In this opinion piece published on sfeir.com (July 23, 2026), SFEIR comments on the Trésor-Éco No. 391 note from the DG Trésor (June 2026) and anchors it to its own doctrine: « amplifying AI rather than enduring it ». The article praises Bercy's cautious tone — which lays out mechanisms and uncertainty rather than settling the matter — and draws from it a three-part thesis « more reversed than it appears ».
No aggregate effect. Within the Acemoglu-Restrepo framework, two forces oppose each other: the displacement effect (substitution) and the productivity effect (complementarity, lower costs, increased demand). They currently offset each other; studies identify no aggregate effect, for lack of hindsight and adoption (~20% of EU firms). Individual gains are nonetheless real (+14% in customer service, +26% among developers), but anxiety outpaces the data (62% of French people worried).
Turning adoption into a lever rather than a pile of POCs.
The only solid signal: juniors. −16% employment among exposed 22-25 year-olds in the US (Brynjolfsson 2025); in France, a contraction in youth employment in IT and rising unemployment among 15-24 year-olds (19.1%→21.1%) — without established causality. The mechanism: AI automates the codified tasks of entry-level positions, the ones that « used to train tomorrow's seniors » — hence a renewal-of-expertise issue.
The argument the debate misses. A profession's fate hinges on the price elasticity of demand, not exposure: developers and graphic designers (elasticity > 1) see demand grow as AI lowers their costs — the Jevons paradox applied to code. The argument is structurally pro-employment for developers. The article also dismantles the "AI layoffs" narrative (4.5-6.2% of US layoff announcements; labeling at 59%) and points to the note's blind spots: the agentic scenario relegated to a footnote (which would invalidate the "assistant" framework), diffusion speed left undiscussed, and source bias (OpenAI/Anthropic having become sources for Bercy).
The real fault line: competitive lag. Bercy shifts the burden of proof — the risk is competitive (falling behind in adoption), not social. Hence the programs (« Osez l'IA », France 2030).
SFEIR's perspective: for a CIO/CTO, this translates into decisions — value migrates toward intent/architecture/control; train augmented engineers (AI Champions); avoid rushed adoption (workslop, technical debt) through context engineering, governance, and POC-to-production criteria. « Turning adoption into a lever rather than a pile of POCs. »