**London**: Industry experts discuss the rise of AI within supply chains, predicting a shift towards autonomous operations by 2025. Innovations like generative AI and agentic AI promise efficiency but raise questions about data quality and human roles in decision-making.
In recent years, the advancement of artificial intelligence (AI) within the supply chain sector has reached remarkable heights, according to industry experts who are anticipating even more significant changes by 2025. Central to these discussions is the rise of generative AI and large language models (LLMs), which are paving the way for what are being referred to as “AI-driven autonomous operations.” These innovations aim to significantly reduce human intervention in crucial decision-making processes.
Hardik Chawla, a senior product manager at Amazon.com, describes this transformation as “end-to-end process automation — completely hands-off,” highlighting the potential for streamlined operations across the board. Others in the field prefer the term “self-driving supply chain,” a phrase that encapsulates the growing reliance on technology to enhance efficiency. Procurement, in particular, is primed for this evolution, as AI systems are being designed to select suppliers capable of fulfilling specific orders while optimising factors such as production lead times and inventory levels.
Moreover, AI is now being employed to make transportation decisions for raw materials and finished products. The technology can rapidly alter routing plans in response to unexpected challenges, including adverse weather conditions or labour strikes, thereby minimising disruptions. However, Chawla points out that while certain applications of this technology are already in play, many segments of supply chain operations are still awaiting broader adoption.
A critical component of this shift is agentic AI, which involves highly advanced systems acting autonomously to solve problems or meet objectives without direct human oversight. Justin Newell, CEO of Inform, elaborates on this concept, stating that an operation utilising agentic AI could independently navigate among various options to select optimal routes. One example of this application can be seen at the Port of Los Angeles, where agentic AI directs crane operations, enhancing container management efficiency.
A recent report by Inform highlights the strategic integration of AI into key business processes like logistics and manufacturing, asserting that these enhancements could unlock significant, yet largely untapped, potential within business AI applications. Slavena Hristova, director of product marketing at ABBYY, notes that AI-driven automation will be “crucial” for simplifying complex tasks such as inventory management and warehouse operations. She references research suggesting that AI could lead to a 15% reduction in supply chain and logistics costs through improved process optimisation.
However, the pace of AI adoption varies across the industry. Larger transportation providers often exploit what Hristova calls “low-hanging fruit,” working to digitise documentation practices that remain heavily paper-based. Newell predicts a future where AI becomes deeply entrenched in the operational fabric of organisations that already employ technology experts, facilitating a move towards decision intelligence that could see 60% to 80% of decisions made without human approval.
Additionally, Hristova envisions a broader perspective enabled by AI, allowing companies to assess their processes holistically and identify bottlenecks. Chawla believes that the upcoming year will witness an increased focus on leveraging AI to bolster supply chain resilience, specifically emphasising the need for real-time visibility across production and logistics.
Looking further ahead to 2025, experts agree that organisations will recognise the importance of clean, well-structured data for harnessing AI effectively. Hristova stresses that this readiness for AI will require procurement of quality data, especially from legacy systems that may struggle to communicate with modern AI-driven applications.
Newell also foresees a growing shift towards software-as-a-service (SaaS) applications, designed to unify multiple processes within organisations. Nonetheless, he and Chawla are clear that the role of humans in supply chain management is not in jeopardy. Chawla states, “It will be a world where people will have to upskill to be well-versed in AI,” envisioning the technology mainly assisting with routine tasks. Newell further asserts that while autonomous supply chains will change the landscape, the goal remains to optimise the collaboration between human decision-makers and AI systems.
Source: Noah Wire Services
