Artificial intelligence and machine learning have firmly established themselves as leading investment priorities across the pharmaceutical supply chain, with 96% of industry leaders placing the technologies among their top areas for investment, according to new research from LogiPharma.
The findings, gathered through a survey of pharmaceutical supply chain professionals ahead of the LogiPharma Digital Connect event later this year, also highlight the growing importance of advanced data analytics, identified as a key investment priority by 73% of respondents.
AI and agentic AI are now among the most frequently cited strategic priorities in the pharmaceutical supply chain sector, reflecting a shift in industry thinking around the role these technologies can play in improving operations and decision-making.
Among the areas attracting the greatest interest for AI deployment are demand planning and forecasting, inventory optimisation and logistics orchestration. These applications are increasingly being considered as potential ways for pharmaceutical companies to improve efficiency, manage inventories more effectively and coordinate complex logistics operations.
However, the research also points to significant challenges surrounding the wider implementation of AI. Governance, compliance and implementation remain important concerns for organisations, with regulatory uncertainty and compliance requirements identified as the single biggest barrier to broader AI adoption.
The industry also appears to remain cautious about AI’s ability to address supply chain disruptions. More than half of respondents said they were still uncertain about whether AI can deliver a meaningful improvement in disruption prediction and mitigation.
Another notable finding concerns the difference in investment priorities between AI and network optimisation. While AI was identified as a priority by 96% of respondents, network optimisation was selected by 53%.
This disparity reinforces recent findings from SkyCell, which described an ‘operational maturity gap’ between the visibility generated by AI and the systems available to organisations to respond when that visibility identifies potential problems.
The results suggest that pharmaceutical supply chain leaders are increasingly convinced of AI’s strategic importance, but that investment in the technology is not necessarily being matched by the operational infrastructure needed to act on the insights it provides.
“What’s particularly interesting is that the industry conversation has evolved beyond whether AI has a role to play in pharmaceutical supply chains,” said Ben Sharples, Event Director at LogiPharma Digital Supply Chain Connect.
The findings therefore point to an industry moving away from questioning whether AI belongs in pharmaceutical supply chains and towards a more practical debate over how the technology can be implemented, governed and connected to the operational systems required to turn its insights into action.
