As pharmaceutical executives grapple with a growing array of complexities, costs and regulations, a greater number of them are turning to artificial intelligence (AI) as a possible solution. As a matter of fact, a recent global market report for the pharmaceutical industry suggests that spending on AI will surpass $3.6 billion by 2026. Use cases for the technology include applications for drug discovery, manufacturing, diagnostic assistance, drug commercialization and business operations. Yet, despite the industry’s commitment of capital and resources to the promising technology, confusion remains among executives about how to best utilize AI.
Especially in the pharmaceutical industry, requirements for data integrity, compliance and government oversight all create an environment where risk mitigation often outweighs continuous innovation. However, I believe pharmaceutical companies can utilize best practices in order to ease the transition to AI tools that can enable insights and shortcuts.
Implementing AI Applications Within New Environments
It’s important to note that the AI’s algorithms don’t just invent information. They need to derive their actionable insights from the data you already have. A critical first step for any organization looking to utilize AI is getting your data in order. The benefits of AI-powered insights are clear, but those capabilities will remain unachievable if an organization’s data management practices remain basic. And no matter how innovative an AI’s algorithms are, results will be disappointing if they run on top of scattered, inconsistent and outdated data.
While AI can take years of sales data and scientific findings and organize them in minutes to uncover precious insights, for companies that have not worked with AI previously, this can mean a complete reorganization of their data foundation and digitization of offline records.
Continue reading: https://www.forbes.com/sites/forbesbusinesscouncil/2022/10/20/how-ai-can-improve-pharmaceutical-commercial-operations/?sh=4302e8f97663
Especially in the pharmaceutical industry, requirements for data integrity, compliance and government oversight all create an environment where risk mitigation often outweighs continuous innovation. However, I believe pharmaceutical companies can utilize best practices in order to ease the transition to AI tools that can enable insights and shortcuts.
Implementing AI Applications Within New Environments
It’s important to note that the AI’s algorithms don’t just invent information. They need to derive their actionable insights from the data you already have. A critical first step for any organization looking to utilize AI is getting your data in order. The benefits of AI-powered insights are clear, but those capabilities will remain unachievable if an organization’s data management practices remain basic. And no matter how innovative an AI’s algorithms are, results will be disappointing if they run on top of scattered, inconsistent and outdated data.
While AI can take years of sales data and scientific findings and organize them in minutes to uncover precious insights, for companies that have not worked with AI previously, this can mean a complete reorganization of their data foundation and digitization of offline records.
Continue reading: https://www.forbes.com/sites/forbesbusinesscouncil/2022/10/20/how-ai-can-improve-pharmaceutical-commercial-operations/?sh=4302e8f97663
