AI Integration in Scientific and Clinical Research Management: Cost Reduction, Decision-Making and Leadership

Weiqi Jin

doi:10.54097/acagt923

Authors

Weiqi Jin

DOI:

https://doi.org/10.54097/acagt923

Keywords:

artificial intelligence, machine learning, Artificial intelligence labor training

Abstract

This essay investigates whether artificial intelligence can help the management department to reduce costs and decision-making within scientific and clinical research organizations. The research subject is mainly scientific and clinical research organizations, with the specific case study of Thermo Fisher Scientific. This case study examines the real-life application of AI within the company, showing AI’s ability to increase productivity, reduce costs, improve decision-making, and change leadership style. Looking into the recent literature, the essay discussed how AI such as Machine Learning and Deep Learning is implicated in the scientific and clinical field. Key challenges include high upfront costs, lack of technology experts, and concerns about data privacy. This essay concludes by providing possible solutions to cope with these challenges, which include AI training in labor, further research data on AI implementation in the real world and strict regulation on AI data privacy.

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References

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