Insight by: Jon Warner, Executive Chair of Citizen Health Strategies (CHS)
Artificial Intelligence (AI) is revolutionizing various sectors, and the pharmaceutical industry is no exception. However, the rapid evolution of AI technology presents unique challenges for small, medium, and large organizations in this sector. This brief article explores these challenges and the implications for future skills and personnel needs.
AI has the potential to transform the pharmaceutical industry, from drug discovery to patient care. However, the fast-paced nature of AI technology presents several challenges. These challenges vary depending on the size of the organization, with small and medium-sized enterprises (SMEs) facing different issues compared to large corporations.
AI Challenges in Pharma by Organization Size
Small and Medium Enterprises (SMEs)
- Limited Resources: SMEs often lack the financial resources to invest in advanced AI technologies. They may struggle to afford the high costs of AI software, hardware, and data storage. Additionally, they may not have the budget to hire AI specialists or train existing staff.
- Lack of Data: AI algorithms require large amounts of data to function effectively. SMEs may not have access to the vast datasets that large corporations do, limiting their ability to leverage AI.
- Regulatory Compliance: SMEs may struggle to navigate the complex regulatory landscape surrounding AI in healthcare. They may lack the legal expertise to ensure compliance with data privacy laws and other regulations.
Large Corporations
- Legacy Systems: Large corporations often have established IT infrastructures that may not be compatible with new AI technologies. Integrating AI into these legacy systems can be complex and costly.
- Data Privacy and Security: Large corporations typically have access to vast amounts of sensitive patient data. Ensuring the privacy and security of this data when using AI is a significant challenge.
- Change Management: Implementing AI can require significant changes to business processes. Managing this change, particularly in large organizations, can be difficult.
The Implications for Future Skills and Personnel
The rise of AI in the pharmaceutical industry at all levels and common to every size of firm is people. In other words, all of the above has significant implications for the skills and personnel likely to be needed in the future, and they must have the ability to both pay attention to AI development and to learn new skills as the tools available involve. This will also means:
- Increased Demand for AI Specialists: There will be an increased demand for AI specialists capable of developing and implementing AI solutions. These specialists will need a combination of technical skills (such as programming and data analysis) and industry knowledge.
- Need for Continuous Learning: Given the fast-paced nature of AI technology, continuous learning will become increasingly important. Employees will need to regularly update their skills to keep pace with technological advancements across all the current AI realms (LLM’s Agents, etc.) and new areas as and when they arise.
- Importance of Soft Skills: While technical skills are important, soft skills such as problem-solving, creativity, and adaptability will also be crucial. These skills will help employees navigate the challenges presented by the rapidly evolving AI landscape.
Conclusion
The rapid evolution of AI technology presents unique challenges for organizations in the pharmaceutical sector at all levels (even though they are some specific differences that should also be considered). By understanding these challenges and preparing for the future skills and personnel needs, pharmaceutical organizations can position themselves to successfully leverage AI and progressively transform the industry. The key to this future is the right people with the right knowledge and skills at all levels.
