforts in supply chains. AI-powered tools assist in carbon accounting, environmental monitoring, and ESG reporting, ensuring that companies not only comply with regulations but also enhance their sustainability profiles. By leveraging AI, supply chains can transition from mere efficiencydriven operations into more sustainable and strategically aligned systems that drive business growth and adaptability in a rapidly changing global environment.
The surprise with GenAI
As with all new digital technologies, some of them are great use cases while others (like blockchain) go down in the hype cycle. Generative AI (GenAI) is different in that it has progressed a lot over time. In March this year, GenAI could barely do some mathematical calculations correctly. By September this year, GenAI with the Data Analytics GPT could do some very sophisticated forecasting (as do many specialized AI applications) and could also explain the logic of the calculations plus the code to insert in Excel to implement it at scale.
The question is, will supply chain professionals see an explosion of use cases in the coming months? Will GenAI provide a huge boost to the most used tool in supply chain, the Excel spreadsheet? The integration of AI in supply chains is no longer just an option, but now a necessity for businesses aiming to stay competitive and resilient amid the megatrends shaping today’s world.
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