Analyst Insight: The past year has been a double-edged sword for supply chain leaders. Despite advances made with artificial intelligence (AI) in supply chain visibility and predictability, events like the U.S. port strikes and record-setting hurricanes left many struggling to move inventory and plan next steps.

While supply chain teams are exploring generative AI (gen AI) within the different functions of plan, source, make, deliver and aftersales, many are only experimenting in one or two areas. According to research from Genpact and HFS Research, 56% of supply chain executives are in the pilot stage, with 50% expecting gen AI solutions to be fully deployed in one to two years. 

It's a pivotal time for supply chain transformation. No matter the industry — from consumer goods to life sciences — the key ingredients are an integrated supply chain ecosystem (the network of networks as we like to call it), a talented workforce trained on AI, and advanced technologies to automate, streamline, and scale operations across the entire chain. 

A Peek Into the Future of Agentic AI 

Whether using large language models to automate and simplify demand planning or setting up autonomous AI agents (agentic AI) to manage orders and deliveries in real-time — redesigning supply chain operations using advanced technologies will scale services and allow team members to work on more strategic issues. The static, well-defined, rule-based automation of today will evolve into dynamic, agentic AI powered by contextual and historical intelligence that goes beyond providing insights, and on to recommending and executing the next-best action. 

Traditional order management takes up a lot of time and resources. Agentic AI will act as a co-pilot, harnessing order intelligence by identifying patterns, looking up previous resolutions, and recommending the best course of action. Agents will identify when things go off track and enable proactive resolution by team members better equipped to resolve issues.

It’s clear that 2025 will be a critical year for organizations to move beyond narrow AI, toward an autonomous, hyperconnected supply chain. Disparate use cases of AI will turn into one connected system of agentic AI “talking” across plan, source, make, deliver and aftersales — ultimately extending beyond the supply chain to a truly interconnected enterprise.

Going Back to the Basics of AI

A hyperconnected supply chain that empowers decision-makers with full visibility into operations, real-time insights and data-driven recommendations is possible. To get there, supply chain leaders must prioritize investments in AI, and focus on boosting adoption today. Where to start? 

• Lead with business value. Leaders should identify supply chain areas where AI can deliver the most impact, and align these with strategic goals.

• Mobilize frictionless operations. AI can resolve bottlenecks by streamlining processes for on-time, in-full deliveries.

• Prioritize customer and user experiences. AI can personalize and elevate service levels for improved satisfaction and loyalty — one of its most tangible benefits.

• Build an AI-ready talent pool. Finding and upskilling the right talent can drive the success of gen AI initiatives — and supply chain leaders are seeking out workers with skills ranging from data science to prompt engineering, who can combine technical knowledge with business skills. 

Outlook: Preparing for 2025 — This year may bring geopolitical conflict, extreme weather, workers’ strikes, and more. That’s why building a resilient supply chain is so crucial, and it requires embedding AI end-to-end to gain a holistic view of operations. Companies that invest in upskilling talent and developing a robust data governance and management strategy for their AI capabilities will be better positioned to navigate any challenges that lie ahead.

Resource Link: https://www.genpact.com/