When an AI system makes a decision in your name, can you prove what it did, why it did it, who authorised it, and how it was stopped? For most enterprises, the honest answer is no. Defensible AI is the practitioner's blueprint for the architecture that survives regulators, underwriters and litigation. Drawing on more than a decade inside fiduciary technology platforms, Aziz Ahmed exposes the dangers of "Liquid Evidence," the Great Liability Transfer from vendors to buyers, and the four-pillar Defensible AI Protocol that lets boards, CIOs and risk leaders deploy AI without losing control of accountability.