Amid the rise of AI, the transformation of work methods, and the quest for technological sovereignty, supply chain professionals are seeking to balance operational performance with employee well-being. But how does innovation—often touted as a miracle solution—align with the realities on the ground?

During the roundtable discussion titled “Augmented Human: Added Value Through Technology and Digital Solutions,” experts such as Pierre Chaffardon (Generix), Vanessa Clemendot (Sanofi), Christophe Plouseau (Louis Vuitton Malletier), and Christophe Vandrome (Kuehne+Nagel) shared their insights.

The key challenge of AI in logistics is decision support to better manage human resources. During the roundtable discussion titled “Augmented Human: Added Value Through Technology and Digital Solutions,” Christophe Vandrome, Contract Logistics Managing Director for France at Kuehne+Nagel , shared his vision of AI-powered decision support to assign tasks based on employees’ skills and preferences . His goal is to improve both employee satisfaction and performance—and ultimately, retention.

Today, a few proof-of-concept projects are underway in Europe based on this principle, but scaling them up remains challenging because it requires evaluating HR data (skills, performance) and structuring its collection to feed into resource allocation and planning models. Christophe Vandrome also cautioned against the dehumanizing use of productivity data to manage teams : “That’s not what real life is like in our warehouses. If we want our people to be happy, we also need to manage our data in the right way and very intelligently.”

Photo credit: Nathalie Vergès Photography

Warehouse resource management was also a central topic of discussion during one of the afternoon workshops dedicated to “Technological Trends in the Supply Chain.”  A live survey allowed for a comparison between the audience’s perceptions and those of the barometer published earlier this year by FRANCE SUPPLY CHAIN’s Digital & Techno LAB regarding AI in the supply chain.

According to respondents in the 2025 survey and the approximately 40 workshop participants, the main benefit of AI in the supply chain remains unchanged: demand optimization through AI (Demand Sensing). Testimonials detailed applications aimed at precise forecasting of operations—specifically, warehouseresource planning ( using Databricks, multi-parameter correlation, and machine learning, with savings of up to 10% on resource costs)—a summary of which is provided below:

All the panelists agreed on the importance of experimenting quickly, accepting failure, and pivoting in the context of digital or technological transformation projects. Pierre Chaffardon, General Manager for EMEA North & APAC at Generix, illustrated this point by noting that the value of AI lies in the ability to experiment and make mistakes quickly, retaining only those use cases aligned with business objectives : “In the area of computer vision, we developed dozens of use cases to test with clients [through co-creation] before ultimately selecting just two that we’re now scaling up.”

Christophe Plouzeau, CIO of Louis Vuitton Malletier, believes that innovation requires accepting a failure rate of 20 to 30 percent of initiatives. He emphasized the need to measure the actual adoption of tools on the ground (far from the Paris offices) and the upheavals caused by Asian countries : “You need to have local teams. You need teams that are capable of immersing themselves in that culture.” Of course, there are regulatory considerations; China demands Chinese solutions, so we have to adapt to that. But generally speaking, Asia has invented—particularly in its interactions with customers—social networks that are central to people’s lives […] these are ecosystems we need to master, and we can’t do that effectively from Paris.”

The enhancement of human capabilities through AI will bring about lasting changes in the way we work. As teams gradually become more familiar with everyday AI tools—such as enterprise ChatGPT— the groundwork is being laid for more structural transformations. During her presentation at RISC, Vanessa Clemendeau, SVP – Global Head of Supply Chain at Sanofi, shared her conviction:“Organizations must prepare for an era of AI agents; my generation is the last that will have to manage only humans. In the future, we will be managing mixed teams of autonomous agents and humans.”

Photo credit: Nathalie Vergès Photography

In response to a question from the audience about data processing prior to the deployment of a digital tool, Christophe Vandrome recommended not waiting for perfect data before launching AI projects : “We get started even if the data isn’t good, and then we make adjustments. In fact, it’s a constant process of refinement. Very often, the data our clients provide isn’t necessarily comprehensive.”

Vanessa Clemendeau added ,“AI also helps us organize the data when that hasn’t been done beforehand. That was the case at Sanofi, which ran a lot of AI models before fully structuring the data, and I was a little surprised when I joined the group. That said, it doesn’t mean it doesn’t work—it just works a little less well, and above all, we need to go back and improve the quality of the data.”

In closing the roundtable discussion, Christophe Plouzeau and Pierre Chaffardon emphasized the growing importance of sovereignty—not only data sovereignty(in the cloud) “Sovereignty isn’t just about France; it’s a regionalized sovereignty, likely spanning at least three or four geographic regions, ” but also of AI models (LLMs) to avoid a new strategic dependency : “We’re not talking about dependency on infrastructure, but rather a dependency on LLM models that we’re all capable of deploying very quickly within our companies.”

The insights shared at the RISC events show that AI and digital tools offer powerful tools for optimizing resource management, anticipating needs, and even rethinking work methods. However, their widespread adoption faces significant obstacles: data quality, the diversity of sites, resistance to change, and the need to maintain a human touch in team management.

The speakers agree on one point:

The Supply Chain of Tomorrow Is Being Built Today

between boldness and pragmatism, with people remaining at the heart of the equation

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AI and automation offer unprecedented solutions for boosting business performance. A race to adopt these technologies is underway in the supply chain—as in virtually every other field—amid full awareness of the risks posed by uncontrolled, large-scale deployment to the world of work as we know it.

While our companies are fighting to keep growing despite repeated crises, people are worried about the future of their jobs and their children.

Two issues that may seem contradictory at first glance but can be addressed through new technologies and digital solutions.

Here is a preview of one of the two panel discussions on the agenda for the upcoming RISC 2026, courtesy of our main sponsor: GENERIX.

Reducing physical strain helps protect workers’ health. Reducing the mental strain of repetitive tasks and boredom helps protect their well-being at work.

Here, technology enhances human capabilities by relieving people of certain tedious tasks.

Let’s take the example of Computer Vision , which enables continuous monitoring of the integrity and compliance of incoming pallets.

This task is so tedious, and the resulting quality so poor, that it is sometimes eliminated altogether, leading to gaps in traceability and associated costs. While AI handles the tedious part of the inspection and identifies errors, humans focus on resolving them. This is a far more satisfying and motivating role.

Well-designed digital tools make the rules of the game clearer: transparent objectives, shared standards, and metrics that are understood and accepted. They enable employees to understand the impact of their actions, measure their contribution, and make progress. Technology then becomes a driver of engagement, rather than a tool of control that is imposed on them.

Here, technology enhances human potential by giving meaning to people’s work.

Let’s take the example of performance analysis and activity reports. With AI, the role of the manager is transforming. Today, managers are essentially Excel experts who spend a significant portion of their time chasing down information and processing it to present it in a clear and coherent way. With AI, they become the architects of an efficient and fast information system. They connect more information sources, streamline and standardize input data, and build reports that are more readable and robust—which enhances their value. They save time and can better focus on identifying new performance drivers. They make the results that inform their decisions more transparent and strengthen their oversight, leading to greater engagement among their teams.

Example of how generative AI can be used to support maintenance technicians (best practices guide from the Digital Techno LAB)

Gain insights from a wider range of data and information from various sources, both internal and external.
Be able to simulate numerous scenarios to compare results by varying assumptions at breakneck speed. Decision support is a highly valued application of AI in supply chain operations, particularly in execution, which must constantly adapt to all kinds of unforeseen events.

Which orders should I prioritize when I don’t have time to process the entire order book? How will this delay affect my schedule tomorrow?

Do I need to hire additional staff? How much will that cost? Who can I call on at the last minute? How can I get started quickly?

With specialized AI agents or models that are well-fed with data, even a junior team leader can fully control their schedule and budget. They can ensure the best work environment and level of engagement among their team members.

Here, technology enhances human capabilities by helping people make better decisions more quickly.

With the advent of technology, the role of the manager is evolving. It is no longer just about “getting things done,” but about “fostering growth”: developing versatility, supporting skill development, and safeguarding critical human know-how and expertise. Managers are learning to assign tasks to different types of resources (technological or human), creating mixed teams and integrating AI agents as members of their teams. Of course, they are training themselves and their teams in “prompt” usage.

Here, technology enhances human capabilities by helping people manage more effectively.

Human review and approval required

An AI system that is well-designed, well-trained, well-fed, and well-monitored should make very few mistakes. In supply chain management—and often in other fields as well—most AI systems do not yet have the necessary conditions to solve complex problems completely on their own.

To address this challenge, Breton Yann LeCun has announcedAdvanced Machine Intelligence ( AMI) Labs, which is capable of understanding the “real world”—that is, the context of a problem and its environment—thus overcoming the limitations of current AI models, which merely manipulate language.

Understanding AI Results

Understanding the decision-making process remains essential when entrusting AI with certain tasks that carry high risks to human health, for example. We want to understand how and why an AI system arrives at a specific result. However, Large Language Models ( LLMs ), Deep Learning (deep neural networks), complex Machine Learning, and quantum computing remain black boxes. At best, they provide a confidence score or warn of limitations regarding the results they deliver. Humans therefore remain in charge, and AI serves as a tool and an aid.

Set decision-making priorities

AI generates results based on a specific request and context. For example, when conducting decision simulations, a human will guide the AI based on their preference between economic performance, service quality, and environmental impact. Or between robustness and hyper-optimization in an uncertain context. This precise framework ensures the relevance of the AI’s responses.

A supply chain powered by augmented human capabilities promises to be more responsive, more profitable, and more sustainable. It puts people back at the heart of the system’s intelligence and embraces technology while adhering to humanistic goals that ensure the long-term viability of the solutions implemented.

To learn more about the full program