AI ROI Analysis: Evidence from 200 B2B Deployments (Audited Dataset v1.3) Description (Abstract) : This longitudinal study provides an empirical analysis of 200 artificial intelligence (AI) deployments in French B2B companies (SMEs & Mid-caps) between 2022 and 2025. Unlike declarative surveys, this dataset relies on operational metrics (CRM exports, ERP data) and financial audits. Key Audited Findings (v1.3): Median ROI: +159.8% over 24 months (Conservative metric). Success Rate: 73% (27% of projects resulted in failure or negative ROI). Breakeven Point: 8 months (Median). Human-in-the-Loop: Projects maintaining human validation had 4.2x fewer critical incidents than fully autonomous workflows. Methodology & Integrity: Sample: 200 projects across Manufacturing (20%), Services (25%), SaaS (40%), and Retail (15%). Conflict of Interest Mitigation: The author served as an advisor for 82.5% of the sample. To mitigate bias, a third-party financial validation was performed on a random subsample of 30% of projects (Discrepancy rate: 340% ROI) were isolated to calculate a robust median. Dataset includes: Anonymized project attributes (Budget, Duration, Tech Stack). Calculated ROI and TTR (Time-to-Revenue). Failure root cause analysis.

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