Agentic R&D: Orchestrated AI Systems for Research and Development (AI and Agents in industrial operations)

Agentic R&D presents a practical and technical blueprint for applying agentic artificial intelligence to research and development organizations. Moving beyond isolated AI assistants and experimental automation, the book explains how orchestrated, multi-agent systems can plan, execute, and continuously improve R&D workflows while preserving scientific rigor, safety, and governance.At the center of the approach is the R&D Orchestrator—a control layer that coordinates specialized agents across literature review, hypothesis generation, simulation, experimental design, lab execution, data analysis, documentation, and knowledge transfer. The orchestrator manages context and memory, enforces policies and approvals, integrates with core R&D platforms (ELN, LIMS, PLM, simulation tools), and provides full traceability and observability across agent actions.The book introduces a strategy-to-execution framework that links R&D objectives—speed, cost efficiency, reproducibility, compliance, and IP protection—to deployable AI capabilities. Readers learn how to design agent roles, build safe tool interfaces, implement closed-loop experimentation, and operate agentic systems in regulated and safety-critical environments.Written for R&D leaders, digital transformation teams, platform engineers, and applied AI practitioners, Agentic R&D combines architectural guidance, operating models, and real-world solution patterns. A dedicated vendor chapter explains how leading R&D software and automation platforms can be integrated into agentic workflows. The result is a clear, actionable path from concept to production-grade deployment of AI in research and development. Read more