Despite rapid adoption, supply chains face challenges in strategy and readiness as organisations harness AI to boost efficiency, sustainability, and resilience by 2025.
Organizations worldwide are accelerating the adoption of artificial intelligence (AI) in their supply chain operations, with more than 80% of supply chain leaders planning to deploy AI technologies in 2025, according to a recent survey by ABI Research. These deployments focus on improving critical functions such as demand forecasting, inventory management, and supply chain network design.
Ryan Wiggin, Senior Analyst at ABI Research, highlights that traditional AI and machine learning (ML) techniques remain adequate for most network design and optimisation tasks. However, generative AI is starting to enhance user experience by offering more intuitive interfaces for interacting with complex system data. Despite this rapid interest, a significant gap persists in readiness — fewer than half of surveyed organisations currently possess capabilities for advanced prescriptive and predictive analytics. According to Wiggin, agentic AI systems, which autonomously generate deeper predictive insights, are still in their infancy, with effective data management and model customisation seen as key enablers for unlocking their full potential.
Supporting the surge in AI adoption, companies are increasingly moving supply chain systems to cloud-based environments. Two-thirds of respondents are already deploying or fully implementing public cloud infrastructure, while private cloud solutions remain mostly in exploratory or proof-of-concept phases.
Complementing these findings, research from Gartner forecasts that by 2030, around 70% of large organisations will implement AI-based forecasting tools to better predict future demand. Such tools aim to bolster strategic decision-making, increase responsiveness to shifting market conditions, and enhance collaboration efficiency across supply chain partners. Gartner emphasises that integrating AI tightly within technology strategies is essential for achieving scalable automation in demand planning.
Additional insights from a joint study by Deposco and Fulfillment IQ reveal that 46% of organisations have already implemented AI in some capacity across their supply chains, with nearly half achieving significant returns on investment. The research stresses the advantage of unified AI platforms, which see adoption rates 3.5 times higher and deliver superior ROI compared to fragmented point solutions. This underscores the importance of comprehensive, integrated AI strategies over isolated applications to fully harvest the benefits of AI in supply chain management.
Geographically, South Korea and the United Arab Emirates lead in AI deployment within supply chain sectors, each boasting a 58% adoption rate in 2025. This leadership follows substantial national investments: South Korea through initiatives like its ‘Smart Factory’ programme, and the UAE via targeted AI applications in port logistics and free trade zones. Their examples demonstrate how coordinated governmental support and focused industry efforts can accelerate AI integration on a national scale.
Beyond operational gains, AI’s role in fostering sustainability is gaining prominence. Recent academic research highlights how AI-driven logistics models contribute to environmental goals by reducing fuel consumption, minimising emissions, and lowering costs through predictive analytics for demand and route optimisation. Such capabilities position AI not only as a tool for efficiency but also as a critical component of eco-efficient, responsible supply chain management.
Large language models (LLMs) are also beginning to transform supply chain processes by improving decision-making and operational efficiency while integrating with emerging technologies like IoT, blockchain, and robotics. Studies note the necessity of addressing ethical considerations around AI deployment to ensure fairness, transparency, and accountability in increasingly automated supply chains.
However, despite strong enthusiasm, a Gartner survey reveals that only about 23% of supply chain leaders have developed formal AI strategies geared towards long-term scalability. Many remain focused on short-term gains, potentially risking inefficient systems and stunting innovation in a sector where adaptability is crucial.
In summary, while AI adoption in supply chains is accelerating rapidly, the journey from initial deployment to fully realised, strategically integrated AI systems remains a challenging one. Organisations must prioritise investment not only in technology but also in data infrastructure, strategy, and governance to harness AI’s transformative potential effectively. The broad trends indicate a future where AI-driven supply chains will be smarter, more agile, and environmentally sustainable, provided companies address readiness gaps and cultivate robust, scalable strategies.
Source: Noah Wire Services
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