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5 Common Mistakes That Risk Your Pharma AI Efforts

By May 13, 2024July 22nd, 2024Marketing Services, Data & Analytics
Published Date: Monday, May 13, 2024
Last Updated on: Monday, Jul 22, 2024
AI in healthcare

This appears in Fierce Pharma online.

By Kelly Waller

While it’s true that artificial intelligence can occasionally falter, the last thing we want to do is compound these errors with misinformed data strategies. The risks are significant, particularly in the context of AI engagement.

This can be a tall order as the global pharmaceutical industry races to adopt AI technologies for patient engagement. Generative AI alone could unlock $110 billion in economic value annually for pharmaceutical and medical product companies, according to a 2024 McKinsey & Co. report.

Indeed, AI tech can produce blockbuster results. Novo Nordisk, the maker of the Ozempic, uses AI to process large volumes of data for clinical trials. These insights could improve drug adherence by pinpointing patient motivations and compliance challenges.

However, the urgency to incorporate AI into an overall data strategy can cause pharmaceutical companies to miss potential hazards, resulting in patients receiving the wrong messages. In our experience, five strategic factors can make a company vulnerable to these mistakes.

 

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