This Master's thesis assesses how to extend a higher-level developmental method for trustworthy artificial intelligent systems, ECCOLA, by evaluating it with Information Governance principles. Artificial intelligent systems are ubiquitous, with their application prevalent in virtually all sectors. In addition, Artificial intelligent systems rely on data and information they collect from users for their development. These issues have prompted ethical concerns, especially as their usage crosses boundaries in sensitive areas such as health, transportation, and security, calling for better governance. As such, there is a need for developing ethical artificial intelligent systems with effective governance that users can trust with their information. Several guidelines exist to help facilitate these developments; however, very few transition into methods with virtually no method existing for higher-level development methods. ECCOLA is proposed as a solution in transitioning from guidelines to development methods at higher levels. The study extends ECCOLA by evaluating its ethical tenets with Information Governance principles (Generally Accepted Recordkeeping Principles, GARP®) as a governance framework to improve its robustness in line with ethical guidelines. This was accomplished by following the Design Science Research methodology approach using a conceptual framework based on ethical guidelines of the European Commission and content analysis. The findings reveal a vulnerability of the GARP® principles of Retention and Disposition in ECCOLA. A possible solution artifact has been developed, which remains to be tested.