Executives from Coupa Software and Informatica explore the profound impact of AI and ML (machine learning) on supply chain management, revealing how companies can harness these technologies to boost efficiency, resilience, and accuracy.
Businesses are increasingly turning to AI-driven solutions to navigate today’s complex supply chain landscape. Generative AI (Gen AI) and ML are emerging as game-changers, enabling companies to optimize operations like never before.
Recent research from CGI, commissioned by Supply Chain Digital and Manufacturing Digital, highlights the strategic importance of AI investments. When surveyed about the key technologies supporting supply chain initiatives, 69% of executives cited AI, advanced analytics, and digital twins as top priorities.
Further data from Epicor and Nucleus Research shows that 63% of high-growth companies—those with over 20% revenue growth in the past three years—have already integrated Gen AI into their supply chain operations to manage costs and improve efficiency.
“The global supply chain has faced continued disruptions, exposing outdated tracking methods and unreliable demand forecasting,” says Fang Chang, EVP and Chief Product Officer at Coupa. “AI and ML enhance forecasting accuracy by analyzing vast datasets, including historical sales, market trends, and external factors like economic shifts and weather conditions. The result? Smarter inventory management and a stronger bottom line.”
The Rise of Generative AI and ML (Machine Learning)
Since the late 2022 launch of ChatGPT, AI and ML have gained mainstream prominence. However, Greg Hanson, Group VP and Head of EMEA North at Informatica, saw this transformation coming.
“The ability to harness data and AI effectively will determine market winners and losers,” Hanson explains. “Supply chains require real-time agility to adapt to disruptions, whether from demand fluctuations or unexpected crises.”
While AI and ML adoption remains in its early stages, organizations primarily leverage these technologies for basic challenges, such as consolidating supplier data for a 360-degree view. A report by EY and HFS shows that while many companies are piloting AI-driven solutions, only 7% have successfully implemented Gen AI, with 62% reassessing their projects due to integration challenges.
Hanson stresses the importance of data quality, noting that AI and ML are only as powerful as the data foundation they rely on. “To unlock AI’s full potential, companies must first ensure they have clean, structured, and well-governed data.”
How Coupa Uses AI to Strengthen Supply Chains
Coupa is an industry leader in AI-driven supply chain innovation, leveraging AI to optimize total spend management. The company’s community-generated AI draws insights from $6 trillion in direct and indirect spending data across a global network of over 10 million buyers and suppliers.
Coupa’s AI continuously learns to predict, prescribe, and automate actions, improving supply chain visibility, risk mitigation, and operational efficiency.
Fang Chang explains how Coupa’s AI capabilities enhance supply chains:
“Our Supply Chain Prescriptions solution identifies cost drivers and offers actionable insights to reduce expenses and carbon emissions. By integrating digital twin technology, businesses can simulate different scenarios, optimize transportation routes, and validate cost-saving strategies.”
Coupa has also introduced AI-driven automation in payment processing, workflow optimization, and procurement—announced at the Coupa Inspire conferences in Las Vegas and Vienna.
AI and ML are also revolutionizing data management in supply chains. Informatica’s Gen AI application, CLAIRE GPT, enables organizations to:
- Use conversational prompts to access and analyze data
- Integrate data from disparate sources into a unified, trusted foundation
- Improve end-to-end supply chain operations with AI-driven insights
A prime example is a leading public health organization that leveraged Informatica’s AI tools to track the entire lifecycle of pharmaceutical products. From research and manufacturing to distribution and regulatory compliance, AI provided a holistic view of the global drug supply chain.
“This 360-degree view allows companies to maintain supply chain integrity, anticipate shortages, and respond to demand shifts efficiently,” Hanson says.
The Future of AI in Supply Chain Management
Supply chains face growing disruptions and increasing pressure to decarbonize in line with sustainability regulations. AI and ML will play a critical role in improving forecasting, visibility, and compliance.
Hanson predicts:
“AI-driven forecasting will enable businesses to simulate ‘what-if’ scenarios, identify risks, and optimize resource allocation in real time. Enhanced visibility will also allow for sustainable decision-making, helping companies track environmental impact and supplier compliance.”
Meanwhile, Chang emphasizes the need for seamless AI integration to drive adoption across businesses of all sizes. “AI-powered predictive analytics will help companies navigate geopolitical tensions, supply shortages, and climate-related disruptions,” he adds.
However, both experts agree: data quality remains the foundation of AI success.
Hanson compares AI adoption to automotive manufacturing: “Without well-maintained machinery, a factory cannot produce high-quality cars. Similarly, without clean and structured data, companies cannot maximize AI’s potential.”
AI and ML are reshaping supply chains, offering unmatched efficiency, automation, and predictive capabilities. As companies embrace these technologies, the key to success lies in establishing a strong data foundation to drive AI-powered transformation.
Businesses that can successfully integrate AI into supply chain management will gain a competitive edge, ensuring resilience in an ever-evolving market landscape.
