Discover how AI is reshaping pharmaceutical industry. Insights from DCAT’s study explore adoption trends, challenges, and implications for the industry.
Artificial intelligence (AI) is poised to revolutionize supply chain management in the bio/pharma industry. A newly released study by the Drug, Chemical & Associated Technologies Association (DCAT) and insights from a panel discussion at DCAT Week explore AI’s potential, applications, and challenges in this sector.
AI in Supply Chain Management in the Bio/Pharma Industry
AI-based solutions promise significant benefits for the bio/pharma industry, which faces pressure to reduce costs, increase productivity, and ensure supply chain security. However, the latest study from DCAT Research & Benchmarking indicates that while AI has transformative potential, its adoption across the bio/pharma industry has been slow. The study, titled “The Emerging Role of Artificial Intelligence (AI) in Supply Chain Management,” was developed by the DCAT Research & Benchmarking Committee. This committee, comprising volunteers from DCAT Member Companies with diverse industry experience, sought to understand AI’s uptake in supply chain management, the challenges faced, and the impact on the bio/pharma customer-supplier relationship.
Study Objectives and Methodology
The study had four main objectives:
- Gauge the status of AI in supply chain management in the bio/pharma industry.
- Understand the challenges in implementing AI in the bio/pharma environment.
- Identify barriers to adoption.
- Help bio/pharma companies and their suppliers understand the impact of AI adoption on their operations and relationships.
To achieve these objectives, the committee developed a survey with approximately 20 content questions and several demographic questions. The survey targeted senior to mid-level executives at DCAT Member Companies and was conducted from mid-October 2023 to mid-January 2024.
Survey Results and Panel Discussion Insights
The survey results, unveiled at a special program during DCAT Week (March 18–21, 2024), and the subsequent panel discussion provided valuable insights into AI adoption trends, data challenges, and strategies to overcome resistance.
AI Adoption Trends
The survey received 41 responses from DCAT Member Companies. Of these, 11 companies (27%) are using or piloting AI applications for supply chain management. This includes 42% of bio/pharma company respondents and 21% of supplier company respondents. Companies using AI in supply chain management exhibit a strong corporate commitment to the technology. Over 80% of these companies consider AI “important” or “very important” to achieving corporate strategy objectives and use it across functions such as R&D, manufacturing, and general management. Common AI applications include demand forecasting, logistics, inventory management, and supply chain risk management. Machine learning is the predominant AI technology, with limited use of generative AI applications like ChatGPT.
Data Challenges
Data availability and confidentiality emerged as the most significant challenges in implementing AI for supply chain management. AI systems require vast amounts of data to be effective, and data from legacy systems often needs to be converted and cleaned. Bio/pharma companies face additional challenges related to data confidentiality and integrity, making it difficult to feed AI systems with the necessary information.
Overcoming Resistance
Nearly 80% of AI adopters reported resistance from within their supply chain organizations, and nearly 50% encountered pushback from corporate management. Panelists at the DCAT Week program emphasized the importance of addressing resistance directly and educating staff about the technology. They suggested focusing initial implementation efforts on applications with limited investment but significant payoffs. For example, using AI to negotiate payment terms can provide measurable benefits with relatively accessible data.
Encouraging Adoption
Responses from non-AI users indicated that adoption is hindered by a lack of understanding of the benefits and implications of AI applications and a lack of expertise to implement AI programs. AI-based service providers, such as Pactum and Everstream Analytics, explained that bio/pharma companies and suppliers could access AI technology without substantial internal investment. Focusing on narrow use cases with potentially large returns can help generate buy-in and fund further AI applications.
Impact on Suppliers
AI is expected to change the dynamics between bio/pharma companies and their suppliers. Over half of survey respondents with AI experience indicated that suppliers would need to provide more data about their operations, necessitating greater investments in information technology. Suppliers will also need to be more agile, as AI applications may lead to more frequent changes, such as redirected shipments and altered specifications. Person-to-person relationships may be augmented or supplanted by interactions with AI-driven systems. Late adopters need to prepare now to respond to AI-based systems implemented by their customers.
The DCAT study and panel discussion underscore AI’s transformative potential in bio/pharma supply chain management. Despite challenges, including data issues and internal resistance, companies that successfully adopt AI can achieve significant benefits in efficiency, cost reduction, and supply chain security. The path to AI adoption involves strategic focus, education, and leveraging external expertise to navigate the complexities and maximize the technology’s potential. As AI continues to evolve, its impact on the bio/pharma industry will likely deepen, reshaping operations and relationships across the supply chain.
Pharmaceutical Industry
Pharmaceutical Industry
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