Artificial intelligence is beginning to reshape how scientific organizations approach research, decision-making, and operational strategy, particularly in environments where complex datasets, specialized instrumentation, and multidisciplinary teams intersect. For many laboratories, the question is no longer whether AI has value, but how it can be deployed responsibly to accelerate discovery, enhance productivity, and support more efficient technical workflows. 

In this Q&A, Michael Connell, chief operating officer at Enthought, discusses how purpose-built AI is emerging in scientific settings, what lab leaders should understand about its capabilities and limitations, and where he sees the greatest opportunities for meaningful impact across research and industry.

Read the full article here here.