In this opinion piece published on sfeir.com (June 24, 2026), Didier Girard (Managing Director of SFEIR) argues a thesis: the AI4IT vs AI4Business reversal. In 2024, the consensus saw AI4Business — AI poured into business processes (sales, support, finance) — as the great reservoir of productivity; AI4IT (AI for producing the information system) was seen as a topic for engineers. Two years later, "the numbers have settled it, and the other way around."
The AI4Business disappointment: the 2025 MIT study ("95% of GenAI pilots with no ROI") is, by Girard's own admission — he disputes its methodology — questionable, but its persistence is the real signal of genuine dissatisfaction: many executives do not see the promised value in their processes. "The symptom is true even when the figure is false." The blockage is organizational (Mollick's Hayekian problem), not technical.
The AI4IT reversal rests on quantified evidence: Salesforce (+151% Effective Output, migration 18× faster, −5% incidents), Intercom (3× R&D productivity, −50% cost/PR), Raiffeisen Bank Ukraine (−8% headcount but 7 new products, −70% blocking incidents), AWS (Bedrock redeveloped by 6 people in 72 days), Atlassian (+19 to +87% PRs), DORA × Google Cloud (39% ROI, 8-month payback). Why? Code verifies itself (compilation, tests, CI); business processes do not. "We equip those who already know how to equip themselves."
The 2027 budget consequence comes down to three breaks. (1) CapEx→OpEx: the token becomes a variable OpEx charge — Arthur Mensch (Mistral) puts it at ~10% of payroll budget spent on tokens among advanced adopters. (2) Token pricing, a double trap: at a given capacity, inference has been divided by ~280 in two years, but the ceiling is rising (Fable 5 at $10/$50 = 2× Opus 4.8), while open models (GLM-5.2) and desktop inference push costs down; the Jevons paradox drives consumption up faster than the price falls. (3) AI FinOps: think in terms of cost per outcome, allocate by rules, turn token→outcome attribution into an asset.
Four COMEX recommendations: fund AI4IT first (payback < 1 year), budget for the J-curve, put token FinOps in place before drift sets in, redefine headcount accounting (humans + agents). Conclusion: "the next budget battle will not be about the price of the token, but about the cost per outcome."