Global Blog

The rapid ascent of Generative AI (GenAI), powered by sophisticated Large Language Models (LLMs), has captured global attention, demonstrating remarkable capabilities in content creation, summarization, and interaction. Businesses are actively exploring and integrating these tools to enhance productivity and unlock new avenues for communication. However, focusing solely on GenAI overlooks the next seismic shift in artificial intelligence: Agentic AI.

In today's relentlessly competitive business landscape, agility and informed decision-making are paramount. The ability to swiftly access and leverage an organization's collective intelligence can be the critical differentiator between thriving and merely surviving. Yet, beneath the surface of many enterprises lies a significant, often underestimated drain on productivity and innovation: the pervasive challenge of fragmented and inaccessible knowledge.

At the recent Artefact Data & AI Summit in Dubai, Vincent Luciani, Co-founder and Executive Chairman of Artefact, shared his insights on the evolving landscape of artificial intelligence. This article covers the main points from Vincent’s session, including the commoditization of AI, its impact on the workforce, the associated challenges and opportunities, and strategic recommendations for organizations.

Imagine a scenario where every operational data point of an industry is continuously captured, organized, scalable, and free from cyber threats. This is the concept of IT/OT (Information Technology/Operational Technology) convergence, an evolution where the synergy between data and technology optimizes efficiency, security, and innovation in manufacturing, enabling high-quality data and robust security that support reliable and strategic decisions.

The Artefact Research Center's mission is to foster an innovation ecosystem around AI and data by encouraging collaboration between university professors and representatives of international partner companies. The goal: cutting-edge research driven by data and the industrial applications of its partner companies.

Vincent Luciani, co-founder and Executive Chairman of Artefact, emphasizes that artificial intelligence (AI) must be concretely integrated into a company's collective processes, if it is to deliver real productivity gains. The entrepreneur will be taking part in the MKIA, an event organized by Maddyness and dedicated to AI, at the Salle Gaveau in Paris, on Tuesday April 29.

No strategy is effective without measurement! Choosing projects, evaluating the performance of AI agents or the hallucinations of the machine: detailed explanations of the governance you need to put in place to stand out from the crowd thanks to artificial intelligence.

In July 2024, Robin was promoted to CTO of Artefact France for his deep technology expertise and management skills. He now leads a large team of data scientists, software engineers and frontend developers, ensuring that his team is at the forefront of technology, with training and curiosity at the heart of his approach.

AI is rapidly evolving toward a future where users no longer think about models, modes, or tools. Instead, systems are becoming dynamically adaptive—automatically adjusting reasoning depth, selecting the right tools, and managing resources in real time based on task complexity.

As AI agents increasingly take over tasks like email drafting or resolving customer service issues, we face a pivotal challenge: how do these agents communicate effectively, not just with humans but with the software ecosystems they rely on?

Generative AI is profoundly reshaping the way we work, introducing tools that automate a wide range of tasks—from coding and data analysis to content creation. These tools don’t replace human expertise; they redefine it. Experienced professionals—whether engineers, analysts, or creatives—are becoming indispensable, not for execution, but for supervising, refining, and integrating the outputs produced by these technologies.

The journey from simple AI assistants to powerful, cross-system agents reflects a profound shift in how businesses leverage generative AI. In 2023, the rise of embedded GenAI promised seamless integration into daily workflows, enabling users to adopt advanced capabilities without disrupting habits. Yet, high costs per user and limited customization left many questioning the value proposition of these black-box solutions.

The adoption of Generative AI (GenAI) is unprecedented, highlighting both its transformative potential and the urgent need for businesses to adapt. Yet, most companies remain unprepared for the profound changes it brings.

In this episode of The Bridge by Artefact, Hanan Ouazan shares his expertise on AI Agents and their impact on automating business processes and accelerating productivity in the enterprise.

AI may be making the headlines, but Vincent Luciani is keeping a relatively low profile. Yet his company, Artefact, is a true success story from which many entrepreneurs can draw inspiration.

As a child, Vincent Luciani was passionate about chess. Although he often won against his little friends, he systematically lost out to the first artificial intelligences. “So, from an early age, I was confronted with AI,” smiles this pragmatist, for whom the best way to dominate it... is to create it. AI may be making the headlines, but Vincent Luciani is keeping a relatively low profile. Yet his company, Artefact, is a true success story from which many entrepreneurs can draw inspiration.

As a child, Vincent Luciani was passionate about chess. Although he often won against his little friends, he systematically lost out to the first artificial intelligences. “So, from an early age, I was confronted with AI,” smiles this pragmatist, for whom the best way to dominate it... is to create it.

As we enter 2025, artificial intelligence (AI) is transitioning from experimental research to real-world applications across industries. Below is a deeper dive into the critical trends shaping AI’s future, supported by relevant statistics and consumer-focused insights.

If your boss asks you for a critical number, and you use your company’s “Ultra Secure Internal GPT” to retrieve the information—only for the result to be incorrect—whose fault is it? The answer, as we all know, is yours for failing to validate the output. This creates a paradox: while companies push AI to accelerate decision-making, they place ultimate responsibility for AI-driven outcomes on humans. The question then becomes: What is the sweet spot between AI autonomy and human oversight?