In the ever-evolving landscape of supply chains, marked by complexities intensified by material shortages, climate disasters, and geopolitical tensions, logistics professionals are seeking innovative solutions to mitigate disruptions. A recent study from Germany reveals that a staggering 65% of companies in the logistics sector have suffered financial losses due to supply chain disruptions, emphasizing the pressing need for alternative approaches.
Amid this backdrop, artificial intelligence (AI) has emerged as a game-changer, aligning with the ongoing digital transformations in the movement of products, materials, and components across supply chains. Market research from ZipDo indicates that 37% of supply chain leaders are either already leveraging AI or planning its deployment within the next 24 months.
Accenture, a global business leader, recently announced an expansion of its partnership with SAP SE to create a cutting-edge nerve center using AI technology. This collaboration aims to enhance supply chain resiliency and sustainability, offering a proactive solution to prevent future disruptions. A pivotal component of this nerve center is Cosmo Tech’s Supply Chain Vulnerability Scan, utilizing AI simulation to generate a multitude of potential outcomes.
So, what sets AI simulation apart?
AI simulation, a groundbreaking type of generative AI, automates thousands of simulations to help supply chain managers identify vulnerabilities and weak spots that may impact their business. Unlike traditional AI models based on historical data, AI simulation uses synthetic data to create numerous future scenarios, offering a unique advantage in decision-making.
Michel Morvan, Cosmo Tech’s co-founder and executive chairman, distinguishes AI simulation as knowledge-based. Rather than learning from past data, it creates new knowledge to provide visibility into the future. Morvan emphasizes the necessity for decision-makers to have visibility into the impact of their decisions, and AI simulation fulfills this need by generating new and unknown scenarios.
This technology is particularly suited for complex decision-making, covering both predictive analysis and exploring hypothetical scenarios with reliability and explainability. AI simulation offers supply chain managers prescribed actions to optimize decisions based on factors such as supply chain efficiency, profits, service level agreements, production capacity, and environmental considerations.
In essence, AI simulation is transforming supply chain management by providing unparalleled visibility into the future, enabling decision-makers to navigate complexities and optimize outcomes in an ever-changing landscape.
