Laboratory automation is undergoing a significant transformation due to the increasing demand for efficiency, accuracy, and reproducibility driven by technology. Laboratories are adopting automation solutions to enhance productivity and make their traditional work processes more efficient. As a result, scientists can focus on more complex tasks that require human insight and creativity.

Artificial intelligence and machine learning-aided laboratory automation use analytical data and results to optimize experimental conditions, streamlining sample analysis preparation of reagents and result interpretation into timelines while limiting human error in the experiment with reliability.