AI blog

AI diagnostic is a methodical 4-step approach allowing companies to identify and prioritize opportunities for applying artificial intelligence in their specific context. Through a structured process of 10 days of guidance (framing, assessment, use case identification, recommendations), organizations obtain a clear vision of the most relevant AI projects to develop and a concrete action plan for their implementation. This pragmatic approach transforms AI from an abstract concept into projects with measurable added value, while raising awareness among teams about the challenges of digital transformation.

It is now possible to use your data effectively without recruiting a data analyst. Thanks to AI and accessible tools, managers, CFOs or business managers can obtain automatic analyses, ask questions in natural language, and manage their business without technical skills.

This guide helps businesses choose the right AI dashboard platform by comparing the best solutions based on key criteria: quality of insights, simplicity, security, security, integration, and advanced features.

Many businesses make strategic decisions based on dashboards that are visually flawless but fed by incorrect or incomplete data. This article explores the risks associated with poor data quality, the invisible errors in visualization tools, and best practices for making reliable analyses and making truly informed decisions.

LoRa is a lightweight and effective fine-tuning method for adapting a language model to specific business needs. Unlike full fine-tuning, which is more expensive, LoRa allows rapid specialization with few resources. It is an ideal solution for businesses that want to customize an AI model without heavy infrastructure.

Data quality is an underestimated strategic driver. Complete, accurate, consistent and up-to-date data is essential to effectively manage your business, avoid reporting errors, and make your decisions reliable. This article presents a concrete method in three steps — audit, cleaning, governance — and shows how adapted tools (including AI) make it possible to structure your databases sustainably. The result: time savings, better internal coordination, and truly useful analyses. Clean data is the starting point for all sustainable performance.

ChatGPT now offers native integration with SharePoint (in beta for Plus, Pro, and Team users). This feature makes it possible to conduct in-depth searches of internal documents, to generate summaries, briefs or analyses based on data stored in SharePoint — while respecting access rights. A significant time-saver for teams working with information spread across multiple sites or departments.

The rise of AI is forcing agencies to reinvent themselves: while brands now internalize content and campaigns at a lower cost, agencies must abandon execution to offer greater strategic value (market expertise, AI workflows, AI workflows, training, data intelligence). Their future lies in orchestration rather than production. Trying Claude again can make mistakes. Be sure to check his answers.

AI agents allow SMEs to automate up to 30% of recurring analytical tasks, such as generating reports or monitoring KPIs. Easy to implement with low-code tools and connected to internal data, they free teams from manual tasks to focus on strategic analysis. This technological lever, accessible and pragmatic, reinforces productivity and responsiveness without complicating the organization.

Canva shows that well-integrated AI can simplify the experience rather than complicate it. With its Studio 2.0 Suite, the tool combines creativity and productivity, making creation faster, more intuitive and accessible to everyone, without sacrificing the simplicity that makes it so successful.

In a world where agility and responsiveness have become strategic imperatives, decision-makers are increasingly turning to real-time insights to inform their choices. A recent study reveals that 51% of business leaders plan to adopt real-time analytics solutions in order to speed up their decision-making process.

Artificial intelligence makes it possible to automate the enrichment of product sheets on a large scale, by generating personalized, SEO-optimized, translated, and A/B testable descriptions. The result: considerable time savings, better catalog consistency, and increased sales performance (+10 to +25% conversion). A particularly useful strategy for e-retailers and B2B/B2C businesses with a large catalog.

Why is the AI ambition of companies coming up against the reality of insufficient data quality? Discover the findings of the “2025 Outlook: Data Integrity Trends and Insights” study and the solutions to strengthen your data foundations.

ChatGPT integrates a new shopping feature, allowing you to search, compare, and explore products through a simple conversation. With no ads or direct purchases, the tool offers a smooth, useful, and structured experience based on trusted sources. This evolution shows how AI can simplify everyday decision-making.

What if expertise no longer stopped at a deliverable, but became a living, evolving platform that was continuously accessible thanks to AI? This is precisely what we have been exploring at Strat37 for over a year: a hybrid approach where expertise is no longer delivered as a static service... but as a living, modular and scalable platform. The observation: → Standardized SaaS, even when doped with AI, struggle to meet specific strategic challenges (except in cases of ultra-verticalization). → Traditional consulting, although rich in value, often dies out once the mission is over. In this article, I am sharing our feedback with you: how AI is becoming the bridge between these two worlds, by giving birth to a new form of service — Service as a Platform (SaaP) — that sustainably transforms the relationship between expertise and technology. 📌 We talk about modularity, customer co-management, integration, and continuous learning. And you, have you already implemented SaaP in your organization? What brakes or levers did you identify?