In uncertain times, supply chains need better insights enabled by agentic AI

Intelligent decision-making has never been so important, and agentic AI is a technology that can deliver the actionable insights the chief supply chain officer needs to build resilience and agility.

Intelligent decision-making has never been so important, and agentic AI is a technology that can deliver the actionable insights the chief supply chain officer needs to build resilience and agility.

To call the current business climate volatile is an understatement – and at enterprises across multiple industrial sectors, the people most keenly impacted by the resulting uncertainty are likely those responsible for managing their organization’s supply chains. These vital, logistical links are subject to powerful external forces – from economic and political factors to environmental impacts and changes in consumer behavior. It’s critical that the executives in charge of supply chains, and their teams, take advantage of every tool to make smarter decisions.

New, multi-AI agent systems can deliver the insights that not only make supply chains more resilient, but also help executives identify opportunities to reduce logistics costs. But organizations must be ready to take advantage of these powerful tools. Preparing for success includes creating the right roadmap and engaging the right strategic technology partner.

Common pain points in the chain

In my conversations with chief supply chain officers, I’ve identified several common pain points they’re keen to address. Most are being challenged to improve supply planning, reduce inventory cycle times and costs, better manage logistics investments, and do a better job of assessing risks associated with suppliers and other partners across their ecosystem.

A company’s own data is an important source of the information required to help CSCOs achieve these goals and to enable agentic AI. Unfortunately, legacy business intelligence systems are not up to the task. There are several ways in which they fail to deliver:

• Analytics systems rarely support strategic foresight and transformative innovation – instead providing business users with yet another dashboard.
• The results are often, at best, a topic for discussion at the next team meeting – not sufficient for a decision-maker to act upon immediately and with confidence.
• Systems typically fail to personalize their output to provide insights contextualized for the person viewing them – instead offering a generic result that satisfies nobody.
• Systems often aggregate data within silos, which means their output still requires additional interpretation to be valuable.

In short, many legacy systems miss the big picture, miss actionable meaning, miss the persona – and miss the point.

Based on my experience, I recommend an organization address this through multi-AI agent systems.

With the introduction of Gen AI Strategic Intelligence System by Capgemini, this could be the very system that bridges the gap between the old way, and a value-driven future. This system converts the vast amounts of data generated by each client, across their enterprise, into actionable insights. It is agentic: it operates continuously and is capable of independent decision-making, planning, and execution without human supervision. This agentic AI solution examines its own work to identify ways to improve it rather than simply responding to prompts. It’s also able to collaborate with multiple AI agents with specialized roles, to engage in more complex problem-solving and deliver better results.

How would organizations potentially go about doing this?

Establish an AI-driven KPI improvement strategy

First, organizations must establish a well-defined roadmap to take full advantage of AI-enabled decision-making – one that aligns technology with business objectives.

For CSCOs, this starts by identifying the end goals – the core business objectives and associated KPIs relevant to supply chain management. These are the basis upon which the supply chain contributes to the organization’s value, and strengthening them is always a smart exercise. The good news is that even small improvements to any of these KPIs can deliver enormous benefits.

The roadmap should take advantage of pre-existing AI models to generate predictive insights. It should also ensure scalability, reliability, and manageability of all AI agents – not just within the realm of supply chain management, but throughout the organization. That also means it should be designed to leverage domain-centric data products from disparate enterprise resource planning and IT systems without having to move them to one central location.

Finally, the roadmap must identify initiatives to ensure the quality and reliability of the organization’s data by pursuing best-in-class data strategies. These include:

• Deploying the right platform to build secure, reliable, and scalable solutions
• Implementing an enterprise-wide governance framework
• Establishing the guardrails that protect data privacy, define how generative AI can be used, and shield brand reputation.

An experienced technology partner

Second, the organization must engage the right strategic partner – one that can provide business transformation expertise, industry-specific knowledge, and innovative generative AI solutions.

Capgemini leverages its technology expertise, its partnerships with all major Gen AI platform providers, and its experience across multiple industrial sectors to design, deliver, and support generative AI strategies and solutions that are secure, reliable, and tailored to the unique needs of its clients.

Capgemini’s solution draws upon the client’s data ecosystem to perform root-cause analysis of KPI changes and then generates prescriptive recommendations and next-best actions – tailored to each persona within the supply chain team. The result is goal-oriented insights aligned with business objectives, ready to empower the organization through actionable roadmaps for sustainable growth and competitive advantage.

Applying agentic AI to the supply chain^*

Here’s a use case that demonstrates the potential of an agentic AI solution for supply chain management.

An executive responsible for supply chain management is looking for an executive-level summary and 360-degree visualization dashboard. They want automated insights and recommended next-best actions to identify savings opportunities.

An analytics solution powered by agentic AI can incorporate multiple KPIs into its analysis – including logistics spend, cost per mile, cycle time, on-time delivery rates, cargo damage, and claims. It can also track performance of third-party logistics service providers – including on-time performance, adherence to contractual volumes, freight rates, damages, and tender acceptance.

The solution can then apply AI and machine learning to optimize asset use through better design of loadings and routes. Partner performance can be analyzed – including insights into freight rates, delays, financial compliance, and lead times – and used to negotiate better rates.

The impact of this can include a reduction in logistics spend of approximately 10 percent, an opportunity to save approximately five percent through consolidation of routes and services, and a 15 percent improvement in transit lead time.

Capgemini enables this use case through an AI logistics insights 360 solution offered for the Gen AI Strategic Intelligence System by Capgemini. Just imagine this agent working 24/7 on your behalf; they don’t sleep, they don’t get tired, they don’t take vacation, and they’re completely autonomous.

Real results that relieve supply chain pressures

Capgemini’s modeling suggests that with the right implementation and support, the potential benefits include reducing overall supply chain spending by approximately five percent – including a 10-percent reduction in logistics spend. Other benefits include a three percent improvement in compliance, plus 360-degree order visibility and tracking.

Given that today’s supply chains are being subjected to so many pressures from so many sources, those are meaningful advantages that cannot be ignored.

^*Results based on industry benchmarks and observed outcomes from similar initiatives with clients. Individual results will vary.

The Gen AI Strategic Intelligence System by Capgemini works across all industrial sectors, and integrates seamlessly with various corporate domains. Download our PoV here to learn more or contact our below expert if you would like to discuss this further.