Intelligent Supply Chains in Action: Fujitsu’s Age...

pavneetbedi · ‎2025 Oct 10

Introduction

Across industries, supply chain disruptions have become the new normal. Global manufacturers are navigating a complex web of challenges, including shifting trade policies, volatile energy prices, climate-driven events, and the growing demand for sustainable operations. The systems and strategies that once brought stability now struggle to keep up with this constant change.

According to a 2024 report by Maersk, 76% of respondents reported experiencing supply chain disruptions, and a startling 58% of them reported that the costs exceeded their predictions. From sudden tariff changes that reshape sourcing decisions to unexpected raw material shortages or port closures, disruptions no longer come one at a time as they overlap, compound, and evolve faster than traditional planning tools can respond.

In this environment, organisations need more than data visibility. They need decision intelligence systems that can sense change, learn continuously, and act responsibly in real time. This cannot be achieved in isolation, and an ecosystem or network play is a must. This is also where the latest innovations in Artificial Intelligence, like Agentic AI, can help redefine supply chain resilience.

The role of Agentic AI in Supply Chain Resilience

Agentic AI has the potential to power the next evolution of intelligent supply chain management. Instead of waiting for analysts or planners to interpret data, AI agents can continuously monitor supply, logistics, and market signals and then autonomously simulate and recommend the best response.

A few scenarios include:

Sudden geopolitical tensions? AI agents instantly recalculate costs, identify alternate suppliers, and propose optimised procurement mixes.
An energy-price surge? AI agents can suggest shifting production to lower-cost facilities or off-peak hours to protect margins and emissions goals.

SAP and its partner ecosystem are harnessing the power of Agentic AI to bring the vision of an intelligent supply chain to life. As a strategic SAP partner, Fujitsu is at the forefront of this innovation - creating next-generation solutions that enhance visibility, resilience, and responsiveness across global value networks.

Among the many factors disrupting supply chains today, cross-border tariffs remain one of the most complex and persistent challenges. In this article, we explore how Fujitsu’s Agentic AI-driven offerings are designed to help businesses anticipate, adapt to, and overcome these disruptions - enabling a smarter, more connected, and future-ready supply chain.

Building a Resilient Supply Chain to respond to Trade disruptions

In recent months, global trade dynamics have become increasingly unpredictable. The rules that once made it easy for goods to flow across borders - like free trade agreements - are now being challenged by new tariffs, shifting political alliances, and unexpected disruptions across the trade lanes. In a recent study published by BCG in 2025, it is estimated that at least 20% to 30% of EBIT margins for companies across all manufacturing sectors are at risk from higher tariffs!

Real-World Example: How Agentic AI Transformed a Global Electronics Manufacturer

A leading global electronics manufacturer in Asia faced significant challenges stemming from supply chain uncertainties, siloed enterprise systems and fragmented data. Their complex IT landscape made it difficult to access and interpret critical information across departments, slowing down decision-making during high-stakes disruptions.

Traditional point-to-point data integration approaches would have taken years to unify these disparate systems. Instead, the company sought a transformative solution - one that could consolidate enterprise data, enrich it with industry and business context, and dramatically accelerate decision cycles.

Agentic AI proved pivotal in transforming the company’s response to disruptions.

During disruptions such as trade tariffs or natural disasters like earthquakes, the manufacturer needed to rapidly assess the impact across their supply chain. This required synthesising internal enterprise data with external sources such as demographic trends, trade data, and harmonised system (HS) codes to simulate scenarios and take informed action.

As part of a broader digital transformation initiative, the company explored how Agentic AI could address supply chain shortages. By deploying intelligent agents across multiple systems - procurement, sales, inventory, and orchestration - they enabled real-time data access and contextual decision-making. These agents were trained to perform specialised tasks and provide actionable recommendations to business users.

For example, in the case of a raw material shortage, agents could evaluate multiple alternatives:

Sourcing from an alternative supplier,
Adjusting production schedules based on material availability, or
Engaging with customers to reschedule orders while maintaining service levels.

Each scenario required granular simulation across millions of SKUs, factoring in product, customer, and supplier contexts. The orchestrator agent played a pivotal role by assessing each option through the lens of cost, priority, and service level, ultimately recommending the most optimal path forward.

This innovative use of Agentic AI not only enhanced agility and collaboration across the enterprise but also earned a global recognition. The World Economic Forum’s AI Governance Alliance acknowledged this solution as one of 18 advanced AI applications transforming business worldwide.

Turning Data into Decisions

Expanding data visibility across enterprise, market, and regulatory sources enhances predictive accuracy and resilience.

Some other examples of how companies can use data and smart technologies to solve supply chain challenges encountered in tariff change scenarios are as follows:

Profit and Cost Analysis: By mapping out where costs are rising due to tariffs, companies can decide whether to pass those costs on to customers, absorb them, or find cheaper alternatives.
Pricing Simulations: Businesses can test how different prices will affect demand and profits in different tariff scenarios, helping them find the best balance between staying competitive and making money.
Operational Changes: If a key supplier is hit by a new tariff, companies can quickly see what other options are available, compare costs and quality, and make a switch if needed.

Fujitsu’s Multi-AI Orchestration Platform

Fujitsu has developed a Multi-AI agent orchestration platform for use cases such as Profit Margin & Cost Analysis that can leverage data stored in both SAP and non-SAP systems to present specific scenarios that can impact a customer’s supply chain. Using the simulation capabilities of this offering, multiple scenarios can be developed and compared, and the right strategy can be devised. The agentic AI platform leverages the data and helps to implement the decisions back into SAP applications like SAP S/4HANA SAP Integrated Business Planning and SAP Digital Manufacturing to effectuate the optimal plan chosen earlier. In the future, these agents could be extended to support SAP Business Network Supply Chain Collaboration and Supply Chain Orchestration as well.

These offerings are also complementary to the AI innovations delivered by SAP with the Business Suite e.g. seamless access with Joule, enhanced collaboration and decision making with SCM agents, etc.

Preparing for an AI-Enabled Future

Introducing technological capabilities isn’t enough. Companies also need to change the way they work with AI. This includes:

Cultivating an “AI-first” mindset: AI projects executed with a traditional mindset rarely deliver transformative outcomes. A transformational mindset is required to transform supply chains with AI. A few key aspects are as follows:
- Myths like “AI will completely replace humans” are making way to “AI agents will work alongside humans”. But accepting this at an individual level requires humans to trust AI.
- Especially within the supply chain, one cannot afford to have unreliable supply chain plans or manufacturing schedules. Balancing the level of AI autonomy with human empowerment is key to gaining this trust.
- An AI-first and transformational mindset is required in transforming supply chains with AI
AI upskilling: Technologies such as Generative AI are being widely used by people to simplify their personal tasks. However, when it comes to corporate use of such tools, there are several nuances that we need to be aware of, like trusted tools, enterprise context and security concerns. These also apply specifically to the use of AI in supply chains
Improve Network relationships: A supply chain network includes partners like component suppliers, logistics partners etc. These partners are important to ensure optimal running of the supply chain in normal times and become critical during disruptions. Trusted data sharing, clear communication channels, and robust digital capabilities are critical to sustaining a resilient partner ecosystem

Conclusion

Agentic AI is redefining how organisations anticipate, adapt, and act amid global supply chain volatility. Fujitsu and SAP’s joint innovation demonstrates that the future of supply chain resilience lies not just in data, but in intelligent, autonomous collaboration.

Learn More

If you’d like to see how such technology can be turned into a solution in action or to learn more, consider attending the Fujitsu ActivateNow event in Singapore.

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