Case study ·
Oil shock, margins to recalculate: Renault turns to AI
Original title, in French: “Choc pétrolier, marges à recalculer : Renault mise sur l’IA”
- Publication
- Alliancy (France)
- Author
- Aude Brès
- Published on
- 16 October 2026 · read in the page structured data
Summary
Renault has overhauled the way it calculates its cost prices and margins using the Dataiku platform, used in a low-code/no-code mode, to respond to unprecedented economic volatility linked in particular to the share of electric vehicles doubling in three months following an oil shock. Laurent David, SVP Group Control, and Cédric Cazaly, COGS Factory & Transformation Director, describe a four-stage transformation carried out by multidisciplinary teams (data scientists, IT, management controllers) in three-week cycles, following a diagnostic in late 2024 that identified 130 pain points. Automation has eliminated more than 100 Excel files and covers 70% of data flows. Around ten AI agents and machine learning were then deployed, notably for memory chip availability. Since late 2025, the group's €30 billion in annual purchasing has been managed through Dataiku, with targeted savings of 6% over three years, according to Ilyas Galzim, Procurement Financial Insights & Analytics Director.
Summary based on the full text of the article.
Read the article on Alliancy →Figures cited
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130 pain points
number of pain points identified in the legacy IT architecture
Renault, diagnostic in late 2024
« ce travail a permis de recenser 130 points de souffrance, touchant à la fois l’organisation et l’efficacité opérationnelle, la data et sa qualité, ainsi que l’architecture et les outils »
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100 files
standalone Excel files eliminated through automation
Renault, finance/COGS function
« Cette phase a conduit à une automatisation massive et à la suppression de plus de 100 fichiers Excel isolés. »
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70 %
share of data flows automated
Renault, finance/COGS function
« 70% des flux de données ont ainsi été automatisés. »
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30 billion EUR
amount of the group's annual purchasing managed through Dataiku
Renault, since late 2025
« Depuis fin 2025, les 30 milliards d’euros d’achats annuels du groupe nécessaires à la construction de véhicules sont intégralement pilotés via Dataiku »
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6 %
targeted gains in purchasing economic performance over three years
Renault, purchasing department
« Les acheteurs peuvent également simuler la nomination des fournisseurs et optimiser la performance économique, avec des gains ciblés de 6 % sur trois ans. »
Classification
- Country
- France
- Company size
- Large companies
- Industries
- Industry and manufacturing · Banking, insurance, asset management, finance departments
- Companies
- Dataiku (supplier), Renault (deploys AI)
- Keywords
- management control, cost price, dataiku, AI agents, purchasing, automotive
Entry written by Marsanne Studio from the cited article, with the help of an AI model (claude-sonnet-5). The rights to the article and its illustrations belong to Alliancy and its author. Entry translated from French by Claude Sonnet 5.5.