The Role of AI in Supply Chain Management in Times of Uncertainty
By: Tom Chapman
Source: AIMagazine
Senior executives at Coupa Software and Informatica examine the broad, transformative impact that artificial intelligence (AI) and machine learning (ML) have had on the supply chain field.
In today’s turbulent world, companies – whether large or small – are always looking for ways to increase efficiency, accuracy, and resilience in supply chain management. New technologies such as artificial intelligence, machine learning and, especially, generative AI (Generative AI) have opened a new gateway to advanced optimization.
Smart investment in AI, a strategic priority
A study conducted by CGI on behalf of Supply Chain Digital magazine shows that AI and advanced analytics are now at the top of managers’ priorities for navigating times of uncertainty.
More than 69% of executives have selected technologies such as AI, advanced analytics, and digital twins as the main tools for the future of the supply chain.
According to a report by Epicor and Nucleus Research, about 63% of high-growth businesses (with growth of 20% or more over the past three years) have previously used Gen AI in their supply chain to address operational and cost challenges.
Redesigning the supply chain with AI and ML
Fang Chang, Senior Vice President of Product at Coupa, says:
«The traditional supply chain still relies on methods such as Excel files and inaccurate forecasts. But AI and ML, by analyzing massive data – including sales history, market trends, and even weather conditions – can increase forecasting accuracy and help with better inventory management and profitability.»
Opportunities and challenges in adopting Gen AI
Greg Hanson, Senior Vice President at Informatica, says:
«The difference between market winners and losers lies in the ability to intelligently leverage data and AI. Especially in the supply chain, which must have real-time responsiveness and high agility.»
He notes that most companies are still in the early stages of leveraging AI and ML and have only solved simple issues such as a general review of market suppliers.
According to a study by EY and HFS, only 7% of companies have fully implemented Gen AI and 62% have been forced to revise their projects.
Coupa and innovation in the supply chain powered by AI
Coupa has introduced itself as an AI-based spend management platform. Relying on data related to $6 trillion in transactions from a global network, Coupa uses AI for better decisions, more accurate forecasting, automating operations, and reducing risk.
One of its notable tools is Supply Chain Recommendations which identifies the most costly supply chain factors and offers solutions to reduce cost and carbon emissions.
Easing data management in the supply chain with Informatica
Informatica, too, has simplified data management using AI, especially the CLAIRE GPT tool. Users can access clean, reliable data through voice commands.
Hanson points to an example of a pharmaceutical organization that, with the help of this technology, was able to create a complete view of a drug’s lifecycle, from research and development to production and marketing – a measure that helps save human lives.
The future of AI in the supply chain: transparency, resilience, and sustainability
Greg believes supply chains are on the verge of a major transformation. The pressure to reduce carbon output, ensure high transparency, and respond quickly has doubled the need for tools such as AI and ML. He says:
«AI enables supply chain managers to forecast demand, simulate different scenarios, and monitor the sustainability of operations daily.»
Fang holds the same view, that AI, alongside predictive analytics, helps companies anticipate shortages, geopolitical tensions, and climate changes. Also, with easier integration with existing systems, AI will become a tool usable by everyone.
Hanson concludes by reminding us that:
«Without strong data infrastructure, AI and ML cannot perform well – like a production line that cannot build a car without machinery.»
