Short answer: In June 2026, QoEAgent co-founder Josh Cashman published a contributed article in ACG Insights explaining how AI is eliminating the 8–15 hours of data-preparation work that precedes every lower-middle-market quality of earnings engagement.
The article — AI Tackles the Lower Middle Market’s QoE Data Problem — explains why the lower middle market ($5M–$50M enterprise value) is where the QoE data problem is most acute, why AI can now handle the variability in privately held company books, and how QoEAgent’s Flash Proof of Cash gives deal teams a high-confidence preliminary reconciliation before full diligence resources are committed.
Key findings:
- 8–15 hours per engagement is the average time spent on data preparation alone — before a single EBITDA adjustment is evaluated.
- Lower-middle-market sellers rarely provide audited financials; books arrive as QuickBooks exports, bank PDF statements, and ad-hoc Excel schedules requiring manual normalization.
- AI trained on diverse financial document sets can now map chart-of-accounts labels across industries and institutions without human intervention.
- The Flash Proof of Cash is designed to run during the LOI-to-diligence window, giving advisors a go/no-go signal before full scope is set.