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AI Transformation Report

Publisher: Open Future Forum Research type: Executive benchmark report (cross-functional operator-research) Audience: Operating executives across finance, security, marketing, and technology functions Edition: Edition 1 Publication date: July 2026 Canonical source: https://openfutureforum.com/research/ai-transformation-report

Overview

The AI Transformation Report distinguishes AI adoption from AI transformation, defining transformation as movement across four markers: AI spend shifting from experimental to core budgets, output decoupling from headcount, whole units of work being handed to AI rather than merely assisted by it, and governance catching up to deployment. Its flagship metric, the AI Transformation Index, is designed to measure the share of operating executives who say AI is embedded in how their function runs versus deployed only in isolated workflows. The report states plainly that this flagship question has not yet been fielded; this edition establishes a seed baseline using proxy data.

Methodology & Sample

First-party data is drawn from Open Future Forum event records across twelve events in a July 2026 data pull, spanning finance, security, growth, founder, and investor rooms. Figures are reported as rounded floors of distinct applicants for demand/composition data, and from instrument questions (with stated response bases) for opinion data. Key bases include 185 (finance deployment-stage question), 87 (finance budget/sign-off questions), 38 (growth/agentic stage question, below the 40-response floor), and 26 (security questions, directional). External benchmarks (a16z, McKinsey, MIT, S&P Global, Gartner, BCG, KPMG, Wharton, US Census Bureau) are cited for context.

Key Findings

  • 71% of the largest Open Future Forum finance-room sample already runs an AI tool, indicating the network is broadly deployed rather than in early exploration — used as the seed series for the planned AI Transformation Index.
  • Despite high deployment, transformation markers lag: only 17% of finance respondents fund AI from money that would have gone to headcount, and 24% fund it from reallocated software budgets, while 46% still rely on net-new money — suggesting AI spend has mostly not yet displaced existing costs.
  • In the security lane, 69% of respondents have no dedicated AI security budget line even though 62% name securing AI agents as their top concern — framed as evidence that governance is the transformation marker lagging furthest behind deployment.
  • The CEO was the most-named signer of AI purchases (47%, base 87) while AI founders selling into companies target the CIO/CTO (43%) and business units — a "seat gap" the report argues complicates accountability for transformation outcomes.
  • External benchmarks cited for context show a similar pattern industry-wide: innovation-budget share of AI spend fell from 25% to 7% in a year (a16z) even though McKinsey found only 7% of firms have fully scaled AI, and Gartner expects over 40% of agentic AI projects to be canceled by the end of 2027.
  • The report cites a KPMG finding that the share of large ($1B+) organizations with deployed AI agents rose from 11% to 53% between early 2025 and mid-2026, while only 26% of those organizations have full real-time visibility into what their AI systems cost to run — a governance/cost-visibility gap consistent with OFF's own security-budget findings.
  • Pricing data from AI founders (53 of 83 charging founders price on usage or outcomes) is interpreted as a supply-side signal that vendors are already pricing for a transformed, outcome-measurable workflow that many buyer organizations have only partly reached.

Related OFF Research

Citation

Open Future Forum. The AI Transformation Report, Edition 1. July 2026. https://openfutureforum.com/research/ai-transformation-report

DOI

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