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Explores how AI-driven lab automation unites robotics, computer vision, and machine learning to accelerate R&D. Details autonomous experiment design, data capture, and analysis; integration with LIMS/ELNs; digital twins; and closed-loop optimization. Highlights gains in throughput, reproducibility, and cost, plus guidance on compliance, data governance, and change management.