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The rapid advancement of digital ecosystems through the growing use of cloud, remote work, and intricate supply chains has posed a significant challenge to traditional, perimeter-based cybersecurity architectures. To address this challenge, the Zero Trust (ZT) model has emerged as a fundamental cybersecurity model based on the principles of "never trust, always verify," least privilege access, and continuous monitoring. This article provides a comprehensive examination of the status of Zero Trust implementation across industries, including the key strengths and entrenched weaknesses related to identity management, micro segmentation, telemetry, and automation. The results show that while inherent Zero Trust concepts have been widely embraced, their level of maturity remains variable due to disparate policy enforcement, legacy integration issues, and operational complexity. The convergence of DevSecOps initiatives, cloud-native applications, and benefits of artificial intelligence (AI) necessitates that Zero Trust be considered beyond the realm of static policies into adaptive, intelligence-driven architectures. Future work on developing Zero Trust principles focuses on continuous adaptive trust assessment, decentralized identity architectures, quantum-resilient methods for encryption, and privacy-preserving telemetry pipelines. The research concludes that the next generation of Zero Trust Security models must be cognitive, self-operational, and interoperable, to enable the integration of ethical design and human factors that can preserve usability in competitive marketplaces. This should be achieved in a way that provides a scalable and resilient connective infrastructure for securing digital enterprises in an increasingly dynamic threat landscape.

Keywords: Zero Trust; Identity Governance; Telemetry; Policy Orchestration; Micro-Segmentation; Phishing-Resistant Authentication; SBOM (Software Bill of Materials); Automation; Service Mesh; Credential Management; CARTA (Continuous Adaptable Risk and Trust Assessment); AI/ML (Artificial Intelligence / Machine Learning); Attestation Frameworks; Supply Chain Security; Trust Score Computation

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