In-depth op-ed published on **sfeir.com** on August 1, 2026, signed **SFEIR** (the firm's editorial voice). It brings together **two July 2026 publications** with opposing methods — the preregistered field experiment **"The Cybernetic Teammate"** at **Procter & Gamble** (Dell'Acqua, Ayoubi, Lifshitz, Sadun, **Ethan Mollick** et al., *Organization Science* 37(4), 2026) and the first report in the **"Work at the Frontier"** series from **OpenAI Economic Research** (July 27, 2026, >800,000 messages from US ChatGPT users) — toward a single thesis: *"generative AI does not merely accelerate existing work, it redistributes who does what."* The architecture unfolds in four stages: **the mechanism** (P&G: AI acts as a *boundary-spanning* device, erasing functional silos — an individual + AI reaches the level of a pair without AI, **+0.37 σ**), **the scale** (OpenAI: **43.5%** of role-specific messages fall outside the user's own role), **the agenda** (Mollick: the walls are thinning, the division of labor must be rethought, and when well orchestrated this "pays off handsomely"), then **the firm's response** — the **Skill Based Organisation (SBO)**, adopted at SFEIR at the initiative of **Rosalie Zandona** (VP People & Culture): **genuinely operational skill** replaces the job description as the unit of organization (**up to 13 skills identified per role**), shifting from a **status-based identity** ("I am a manager") to an **operational identity** ("I know how to design complex architectures"). The rhetorical move is proof by internal example: *"we made the shift ourselves before recommending it."* ⚠️ **Three caveats on record**: the SBO shift dates to **February 2026**, so it *predates* the diagnosis it is supposed to resolve (the argumentative order reverses the chronological order); **nothing in the data demonstrates** that a skill-based organization absorbs crossover better than a role-based one (a design hypothesis, untested); the P&G result has been circulating **since March 2025** (NBER w33641), the "a few weeks earlier" applies to the peer-reviewed publication, not to the result.
#Skill Based Organisation#SBO#skill-based organization
**SFEIR** — ESN française « AI Only » (~850 ingénieurs, 8 agences France & Benelux). Voix éditoriale du cabinet (byline « SFEIR »).
Post and report from **OpenAI Economic Research** published on **July 27, 2026**, the first installment in the **Work at the Frontier** series, based on an analysis of **more than 800,000 messages from U.S. ChatGPT users**. **Coined concept**: ***task crossover*** — *« work historically associated with one occupation appearing in the AI use of people in another »*. **The headline figure is actually two figures, and that's the point most coverage loses**: **16.8% of work-related messages** concern tasks associated with a different occupation, and **43.5% of occupation-specific messages**. The funnel explains the gap: **61.5% of usage is generic** (writing, summarizing, planning — too widely shared to count as evidence of crossover) and is excluded; of the **remaining 38.5%**, **43.5% fall outside the occupation** and 56.5% are *« inside **or near** »* — the upper bound is thus calculated on a reduced base, the lower bound on the entire work-related usage. **By occupation** (share of occupation-specific messages pointing to an outside task): customer experience **77%**, design **75%**, HR **69%**, legal **56%**, marketing **53%**, sales **40%**, finance **40%**, engineering **28%** — *« a majority in five of eight groups »*. **Two distinct directions of circulation**: design **imports** (35.2%) and barely **exports** anything (1.7%); engineering does the opposite (imports 18.5%, exports 7.4%); **marketing accumulates both** (imports 24.3%, exports **8.9%**, the highest outward share in the sample). **Two tasks appear in the top 3 of borrowings for the other seven groups**: **financial calculation** and **technology troubleshooting**. ⭐ **The heatmap, absent from the coverage, is the richest object**: it gives the full distribution of tasks by user occupation, and its diagonal is striking — engineering retains **53%** of its own work while customer experience retains only **11%**, HR **10%** and design **12%**. **Size effect**: the outside-occupation share drops from **18.9%** (2-5 employees) to **16.3%** (>100 employees) — ⚠️ **but only "among average users"**, OpenAI noting that *« among the heaviest users, we do not see the same monotonic pattern »*, and concluding conditionally: *« AI **may be** especially useful as a generalist tool where specialist resources are scarce. »* **Claimed status**: an **early signal**, visible *« before firms rewrite job descriptions or create new job titles »*. ⚠️ **Structural caveat**: OpenAI measures OpenAI's own usage, on U.S. ChatGPT users only, and presents this position as an asset — *« our unique window into how the world of work is changing »*.
#OpenAI Economic Research#Work at the Frontier#task crossover
**OpenAI Economic Research** — équipe de recherche économique d'OpenAI ; la page crédite simplement *« OpenAI »* et la classe sous les tags *Economic Research* et *2026*. Le billet est la porte d'entrée d'un **rapport PDF** (`work-at-the-frontier-report.pdf`) et s'adosse à un cadre antérieur de la même équipe · l'**AI Jobs Transition Framework** · dont il reprend la thèse que de nombreux métiers vont **se réorganiser** plutôt que disparaître.