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Transformation & Adoption Auto-verified translation

AI4IT vs AI4Business : le renversement, et ce qu'il fait à vos budgets 2027

In-depth opinion piece published on **sfeir.com** on June 24, 2026, authored by **Didier Girard** (Managing Director, SFEIR). **Central thesis**: in 2024 everyone was betting on **AI4Business** (AI in business processes) as the great reservoir of value; by 2026, the assessment has **flipped** — it is **AI4IT** (AI for producing the information system: code, SDLC, software factory) that creates **measurable** value. The article *grounds* this thesis in the firm's watch: AI4Business disappointment (MIT study "95% of pilots without ROI," contested but revealing; **organizational** blockage / Mollick's Hayekian problem) vs. 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 pricing dynamics (the ceiling rising — 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 COMEX recommendations**.

#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.

Transformation & Adoption Auto-verified translation

How Cornell Recovered $100,000 in Unidentified Payments With AI

Case study published by the **Cornell AI Innovation Hub** (June 15, 2026): how a two-semester collaboration between the AI Hub, graduate students, and Cornell's Treasury team turned a time-consuming manual investigation into an AI tool that **recovered $100,000** in unidentified payments on a first batch. A successful **AI4Business** use case (financial process) that illustrates the **Leader-Lab-Crowd** framework of **Ethan Mollick** almost point by point: the **AI Hub** plays the role of the **Lab** (a central, ambidextrous team of technologists plus students); **Treasury** (Cheryl Barnes, Marie Graves…) is the **Crowd** carrying business knowledge and the real pain point; and the **$100,000** constitutes the **visible reward** (vivid win) that anchors adoption — exactly the incentive lever Mollick considers decisive. Key method: **"context first, then plan, then build"** via **Claude Code Plan Mode**, a chain of **fuzzy matching → Gemini Enterprise Web Search → Claude synthesis**, all within the governed **Cornell AI Gateway**. *"The $100,000 is a start."*

#Cornell AI Innovation Hub#unidentified payments#payment reconciliation

**Pete Stergion** — Desktop Engineer au Cornell AI Innovation Hub · co-tech lead du projet (avec Phil Williammee). Article institutionnel signé de l'AI Hub.