Climatiq AI Carbon Computing Capabilities and Customer Enterprise Scope 3 Emission Reduction Potential Identification—a Single-Case Process Tracking Based on Climatiq Embedded in The Thyssenkrupp Rasselstein Logistics Process via Celonis.

Abstract

This paper focuses on the cross-organizational carbon information transfer between carbon data provider Climatiq and client company thyssenkrupp Rasselstein. Based on organizational information processing theory, this paper aims to analyze how Climatiq's AI carbon computing capabilities are translated into thyssenkrupp Rasselstein's transportation and procurement processes via the Celonis platform, supporting the client company in identifying Scope 3 emission reduction potential. The study finds that Climatiq does not directly change physical emissions, but first transforms the client company's fragmented transportation data into system-accessible kgCO2e information assets, then embeds them into the client company's ERP/TMS and process intelligence scenarios, making them decision variables in areas such as route optimization. Public case data shows that this application can identify considerable carbon emission reduction potential for client companies. The theoretical contribution of this paper lies in extending organizational information processing theory from intra-organizational information processing to the cross-organizational carbon information transfer context between "AI carbon computing provider—client company," and proposing mechanisms for carbon information assetization, platform translation, and client decision embedding.