Voice cloning detection and anti‑spoofing covers the technologies, processes, and governance needed to detect synthetic or impersonated voices and prevent fraud, misinformation, and unauthorized access. By 2026, increasingly realistic voice synthesis and wider deployment of voice agents have made reliable detection and auditable anti‑spoofing controls a business and regulatory priority for contact centers, security teams, and platform operators. Detection approaches include acoustic and spectral anomaly analysis, speaker verification with liveness checks, cryptographic watermarks, and behavioral or transaction‑context signals. Real‑time deployment is critical for contact centers and voice assistants, while forensic tools help post‑incident attribution and compliance reporting. Equally important are governance layers—policy, incident playbooks, and visibility into AI agents and integrations—to manage risk across enterprise workflows. Tools in this space play complementary roles: Observe.AI’s conversation‑intelligence and VoiceAI offering is positioned to embed detection and mitigation into live contact‑center workflows (real‑time assist, auto QA, and voice agents). Xilos-style agentic AI infrastructure provides enterprise visibility and auditability of agent actions and service connections, supporting governance and forensic trails. Knowledge and policy management (Notion) help operationalize anti‑spoofing rules, training materials, and incident playbooks. Document‑centric analysis tools (PDF.ai) speed ingestion and querying of research, standards, and contractual obligations relevant to voice security. Selecting effective defenses means combining signal‑level detectors with infrastructure logging, automation for triage, and clear governance processes. Organizations should prioritize deployable real‑time controls for customer‑facing systems, robust audit trails for investigation, and centralized policy and documentation to maintain compliance as voice synthesis capabilities evolve.