This white paper introduces the Agentic Technology Landscape Assessment (ATLA), a methodology pairing AI agents with human oversight to evaluate the secure integration of agentic AI systems in research and enterprise environments operating under restricted‑access data constraints. It outlines the motivation for ATLA and contrasts it with conventional Technology Landscape Assessments, highlighting how strict trust boundaries and data‑governance requirements reshape assessment workflows. The paper presents the ATLA execution lifecycle, the restricted‑access triage model, and the metrics used to evaluate actionability, risk mitigation, and operational impact, offering a clear foundation for organizations exploring agentic AI integration in high‑sensitivity environments.