AI in Enterprise Architecture

Offentlig prosjektsammendrag

Enterprise Architecture (EA) builds a dynamic, connected ‘Digital Twin of the Organization’ (DTO) as the basis for a holistic approach to enterprise governance and transformation planning. And while EA methodologies are mature, historically the scope, complexity, effort and time-to-value for implementing them has limited EA’s value and its ability to realize its full potential in guiding the governance and transformation of complex organizations. Artificial Intelligence (AI) offers the opportunity to automate significant proportions of the EA process - for example integrating data to build the DTO, analyzing it to understand the impacts of change on complex business processes and technology estates, and even generating and analyzing different organizational change scenarios - for example, a mergers versus a divestiture, or a cloud migration versus refresh of on-premise infrastructure. The objective of this project is to learn how AI can be leveraged and applied to enterprise architecture in a holistic manner. We propose to do this by identifying points in the end-to-end EA process where AI can be a value driver, then using iterative build-test-learn of both individual product solutions and best-practices to test our hypotheses with customers in real-life governance and transformation scenarios. Our objective is both to develop, test and validate the technology approaches and methodologies for applying AI to enterprise architecture processes in support of organizational governance and transformation; and also to establish a sustainable and ongoing AI capability that can continue to innovate, deploy and learn beyond the lifetime of the project. The result, we believe, will be the ability to realize a ‘step-change’ in capability and of EA’s ability to realize value for complex organizations wrestling with the problems of governance and change.