AI Blog

This is THE question that most leaders and innovation managers are asking themselves today. Between rare technical profiles, AI consultants, and employees in need of training, it's hard to know where to start. In this article, we help you identify the right profiles and structure an AI team adapted to your reality, whether you are an SME, a large group or a startup. Read the full article to discover the 5 key profiles that make it possible to effectively integrate AI into a business.

The pure SaaS model shows its limits: saturated market, slower growth, more demanding customers. At the same time, AI is paving the way for a new generation of businesses that merge technology and human expertise. This is called Service as a Platform (SaaP). This model no longer sells a tool, but a result. Find out why the most visionary players are adopting this approach, and how it could redefine your business.

Anticipating sales, avoiding stockouts, estimating the obsolescence of a product or forecasting demand: prediction is no longer science fiction, but a strategic lever for any data-driven company. In this article, learn how AI—from Machine Learning to Deep Learning to Language Models—is revolutionizing prediction, and how to choose the right approach for your business needs.

Faced with the frenzy around artificial intelligence, many are wondering if it is not a bubble. However, behind the fashion effect, AI is making a lasting impression in businesses. But before integrating AI into processes, one prerequisite is essential: having reliable, rich and well-structured data. This article explores why data is the foundation of any successful AI strategy and how businesses can prepare for it today.

All organizations seek to increase efficiency, reduce waste, and focus on adding value. But beyond classical methods, Artificial Intelligence is now opening up new perspectives. In this article, discover how AI can become a catalyst for Lean Management, with concrete examples and strategic courses of action.

Artificial intelligence is no longer a distant promise: it is already redesigning our jobs and our skills. Between new opportunities and a feeling of overwhelm, a LinkedIn study reveals how French professionals are experiencing this revolution. In this article, discover the most transformed sectors, the skills to be developed and the concrete strategies to succeed in the age of AI.

AI is disrupting employment, some positions are disappearing... but it is above all a transition. New jobs are emerging, productivity is increasing and data is becoming a strategic lever thanks to AI. Rather than a threat, it's an opportunity to reinvent work.

Artificial intelligence is emerging as a major driver of competitiveness. However, a study conducted by Think with Google and BCG reveals that the main obstacle to its adoption is not technological, but cultural. Businesses often find themselves torn between two crippling postures — fear of missing out (FOMO) and fear of doing wrong (FOMU). Conversely, those who succeed in taking advantage of AI take a third approach: the desire to maximize benefits (FOMA).

Are your AI projects waiting “waiting for perfect data”? And if it were the other way around: start to become more reliable more quickly. With the AI Act, data becomes an asset to be qualified, traced, explained — without immobilizing your teams. In this article, we show how to place AI in the right place in the flow, measure the gains (F1, completeness...), document each step and achieve concrete results in less than 60 days. Real cases, figures, operational method. The transition from diagnosis to impact is yours.

How do you know if your AI is really improving? Behind every successful data pipeline, there is an element that is often invisible but decisive: Gold. This reference data set makes it possible to objectively assess the progress of AI, to avoid perception biases and to align technological innovations with business priorities. This article explains why Gold is essential, how to design it, and how it transforms the governance of your AI projects.

Is your data really reliable? Each error, duplicate, or missing piece of information seems trivial, but added up, they cost businesses millions. What if your organization's biggest hidden expense was... in your data?

In a world where businesses are overwhelmed by data, the challenge is no longer to collect, but to transform this mass into concrete decisions. Discover how a pipeline powered by AI — from collection to action, including cleaning, enrichment and analysis — makes it possible to make information reliable, to anticipate trends and to make data a real strategic lever.

Choosing an AI agency is not an operational decision, but an act of governance. Behind each project is a central question: who will support your company in its digital transformation? More than a technological selection, it is a strategic choice. In this article, we explore the 7 fundamental questions to ask to identify an agency that can become a true partner, not just a supplier.

Businesses don't fail in their AI projects because of a lack of technology, but because of a lack of strategy, reliable data, and business adoption. This is where the AI agency comes in: a hybrid player, halfway between advice and execution, capable of transforming AI into operational and strategic leverage. Far from being a simple technical service provider, it is becoming a true Chief AI Partner, guiding the maturity of organizations and shaping the governance of tomorrow's AI. An article that dissects this new model, explores its future in the face of consulting firms, and proposes a concrete framework for choosing an AI agency.

Businesses have never had so much data. However, decisions have never seemed so complex. Why? Because the numbers remain isolated, devoid of context. From retail to real estate, the observation is the same: raw data is no longer enough. AI is changing that equation.