Artificial intelligence in healthcare forecasting: Enhancing market strategy with predictive analytics

This research examines the transformative role of artificial intelligence (AI) and predictive analytics in healthcare market forecasting, with a specific focus on their application at Eli Lilly. AI-driven insights are becoming critical tools in anticipating market trends, assessing the impact of regulatory changes, and optimizing product positioning in the competitive global healthcare landscape. By leveraging machine learning algorithms and vast datasets, AI can identify patterns and correlations that traditional forecasting methods may overlook, offering companies like Eli Lilly a more comprehensive understanding of future market dynamics. The study explores how AI enhances decision-making by predicting healthcare market trends, particularly in response to regulatory shifts such as the U.S. Inflation Reduction Act. This legislative change, aimed at reducing drug prices and increasing market access, presents significant challenges and opportunities for pharmaceutical companies. AI allows firms to model the potential outcomes of such regulatory changes and adjust their market strategies accordingly. For example, predictive analytics can forecast the pricing pressures on specific drugs, helping companies develop competitive pricing models while maintaining profitability. Moreover, the research highlights the use of AI in mitigating risks associated with market volatility. By continuously analyzing real-time data, AI can detect early signals of potential disruptions—whether from economic downturns, competitor actions, or public health crises—allowing companies to take proactive measures. Additionally, AI-driven forecasting helps identify growth opportunities in emerging healthcare markets by analyzing demographic trends, disease prevalence, and healthcare infrastructure development. In conclusion, AI and predictive analytics are revolutionizing how healthcare companies like Eli Lilly approach market forecasting and strategy development. By offering deeper insights into future market conditions, these technologies not only reduce risks but also optimize product positioning and unlock growth opportunities in the global healthcare market. This research underscores the critical importance of AI in shaping the future of healthcare market forecasting. Keywords: Artificial Intelligence, Predictive Analytics, Market Forecasting, Regulatory Impact, Healthcare Strategy

Authors

Publication Details

Journal
International Journal of Applied Research in Social Sciences
Published
2024-10-16
DOI
https://doi.org/10.51594/ijarss.v6i10.1640
Citations
6
Primary Topic
Healthcare Systems and Public Health
Type
article
Field-Weighted Citation Impact
2.32
Controls
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article

Artificial intelligence in healthcare forecasting: Enhancing market strategy with predictive analytics

Victor Alemede, Precious Azino Usuemerai, Olumide Emmanuel Ibikunle, Akachukwu Obianuju Mbata et al.
6 citations
International Journal of Applied Research in Social Sciences
Healthcare Systems and Public Health
2.32
article

Artificial intelligence in healthcare forecasting: Enhancing market strategy with predictive analytics

Victor Alemede, Precious Azino Usuemerai, Olumide Emmanuel Ibikunle, Akachukwu Obianuju Mbata, Luqman Adewale Abass, Ejike Innocent Nwankwo
article en
6 citations

Abstract

This research examines the transformative role of artificial intelligence (AI) and predictive analytics in healthcare market forecasting, with a specific focus on their application at Eli Lilly. AI-driven insights are becoming critical tools in anticipating market trends, assessing the impact of regulatory changes, and optimizing product positioning in the competitive global healthcare landscape. By leveraging machine learning algorithms and vast datasets, AI can identify patterns and correlations that traditional forecasting methods may overlook, offering companies like Eli Lilly a more comprehensive understanding of future market dynamics. The study explores how AI enhances decision-making by predicting healthcare market trends, particularly in response to regulatory shifts such as the U.S. Inflation Reduction Act. This legislative change, aimed at reducing drug prices and increasing market access, presents significant challenges and opportunities for pharmaceutical companies. AI allows firms to model the potential outcomes of such regulatory changes and adjust their market strategies accordingly. For example, predictive analytics can forecast the pricing pressures on specific drugs, helping companies develop competitive pricing models while maintaining profitability. Moreover, the research highlights the use of AI in mitigating risks associated with market volatility. By continuously analyzing real-time data, AI can detect early signals of potential disruptions—whether from economic downturns, competitor actions, or public health crises—allowing companies to take proactive measures. Additionally, AI-driven forecasting helps identify growth opportunities in emerging healthcare markets by analyzing demographic trends, disease prevalence, and healthcare infrastructure development. In conclusion, AI and predictive analytics are revolutionizing how healthcare companies like Eli Lilly approach market forecasting and strategy development. By offering deeper insights into future market conditions, these technologies not only reduce risks but also optimize product positioning and unlock growth opportunities in the global healthcare market. This research underscores the critical importance of AI in shaping the future of healthcare market forecasting. Keywords: Artificial Intelligence, Predictive Analytics, Market Forecasting, Regulatory Impact, Healthcare Strategy

International Journal of Applied Research in Social SciencesVol. 6(10)
Industry, innovation and infrastructure
Openalex Percentile: Top 11%
Healthcare Systems and Public Health
2.32
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