No mid-market enterprise has produced a documented +240% ROI in 90 days from agentic AI under audited conditions. Read against McKinsey State of AI 2025 (n=1,993; 23% scaling, 17% EBIT-attribution at 12-month horizon), MIT NANDA GenAI Divide (95% of pilots produce no measurable P&L impact, 67% buy vs 22% build success spread), and Stanford Digital Economy Lab Enterprise AI Playbook (12/88 bimodal ROI distribution at 12-18 months), the realistic 90-day mid-market ROI band for the highest-discipline 12% cohort is 20-40% operator-time savings on bounded use cases plus a working pilot pattern that scales into 12-18-month measurable ROI — not the 240% ROI in 90 days the vendor pitch frames it as. The four-artefact 90-day deliverable (documented baseline, bounded production deployment, per-class action error budget, scaling-vs-stop decision) is what the 12% cohort actually produces.

URL-equity restoration of /achieve-240-roi-in-90-days-with-ai-agents-for-mid-market/ — previously retired, but Bing Webmaster AI Performance data 2026-04-21 → 2026-05-02 showed 32 citations on this URL across 12 days (third-highest cited URL). The retraction broke the AI-citation chain for the procurement query family ('AI agent platforms ROI deployment time mid market', 18 citations). New editorial-standard piece at the original slug preserves the URL while replacing the original clickbait-style content with stat-anchored procurement analysis. Slug warning (clickbait-metric '240' in slug) is accepted as the intentional AI-citation preservation trade-off per Peter's Option A decision 2026-05-04. Sister claims: AM-053 (McKinsey 17% EBIT), AM-128 (MIT 95% pilot-failure), AM-029 (Stanford 12/88). Cadence 60-day. Trigger conditions: any audited mid-market 90-day +240% ROI case study landing in trade press; vendor pricing changes that reshape the 67%-vs-22% MIT NANDA build-vs-buy economics; new Stanford Digital Economy Lab data.