aspg-37-4402-1792223298 20261017074818 American Scientific Publishing Group admin@americaspg.com American Scientific Publishing Group Financial Technology and Innovation FinTechI 2836-5372 2025 5 1 Mahmoud A. Zaher Data Science Department, Faculty of Artificial Intelligence, Horus University (HUE), Egypt The rapid institutionalisation of artificial intelligence across financial services, healthcare, technology, and the public sector has generated a parallel proliferation of governance frameworks, ethical principles, and regulatory instruments that collectively demand organisations translate abstract values into operational practice. The gap between stated principle and enacted governance—what we term the responsible AI implementation gap—is now recognised as one of the central practical challenges in AI deployment, yet its magnitude, distribution across sectors, and organizational determinants remain poorly characterised in the empirical literature. This paper addresses that gap through a three-phase mixed-methods programme combining systematic analysis of publicly available governance frameworks, a cross-sector practitioner survey, and a governance maturity scoring exercise. Significant variation is documented across sectors on all five governance dimensions examined, with the technology sector leading on accountability and transparency, healthcare on privacy and human oversight, and the public sector on regulatory compliance readiness. Across all sectors, however, a persistent and pronounced gap exists between the governance principles that organisations formally endorse and the operational processes through which those principles are enacted: the average policy-to-practice gap across all eight governance principles assessed is consistent and substantial. Regression analysis identifies the presence of a dedicated responsible AI team as the single strongest organisational predictor of maturity, followed by staff training investment and senior executive sponsorship. The paper contributes a validated governance maturity framework, a framework coverage taxonomy for twenty-four public AI governance instruments, and six evidence-based implementation guidelines for organisations seeking to move from principle adoption to genuine operational accountability. 2025 10 23 4402 https://creativecommons.org/licenses/by/4.0/ 10.54216/FinTech-I.050102 https://americaspg.com/journal/37/article/4402 https://americaspg.com/storage/articles/manuscripts/01KV3JAN1WJXZ1CH1VW1DWS1FZ.pdf