Where EBITDA leakage actually hides in a mid-market business

The first pocket is SG&A and administrative process inefficiency — manual, exception-heavy back-office work such as accounts payable, reconciliations, and reporting that quietly inflates cost per transaction. APQC's data shows bottom-quartile AP functions cost four to five times the top quartile for the same task. The second is pricing and contract drift — margin lost to unmanaged discounting, unenforced terms, and renewals that are never repriced. The third is supply-chain and vendor concentration — overspend hidden in single-source dependencies and maverick buying, plus working capital trapped in extended days-sales-outstanding.

Each pocket is invisible on a standard P&L because it is spread across hundreds or thousands of small transactions, none material on its own. Traditional analysis samples; it cannot examine every invoice, contract line, and purchase order. This is precisely the structural advantage of agentic AI: it can interrogate the full transaction population rather than a sample, which is why it surfaces leakage that periodic audits and consulting reviews miss. It also explains why MIT found value accrues to workflow-level integration — the leakage lives in the workflow, not in the headline numbers.

The disciplined first move is therefore not deployment but diagnosis: a structured assessment that scores all three pockets against external benchmarks and produces a baseline before any technology is purchased.