AI governance is increasingly defined through ethical principles, regulatory frameworks, and organisational policies. However, as AI systems operate within contested digital environments, governance models that ignore cyber risk and forensic realities prove structurally inadequate. This article argues that effective AI governance in 2026 requires a shift from abstract frameworks to adversarial-aware control structures. By integrating cyber intelligence and forensic reasoning, organisations can design governance models capable of withstanding manipulation, system degradation, and post-incident scrutiny. Without this foundation, AI governance remains aspirational rather than enforceable, particularly in high-risk, automated decision-making contexts.