In the past few years, artificial intelligence (AI) has grown tremendously in the life sciences. With a commitment to make data more accessible and actionable, and to provide insights into individual customer behavior, artificial intelligence technology has the potential to change the life sciences, business model, we know. But where do we start, and how can we stay successful?

Artificial intelligence
Artificial intelligence


In his report, "Life Science CIOs can accelerate business efficiency through new applications of artificial intelligence," Gartner points out: "The term "artificial intelligence" is used to describe a variety of technologies when life science CIOs are considering which AI investments to make. Will increase confusion and worry. Do."

Despite the company's massive investment in AI, the technology is rapidly evolving, and there are many bold claims about what value these systems can bring. Between companies, and even within companies, the interpretation of how AI can help a life sciences business team may vary.

One of the most common misconceptions is the idea of ​​using AI as an omniscient, omniscient program that answers unanswered questions. Although AI technology can solve many problems, the team must first solve an apparent problem and conduct a testing process.

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