In the face of tariff talks, trade tensions, volatile demand cycles and reconfigurations in global supply chains, businesses are increasingly relying on artificial intelligence technology for greater predictability and risk management.
Use cases are emerging across industries such as manufacturing, retail, consumer goods and large conglomerates. They include intelligent demand forecasting, dynamic route optimisation and sourcing, inventory and procurement management, digital twins of supply chains, tariff code management, order processing and quality control and logistics optimisation, experts and executives said.
The focus is on making supply chains more resilient, scanning global events to identify risks in real-time. Until recently, deriving efficiency and reducing environmental impact were the major reasons for AI deployment in this domain. But the current global scenario has shifted the focus to stability as well, executives said.
More than 60% of enterprises are focused on piloting multiagent systems for autonomous value chain operations, according to a recent Nasscom survey. “With GenAI, value chain optimisation has emerged as an important use case as models learn from the value chain interactions and data flows to optimise resource, asset, and time efficiencies,” the report said.
This helps companies get more nimble.
“By using AI to predict disruptions, whether due to trade tensions, raw material shortages, or climate-related events, we can adapt quickly while continuing to deliver responsibly,” a spokesperson for multinational industrial technology company Siemens AG told ET. “Real-time data on demand shifts, component shortages, or regulatory changes allows us to respond quickly without compromising on our sustainability standards.”
The firm is seeing improved capacity utilisation, faster response times, and significantly lower carbon impact by using AI in supply chain management. This includes a 15% reduction in logistics costs and 40% faster delivery times. It is also deploying AI-powered digital twins that simulate supply chain scenarios in real-time.
GenAI can reimagine nearly 60% of 122 supply chain processes, from design and planning to after-sales and service, according to Accenture analysis. 0“For example, embedding gen AI into supply chain control towers improves data interaction, real-time decision making and proactive risk management,” said Vijay Kumar Baliyan, MD and lead, Industry X, Accenture in India. “We are seeing an uptick in AI adoption in supply chain operations across industries, specifically in retail and ecommerce, consumer goods, healthcare and transportation.”
Applications in sourcing and procurement include auto-generated vendor-specific insights to support contract renewals and contextualised performance metrics, he said. This enhances explainability, efficiency and operational performance.
“We are seeing a sharp rise in AI adoption across sectors we serve, from energy to infrastructure to manufacturing,” said Anshum Jain, vice president, global supply chain, greater India, Schneider Electric. “In India, where supply chains face unique challenges like infrastructural variability and regional disruptions, we’re seeing AI play a critical role in building operational continuity. AI allows us to detect early signs of disruption, model various scenarios, and proactively address risks, whether it’s a raw material shortage or a logistics bottleneck.”
Firms are looking to strengthen their capacity to anticipate disruptions and respond with precision. “Machine learning is used to model supply chain risks, while natural language processing enhances customer communication and sentiment analysis,” said Naresh Kumar, COO of electrical and automation firm Lauritz Knudsen.”
AI-driven sales value projections are enabling smarter monthly planning cycles for the company, grounded in real-time data, he added. “Amid ongoing geopolitical and macroeconomic uncertainties, businesses are grappling with challenges such as price volatility, supply chain disruptions, unplanned tariff costs and unpredictable operational shifts,” said Prashanth Kaddi, partner, Deloitte India.
AI-driven tools for scenario planning and predictive analytics, including predictive simulations, are becoming indispensable for navigating uncertainty and managing disruptions, he said. For instance, AI can support complex tasks such as trade classification, cost structure analysis, and regulatory compliance, enabling faster and more strategic decisions.
Microsoft customers like L&T are leveraging AI to reduce project planning time from two weeks to 10 minutes, unlocking faster decisions and cost savings in infrastructure and EPC, said Himani Agrawal, COO, Microsoft India and South Asia. Globally, procurement and supply chain solutions provider GEP is driving around 50% productivity gains with its AI-powered procurement platform. In a rapidly evolving global environment where trade dynamics are shifting, AI is no longer optional. In fact, it’s becoming foundational to how supply chains operate,” said Agrawal.
The automotive industry is also leveraging AI to manage vast supplier networks, especially as electric and autonomous vehicles become mainstream, said Manish Singhal, secretary general, Assocham.
“Retail is undergoing a quiet revolution, using AI to decode consumer behavior and respond to shifts almost as they happen,” Singhal said. “In food and beverage, AI helps ensure freshness and reduce waste, while healthcare and pharmaceuticals are using it to manage critical, life-saving logistics.”
Use cases are emerging across industries such as manufacturing, retail, consumer goods and large conglomerates. They include intelligent demand forecasting, dynamic route optimisation and sourcing, inventory and procurement management, digital twins of supply chains, tariff code management, order processing and quality control and logistics optimisation, experts and executives said.
The focus is on making supply chains more resilient, scanning global events to identify risks in real-time. Until recently, deriving efficiency and reducing environmental impact were the major reasons for AI deployment in this domain. But the current global scenario has shifted the focus to stability as well, executives said.
More than 60% of enterprises are focused on piloting multiagent systems for autonomous value chain operations, according to a recent Nasscom survey. “With GenAI, value chain optimisation has emerged as an important use case as models learn from the value chain interactions and data flows to optimise resource, asset, and time efficiencies,” the report said.
This helps companies get more nimble.
“By using AI to predict disruptions, whether due to trade tensions, raw material shortages, or climate-related events, we can adapt quickly while continuing to deliver responsibly,” a spokesperson for multinational industrial technology company Siemens AG told ET. “Real-time data on demand shifts, component shortages, or regulatory changes allows us to respond quickly without compromising on our sustainability standards.”
The firm is seeing improved capacity utilisation, faster response times, and significantly lower carbon impact by using AI in supply chain management. This includes a 15% reduction in logistics costs and 40% faster delivery times. It is also deploying AI-powered digital twins that simulate supply chain scenarios in real-time.
GenAI can reimagine nearly 60% of 122 supply chain processes, from design and planning to after-sales and service, according to Accenture analysis. 0“For example, embedding gen AI into supply chain control towers improves data interaction, real-time decision making and proactive risk management,” said Vijay Kumar Baliyan, MD and lead, Industry X, Accenture in India. “We are seeing an uptick in AI adoption in supply chain operations across industries, specifically in retail and ecommerce, consumer goods, healthcare and transportation.”
Applications in sourcing and procurement include auto-generated vendor-specific insights to support contract renewals and contextualised performance metrics, he said. This enhances explainability, efficiency and operational performance.
“We are seeing a sharp rise in AI adoption across sectors we serve, from energy to infrastructure to manufacturing,” said Anshum Jain, vice president, global supply chain, greater India, Schneider Electric. “In India, where supply chains face unique challenges like infrastructural variability and regional disruptions, we’re seeing AI play a critical role in building operational continuity. AI allows us to detect early signs of disruption, model various scenarios, and proactively address risks, whether it’s a raw material shortage or a logistics bottleneck.”
Firms are looking to strengthen their capacity to anticipate disruptions and respond with precision. “Machine learning is used to model supply chain risks, while natural language processing enhances customer communication and sentiment analysis,” said Naresh Kumar, COO of electrical and automation firm Lauritz Knudsen.”
AI-driven sales value projections are enabling smarter monthly planning cycles for the company, grounded in real-time data, he added. “Amid ongoing geopolitical and macroeconomic uncertainties, businesses are grappling with challenges such as price volatility, supply chain disruptions, unplanned tariff costs and unpredictable operational shifts,” said Prashanth Kaddi, partner, Deloitte India.
AI-driven tools for scenario planning and predictive analytics, including predictive simulations, are becoming indispensable for navigating uncertainty and managing disruptions, he said. For instance, AI can support complex tasks such as trade classification, cost structure analysis, and regulatory compliance, enabling faster and more strategic decisions.
Microsoft customers like L&T are leveraging AI to reduce project planning time from two weeks to 10 minutes, unlocking faster decisions and cost savings in infrastructure and EPC, said Himani Agrawal, COO, Microsoft India and South Asia. Globally, procurement and supply chain solutions provider GEP is driving around 50% productivity gains with its AI-powered procurement platform. In a rapidly evolving global environment where trade dynamics are shifting, AI is no longer optional. In fact, it’s becoming foundational to how supply chains operate,” said Agrawal.
The automotive industry is also leveraging AI to manage vast supplier networks, especially as electric and autonomous vehicles become mainstream, said Manish Singhal, secretary general, Assocham.
“Retail is undergoing a quiet revolution, using AI to decode consumer behavior and respond to shifts almost as they happen,” Singhal said. “In food and beverage, AI helps ensure freshness and reduce waste, while healthcare and pharmaceuticals are using it to manage critical, life-saving logistics.”
