Choosing AI Projects That Deliver Value for Your Lab

As organizations look to adopt AI, how do you decide where it can deliver meaningful value in your lab? Start with a problem worth solving, measurable goals, and a clear understanding of what success looks like. The right opportunity must fit your lab’s workflows and offer benefits that justify the effort required to implement and sustain it.

Through a practical laboratory example, this session explores how to evaluate an opportunity, determine whether AI is the right approach, and select a manageable pilot. Participants will learn to weigh expected benefits against implementation demands, including data readiness, staff training, and ongoing human review. You’ll leave with a practical framework for making investment decisions and using pilot results to determine what comes next.

Key learnings:

• Define a business need and measurable goals before selecting an AI tool.
• Assess whether AI, existing automation, or a process change best addresses the problem.
• Choose a pilot that fits your lab’s resources and readiness.
• Account for implementation costs and ongoing human oversight when evaluating value.
• Use pilot results to decide whether to expand, adjust, or stop a project.