Report **The AI Agenda 2026 — The reality check** from the **Oliver Wyman Forum** (the **Oliver Wyman** consultancy, **Marsh** group), a **91-page** PDF dated **October 15, 2026** (file metadata), prefaced by **John Romeo** (CEO) and **Ana Kreacic** (COO). Empirical base: two waves of the **Global Voices** survey (April, **N = 12,883**; August, **N = 12,837**; 15 markets including France), the **Oliver Wyman Forum × NYSE CEO Agenda 2026** survey (**415 CEOs**), parallel CEO / tech-leader surveys (**N = 200**), a **Sovereign AI Index** (top 100 economies), and three agent-purchase simulations. Overall thesis: *"AI is everywhere in our company except the P&L"*; AI capability is arriving faster than the decisions needed to extract value from it.
#AI ROI#return on intelligence#ROI harvester
Oliver Wyman Forum — préface de John Romeo (CEO) et Ana Kreacic (COO) ; cinq équipes d'auteurs par chapitre (Aaron Fine, Helen Leis, Adrian Oest, Daniel Cope, Abhishek Sharma et al.).
Editorial article **SFEIR AI** published on sfeir.com on **September 6, 2026** (~9,000 characters, seven sections, two sources noted). It recaps an episode of the **DataGen** podcast hosted by **Robin Conquet**, recorded at the **Dev Summit** co-organized by **Adeo** and **Decathlon** (Lille, **May 26-28, 2026**, more than **2,000** attendees), with **Matthieu Grymonprez**, who heads digital, tech, and data at Adeo (Leroy Merlin, Weldom, Obramat), and **Romain Taillade**, Global CTO of Decathlon. Three takeaways. **(A)** The platformization carried out over five years to absorb Leroy Merlin's marketplace (**60,000** in-store references, several million online) and Decathlon's expansion (**more than 50** countries) was not aimed at agentic AI, but forms its foundation: *"the platform built the muscles, the age of intelligence builds the nervous system."* **(B)** Three named workstreams — the development **harness**, zone-based **security** across the IT system (zero agentic activity on payment, the checkout flow, and the supply chain), and **data semantics**, tackled by vertical and where Adeo admits it is in debt. **(C)** A precedent the group paid for: self-service BI produced more than **150,000 dashboards** before the return to certified data products. Grymonprez's framing sentence holds it all together — *"an agent has no common sense"*: it applies the definition as given and accelerates disorder wherever it is lacking. Continues, with the same executive, [[alafrench-grymonprez-adeo-ia-agentique-grands-groupes-2026-06-18]].
#Agentic AI#platformization#API-exposed business domains
SFEIR AI (voix éditoriale du cabinet) · article non signé individuellement. Restitue un entretien de Matthieu Grymonprez (Adeo) et Romain Taillade (Decathlon).
In-depth opinion piece (point of view) published on **sfeir.com** on June 24, 2026, by **Didier Girard** (Managing Director, SFEIR). **Central thesis**: in 2024 everyone was betting on **AI4Business** (AI in business processes) as the great value reservoir; by 2026 the picture has **reversed** — it is **AI4IT** (AI to produce the information system: code, SDLC, software factory) that is creating **measurable** value. The article *grounds* this thesis in the firm's tech watch: AI4Business disappointment (the MIT study "95% of pilots without ROI," contested but revealing; an **organizational** blockage / Mollick's Hayekian problem) versus quantified AI4IT evidence (Salesforce, Intercom, Raiffeisen, AWS/Bedrock, Atlassian, DORA). Mechanistic explanation: **code verifies itself** (compilation, tests, CI) whereas business processes have neither a compiler nor an immediate feedback loop. **2027 budget consequence**: a **CapEx→OpEx** shift, token price dynamics (rising peak — Fable 5 at 2× Opus — vs inference ÷280 and downward pressure from open weights/desktop), and **AI FinOps** driven by **cost per outcome**. Closes with **4 recommendations for the COMEX**.
#AI4IT#AI4Business#reversal
**Didier Girard** — Managing Director (CTO / DG) de **SFEIR** · ESN française (~1 000 personnes, France · Belgique · Luxembourg · Suisse). Auteur de l'article ; voix éditoriale du cabinet sur la transformation IA des DSI.
Op-ed by **Olivier Rafal** (Consulting Director Strategy at **WeNvision**) published on **February 23, 2024** on **CIO-Online** (*Tribune* section), advancing a thesis still counter-intuitive at the time: **generative AI is more a matter of technology product than an AI/data science project**. **Argument 1 — data science is not the core issue**: building a *foundation model* from scratch requires *« several months, millions of euros, and access to enormous quantities of data »* — reserved for players with specific, monetizable datasets (e.g. **Bloomberg** and its **BloombergGPT** for finance). For nearly all companies, the right reflex is therefore not to hire data scientists. **Argument 2 — skills mismatch**: what is mainly needed is **development and integration engineers** (back/front), **strong cloud skills**, and **DevOps**. Client quote: *« You don't necessarily need to be a data scientist, but you need to understand the basic concepts, have back-office development skills, and strong cloud skills. »* **Argument 3 — platform architecture (orchestrators + APIs)**: building an enterprise **plateforme d'IA générative** via orchestrators and APIs makes it *« possible to work with the best LLMs on the market and switch between them as their respective capabilities evolve, without reworking the applications »* (anti vendor lock-in). **Argument 4 — from project to product**: *« The platform […] must be regarded as a product in its own right »*; instead of a one-off investment, plan for a **monthly funding stream** (continuous iteration, ongoing innovation). **Argument 5 — governance & shadow AI**: the unprecedented democratization of GenAI generates *« as much shadow AI as strong expectations toward the CIO office »* → governance to capture business needs, **prioritize products by value**, and oversee proper operation. **Paradigm shift** announced: *« the shift is from classic algorithmic programming to agents Langchain that handle part of the decisions »*. **Relevance to the watch**: a **founding text (2 years ahead)** of WeNvision's doctrine (product > project, platform/API, flow-based funding, governance, shadow AI), later extended by [[wenvision-ai-agents-enterprise-deployment-2025-10-01]], [[habert-ia-agentique-production-2025-10-29]], and rafal-wenvision-tokenomics-foundation-finops-ia-2026-06-04 (FinOps/token, flow-based funding → financial governance). It also foreshadows the *harness/platform around the model* (Dropbox/Okumura: *systems around the model*) and **model independence** achieved through an orchestration layer.
#generative AI#technology product#product vs project
**Olivier Rafal** · *Consulting Director Strategy* chez **WeNvision** (cabinet de conseil FR). Tribune publiée dans la rubrique *Tribune* de **CIO-Online**. Auteur déjà présent dans la veille (cf. fiches WeNvision/Atlas/Tokenomics). Publié le **23 février 2024**.