How To Navigate AI Evaluation and Implementation in Healthcare

With no shortage of artificial intelligence solutions to choose from, healthcare organizations focus on the problems they want to solve.

Jordan Scott

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Traditional predictive artificial intelligence, generative AI and agentic AI are all being used in healthcare today. As organizations consider which tools to implement, it’s important that they take a step back to consider what problems they need solved. Starting with a problem and mapping that to an AI use case or other solution will lead to more success than implementing an AI tool for the technology’s sake.

However, even after mapping a problem to an AI use case, organizations can still run into trouble determining which solution is right for their needs. AI solutions are being added to the market at a rapid pace. Healthcare organizations can turn to a technology partner familiar with the AI landscape to help identify effective solutions that will meet their needs and bring the desired ROI.

Participants:

Bryce Thompson, Healthcare Strategist, CDW

Video Highlights:

Rather than starting with an AI solution, healthcare organizations should start with a particular problem and identify an AI use case that works.
When evaluating AI solutions, healthcare IT leaders should consider what the organization is trying to accomplish, the value a tool brings to the organization and whether it still makes sense after a cost-benefit analysis.
A partner can help healthcare organizations understand the AI solution landscape and prepare their IT and clinical environments for implementation.