Artificial Intelligence (AI) is transforming society's digital landscape, redefining knowledge work and how we produce and consume information. Yet, extending AI into the physical world raises major challenges—not only in terms of the technological requirements to embody intelligence that interacts with physical environments, but more importantly, in the lifecycle and systems engineering necessary to deploy these systems with justified confidence that their benefits will outweigh the risks. This talk focuses on accelerating the deployment of advanced, embodied AI capabilities to operations, highlighting advanced research performed at the Lockheed Martin Advanced Technology Laboratories. Throughout the presentation, we illustrate our points using disaster response use cases, starting with the presentation of a continuous knowledge-compounding lifecycle. We then cover examples of ongoing work, including the application of generative AI for systems engineering, leveraging digital twins for advanced Test, Evaluation, Verification, and Validation (TEVV), and evaluating operational effectiveness alongside normative compliance.