In treating patients with pancreatic cancer, multidisciplinary team (MDT) meetings have been established as the clinical standard for discussing patient cases using combined expertise from various specialisations. However, despite the combined expertise, 19%-33% of all pancreatic surgeries is observed to be prematurely abandoned due to locally advanced pancreatic cancer or metastatic disease. Furthermore, MDT meetings typically feature an open discussion format that can be subject to social influence factors affecting the overall objectivity of individual expert opinions. Subsequently, this research explores Artificial Swarm Intelligence (ASI) as a potential technology to overcome the aforementioned issues. Through an experiment, this research tests the use of ASI in a simulated MDT meeting and examines its effects on the accuracy of resectability assessment. Furthermore, a survey is conducted to assess the perceived impact of ASI on social loafing and social bias influences, as well as potential enablers and barriers for the potential implementation of ASI. Based on the experiment results, the use of ASI shows equal assessment accuracy compared to assessing tumor resectability through discussion as with regular MDT meetings. However, with regard to social influ- ence, participants assessed ASI to moderately drive reduction factors that reduce social loafing and social bias - suggesting indirect benefits to the objectivity of the decision process.