Background: When it comes to how Supply Chain (SC) works, it can often be viewed as a chain linking entities together. The linking process can often be viewed as collaboration between two or more SC partners. Without a connection, or collaboration, goods cannot circulate between the beginning of the chain all the way to the end of the chain. This is why collaborating with your partner and being aligned on the same level is important, which is often not the case, as struggles typically appear in the process. When it comes to solutions for these struggles, Artificial Intelligence (AI) tools could be an answer. This study aims to understand this relationship, as there is little to no academic attention towards AI solutions for collaboration in the SC. Purpose: The purpose of this study is to investigate how AI technologies can influence collaboration between SC partners, as well as to understand which could be the outcomes of an AI mediated SC collaboration. Furthermore, the intent is to summarize the findings into a framework for better visualization. Method: To fulfill the purpose of the study, an exploratory qualitative study has been conducted using 13 qualitative interviews with managers and highly skilled individuals in SC, while using an inductive approach. Finally, the data has been analyzed and interpreted using a thematic analysis, which resulted in five dimensions: information automation, AI aided human based decisions, AI based decisions, incentive alignment automation and outcomes of AI mediated collaboration. Conclusion: The study presented a new framework that explains the new dynamic relationship between the AI affected collaboration elements, with information automation sitting at the roots and coordinating the process. Furthermore, by automating information flows, forecasts and analyses could also be automated, making the incentive automation and decision making elements faster and better focused on real data, thus strengthening the outcomes of the collaboration. Lastly, an AI mediated collaboration could affect the trust among partners, as well as how power dynamics work in a partnership.