AI is both material and partner. We show how generative and agentic systems widen search, tighten evidence loops, and scale analysis, prototyping, and evaluation—when embedded with goals, roles, guardrails, and escalation paths. The chapter covers data grounding, verification/validation, bias and safety, provenance from data to decision, and human–AI workflow design. The aim is dependable capability: systems that earn trust through transparency, testing, and governance.