Artificial intelligence (AI) is evolving and reshaping the way industries work, and it is doing so in almost every sector without exception. Dataconomy sat down with the leaders from NVIDIA, Siemens, Capgemini, and Scaleway at VivaTech 2024 to hear their views on how AI is reforming industries and driving innovation. In these exclusive interviews, we have discussed AI’s opportunities, ethical considerations, and long-term challenges of implementing such powerful technologies. The common theme? AI is not just changing processes; it’s changing mindsets, strategies, and entire markets, opening up incredible opportunities and bringing huge responsibilities.
AI at scale in the new era of computing
NVIDIA has been one of the leading pioneers of the AI revolution for over 15 years, with its technology driving AI advancements. We talked to Nat Ives, Enterprise Director at NVIDIA France, who emphasized two major innovations on their front: AI-enabled robotics and the NVIDIA Inference Microservice (NIMS).
“AI-enabled robotics will be the physical interface of AI in the real world,” said Ives, explaining how these advancements will allow robots to operate autonomously in real-world settings. This opens up a world of possibilities for industries such as healthcare and manufacturing, where robots will manage tasks that previously required human intervention.
“AI-enabled robotics will be
the physical interface of AI in the real world”
What does this mean for human workers? The days of robots simply performing pre-programmed tasks are coming to an end. These AI-powered robots will be able to learn, adapt, and collaborate with human teams in real-time, creating a seamless relationship between humans and machines. This shift will change how industries view workforce productivity, with robots handling repetitive tasks, allowing humans to focus on problem-solving and decision-making.
NVIDIA Inference Microservice (NIM), another innovation emphasized by Ives, is a tool that offers pre-configured microservices that simplify AI integration into existing IT infrastructures. This allows companies, from startups to large corporations, to deploy AI at scale without rebuilding their entire systems. Pointing out that NIMS aims to democratize AI, Ives said, “We want to make sure AI is not just for the big players. Smaller companies, startups—they should have access too.”
However, the transition to this next phase of AI is not without its challenges. Ives highlighted the need for significant upgrades to data centers, saying, “There’s a huge piece of work to evolve all the data centers to embrace this innovation, but we have the answers. It’s a matter of implementing them.”
AI’s strategic evolution in the industry
At Siemens, AI is not a groundbreaking addition but a natural evolution of their long-standing mission to optimize industrial operations. Jean-Marie Saint-Paul, General Director of Siemens Digital Industries France, explained that AI enhances their industrial automation processes, aligning with their broader goal of efficiency and knowledge retention. “AI is pervading across society in the same way it is within industries,” Jean-Marie told me.
Siemens has integrated AI into its Xcelerator portfolio, focusing on improving productivity and decision-making, particularly in industries grappling with an aging workforce and a shortage of skilled labor. AI plays a pivotal role in predictive maintenance, smart automation, and workflows, identifying potential failures before they occur, optimizing performance, and reducing downtime.
“AI needs to be deployed
with a mindset focused on real world production”
However, Jean-Mariel stressed the importance of reliability when deploying AI in critical environments like production lines. The company takes a cautious approach, rigorously testing AI systems before integrating them. “AI should not just be a fancy tool. It needs to be deployed with a mindset focused on real-world production,” he said.
Siemens’ strategy involves introducing AI as an advisor before fully entrusting it with control. This ensures that AI is thoroughly tested and proven reliable before taking on more responsibilities. This phased approach to AI implementation is designed to prevent errors in highly sensitive environments, ensuring that AI contributes to efficiency while maintaining safety and ethical standards.
The AI renaissance
Andy Vickers, CTO of Generative AI at Capgemini Engineering, referred to this period as an “AI Renaissance,” signaling a new chapter in technological evolution. Vickers believes that AI will not transform industries by itself but by integrating with other cutting-edge technologies. As he explained during our interview, “This isn’t just about AI working on its own; it’s about AI working in tandem with other powerful tools to create something far greater.” He further emphasized that AI, combined with technologies like edge computing and the Internet of Things (IoT), sparks a new industrial revolution.
Capgemini focuses on building applications that offer hyper-personalized experiences. According to Vickers, “Our strategy is about creating AI solutions that empower businesses to deliver individualized services while maintaining transparency and trust.”
“AI systems should be humble, acknowledging their limitations
while enhancing human creativity and decision-making”
But Capgemini focuses on more than technology—ethics also play a central role in its approach. Vickers was clear that ethical AI is about more than compliance. “AI must acknowledge its limitations. Having an ethical policy isn’t just about compliance; it’s about building a healthy relationship between humans and machines,” he said.
To ensure AI’s responsible development, Capgemini has implemented a rigorous ethics policy addressing bias, data compliance, and transparency. “AI systems should be humble, acknowledging their limitations while enhancing human creativity and decision-making,” Vickers explained. For Capgemini, responsible AI isn’t just a corporate responsibility; it’s about securing long-term trust and ensuring that AI serves as a tool to complement human capabilities rather than replace them.
Empowering Europe with ethical AI commitment
During our conversation, Adrienne Jan, Chief Product Officer at Scaleway, presented a unique European perspective on AI. Scaleway has positioned itself as a vital cloud provider for startups, focused on training AI models in Europe without relying on U.S. or Chinese infrastructure. “We want to be the cloud of choice for European startups, supporting innovation while complying with European data laws,” Jan explained.
Jan explained that data sovereignty has become crucial for European startups. With increased global concern over data privacy and security, European companies are looking for ways to innovate without sacrificing control over their data. “We’re offering European startups a cloud solution that respects European data laws,” Jan explained. This ensures that companies can innovate and remain compliant with strict privacy regulations.
“Mission Possible: Supporting innovation
while complying with European data laws”
Scaleway’s infrastructure, which includes sustainable adiabatic data centers, operates with sustainability at its core. The company is proud of these data centers, which use 90 percent less water and dramatically cut electricity usage. “We’re building the cloud industry’s first environmental calculator,” Jan revealed, highlighting the company’s mission to help clients track and reduce their environmental impact.
This ethical approach to AI development is grounded in European data sovereignty and privacy values. The goal of Scaleway is to enable European startups and companies to lead in AI innovation within a fair balance of technical progress and ethical responsibility.
Building a responsible AI future
At VivaTech 2024, leaders from NVIDIA, Scaleway, Siemens, and Capgemini shared their perspectives on AI’s growing role in industries worldwide. While these companies are pioneering some of the most advanced AI technologies, they also emphasize ethical considerations, understanding that innovation without responsibility could lead to unintended consequences.
From AI-powered robots to sustainable cloud infrastructure, AI’s future lies in pushing technological limits and creating systems that enhance human creativity and foster trust. It’s about building ‘humble’ AI—tools that work alongside humans, acknowledge their limitations, and ensure transparency and fairness. This human-centered approach to AI isn’t just about compliance; it’s about forging a relationship between people and machines that benefits everyone.
When applied thoughtfully in industries like manufacturing, AI needs to be a reliable advisor before it can take on more responsibilities. This careful approach is mirrored across the board, with companies championing ethical AI development that aligns with sustainability and data sovereignty principles.
As AI continues to become part of society’s fabric, these industry leaders are setting the tone for a future where AI empowers rather than replaces the human workforce. These insights remind me that the AI revolution is still young, and the choices we make now will shape its impact on industries, economies, and everyday life. By aligning innovation with ethical standards, we can build an AI-driven future prioritizing human creativity, trust, and collaboration.
