
REFERENCE
Usable data: the raw material of AI
No clean data, no useful AI: usable data — available, reliable, structured, documented — is the first line in the budget and the schedule. The first project is not AI; it is the data.
Our mission: give the leaders of SMBs and mid-market companies a fact base, clear pointers, and real cases to decide on their AI — and move from ambition to execution.
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REFERENCE
No clean data, no useful AI: usable data — available, reliable, structured, documented — is the first line in the budget and the schedule. The first project is not AI; it is the data.

REFERENCE
A pilot is not a showcase: it is a decision tool — brief, quantified, and dated — whose sole mission is to say whether an AI project deserves to scale. And scaling is prepared during the pilot, never after.

REFERENCE
The license price is not the project cost: setup, change management, and operations add up. Data and adoption — the two invisible costs — often outweigh the license.

PERSPECTIVE
AI is not what gets bought: what gets bought is the resolution of a named problem, on owned data, toward a measured result. Three decisions belong to the leader before any purchase — the problem, the data, the measure of success.

PERSPECTIVE
AI ideas abound and the technology is available: what blocks companies is the absence of a decidable first project — bounded, quantified, dated. A committee decides on a specific project, never a vague ambition.

REFERENCE
A use case is neither "AI" nor a tool: a precise, repeated task where the machine delivers a measurable gain. Six categories to classify, one grid to choose the first case — real, measured, repeated.

REFERENCE
The ROI of an AI project is not measured at the end: it is made calculable at the outset. An honest total cost (three components), a net gain read in the books, two horizons — 12 and 24 months. AI pays off for those who know what it replaces.

REFERENCE
Buying means renting a proven capability; building means funding an asset and its upkeep. For most SMBs and mid-market companies: buy and integrate — custom development is only justified by a proprietary advantage worth protecting.
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The analysis to read first this week.

FOUNDER · EVERY WEDNESDAYFEATURED
A ten-person firm goes deep on AI as often as a five-thousand-person one.
More featured articles

ANALYSISFINANCIAL SERVICES
Finance deploys AI more than any other sector (92% of EU banks, 200,000 employees equipped at a single bank), yet only 4 banks in 50 prove their ROI. Three decision regimes, four fault lines, and a decision tree for where to start.

ANALYSISINSURANCE
Insurance is the economy's most AI-equipped sector — yet only 10% of insurers have industrialized it, while catastrophe losses top $100bn for the sixth year. Six use-case families, four breaking points, five 90-day decisions.
FOUNDER · EVERY WEDNESDAY

ANALYSISTRANSPORT & LOGISTICS
Transport uses AI half as much as the average economy, while failures and the driver shortage squeeze the sector. Six documented use-case families and five 90-day decisions to join the first movers.
FOUNDER · EVERY WEDNESDAY
Siparex and Bpifrance documented twenty completed AI projects in French SMEs and mid-market companies: 70% cost between 15,000 and 100,000 euros and 80% shipped in under six months. The Aldes case: 40,000 euros, five months.

ANALYSISRETAIL & DISTRIBUTION
A third of customers already shop with AI; 13% of retailers use it. Six documented use-case families and five 90-day decisions to join the 26% that scale.
FOUNDER · EVERY WEDNESDAY
AI drafts faster, but speed is not accuracy. The lesson from Ashurst: where a signature commits you, review is not overhead, it is the product.
FOUNDER · EVERY WEDNESDAY
Your teams are already using AI, with or without you. The lesson from BBVA: you don't control enthusiasm, you channel it. Two rules, a sharing ritual, and something better than the free tool.
Four ways into the fact base.
Lessons and convictions from the field.
Where a sector stands on AI.
Definitions, methods and key figures.
The daily brief: one fact, one source, one implication.
The weekly note from Arnaud Quintin, founder of YPrtnrs: one case, one lesson, one live project.
All our publications, most recent first.

ANALYSISFINANCIAL SERVICES
Finance deploys AI more than any other sector (92% of EU banks, 200,000 employees equipped at a single bank), yet only 4 banks in 50 prove their ROI. Three decision regimes, four fault lines, and a decision tree for where to start.

FOUNDER · EVERY WEDNESDAY
A ten-person firm goes deep on AI as often as a five-thousand-person one.

ANALYSISINSURANCE
Insurance is the economy's most AI-equipped sector — yet only 10% of insurers have industrialized it, while catastrophe losses top $100bn for the sixth year. Six use-case families, four breaking points, five 90-day decisions.
FOUNDER · EVERY WEDNESDAY

ANALYSISTRANSPORT & LOGISTICS
Transport uses AI half as much as the average economy, while failures and the driver shortage squeeze the sector. Six documented use-case families and five 90-day decisions to join the first movers.
FOUNDER · EVERY WEDNESDAY
Siparex and Bpifrance documented twenty completed AI projects in French SMEs and mid-market companies: 70% cost between 15,000 and 100,000 euros and 80% shipped in under six months. The Aldes case: 40,000 euros, five months.

ANALYSISRETAIL & DISTRIBUTION
A third of customers already shop with AI; 13% of retailers use it. Six documented use-case families and five 90-day decisions to join the 26% that scale.
FOUNDER · EVERY WEDNESDAY
AI drafts faster, but speed is not accuracy. The lesson from Ashurst: where a signature commits you, review is not overhead, it is the product.
FOUNDER · EVERY WEDNESDAY
Your teams are already using AI, with or without you. The lesson from BBVA: you don't control enthusiasm, you channel it. Two rules, a sharing ritual, and something better than the free tool.
The information you need to act better and faster.
Read-only snapshot of the Institute's published content as of 2026-10-05.